A Comparison of Three-Dimensional Printing Technologies on the Precision, Trueness, and Accuracy of Printed Retainers

Purpose: The aim of this study was to evaluate the differences in the precision, trueness, and accuracy of 3D printed orthodontic clear retainers produced using printer systems with various printing technologies. Methods: Retainers (n=15) were printed using four different 3D printers: a stereolithography (SLA) printer, two different digital light processing (DLP and cDLP) printers, and a polyjet photopolymer (PPP) printer. The 3D printed retainers were transformed into a digital file through a cone-beam computed tomography scan that was compared to the original image using a 3D superimposition analysis software. At previously chosen landmarks (R6, L6, R3, L3, R1, L1) retainers were compared to the reference model. The intercanine and the intermolar width measurements were also analyzed for deviations between the samples and the original file. A discrepancy up to 0.25mm was considered clinically acceptable. Precision of printers was evaluated on 5 randomly chosen samples. Trueness was determined by comparing the measurements on printed retainers to those on the original image file. Root mean square (RMS) and percent of points within the tolerance level (inTOL) were also calculated with respect to precision and trueness for each retainer. Samples were analyzed for intra-printer reliability (precision), and inter-printer trueness. Statistical significance was set at P\u3c0.05. Results: Interrater correlation coefficient indicated good agreement and all measurements were within 0.10mm at least 95% of the time. Statistically significant differences were found between printer types among each of the 6 landmarks and the arch widths. When evaluating inTOL and RMS, statistically significant differences in both median precision and trueness among each printer type were found. SLA and PPP printing technologies exhibited both excellent precision and trueness. Conclusion: Retainers fabricated by SLA, DLP, cDLP, and PPP technologies were shown to be clinically acceptable and accurate compared to the standard reference file. SLA and PPP printers showed greater accuracy, and the DLP and cDLP printers exhibited greater precision. The PPP printer had the most accurate intra-arch measurements followed by the SLA printer, and therefore, based on their high trueness and precision values, were deemed to be the most accurate overall

Electrical transport and optical studies of ferromagnetic Cobalt doped ZnO nanoparticles exhibiting a metal-insulator transition

The observed correlation of oxygen vacancies and room temperature ferromagnetic ordering in Co doped ZnO1-o nanoparticles reported earlier (Naeem et al Nanotechnology 17, 2675-2680) has been further explored by transport and optical measurements. In these particles room temperature ferromagnetic ordering had been observed to occur only after annealing in forming gas. In the current work the optical properties have been studied by diffuse reflection spectroscopy in the UV-Vis region and the band gap of the Co doped compositions has been found to decrease with Co addition. Reflections minima are observed at the energies characteristic of Co+2 d-d (tethrahedral symmetry) crystal field transitions, further establishing the presence of Co in substitutional sites. Electrical transport measurements on palletized samples of the nanoparticles show that the effect of a forming gas is to strongly decrease the resistivity with increasing Co concentration. For the air annealed and non-ferromagnetic samples the variation in the resistivity as a function of Co content are opposite to those observed in the particles prepared in forming gas. The ferromagnetic samples exhibit an apparent change from insulator to metal with increasing temperatures for T>380K and this change becomes more pronounced with increasing Co content. The magnetic and resistive behaviors are correlated by considering the model by Calderon et al [M. J. Calderon and S. D. Sarma, Annals of Physics 2007 (Accepted doi: 10.1016/j.aop.2007.01.010] where the ferromagnetism changes from being mediated by polarons in the low temperature insulating region to being mediated by the carriers released from the weakly bound states in the higher temperature metallic region.Comment: 7 pages, 6 figure

Inferring destination from mobility data

Destination prediction in a moving vehicle has several applications such as alternative route recommendations even in cases where the driver has not entered their destination into the system. In this paper a hierarchical approach to destination prediction is presented. A Discrete Time Markov Chain model is used to make an initial prediction of a general region the vehicle might be travelling to. Following that a more complex Bayesian Inference Model is used to make a fine grained prediction within that destination region. The model is tested on a dataset of 442 taxis operating in Porto, Portugal. Experiments are run on two maps. One is a smaller map concentrating specificially on trips within the Porto city centre and surrounding areas. The second map covers a much larger area going as far as Lisbon. We achieve predictions for Porto with average distance error of less than 0.6 km from early on in the trip and less than 1.6 km dropping to less than 1 km for the wider area

NL-based automated software requirements elicitation and specification

This paper presents a novel approach to automate the process of software requirements elicitation and specification. The software requirements elicitation is perhaps the most important phase of software development as a small error at this stage can result in absurd software designs and implementations. The automation of the initial phase (such as requirement elicitation) phase can also contribute to a long standing challenge of automated software development. The presented approach is based on Semantic of Business Vocabulary and Rules (SBVR), an OMG’s recent standard. We have also developed a prototype tool SR-Elicitor (an Eclipse plugin), which can be used by software engineers to record and automatically transform the natural language software requirements to SBVR software requirements specification. The major contribution of the presented research is to demonstrate the potential of SBVR based approach, implemented in a prototype tool, proposed to improve the process of requirements elicitation and specification

Logistic regression analysis of employment behavior data using randomized response technique

Direct survey techniques deal with collecting information on sensitive issues data, such as induced abortion, drug addiction, and so on. RR (randomized response) techniques are available for many interviewees, who do not feel comfortable to disclose their personal data due to privacy risks. RR techniques are used in the estimation of the number of people having a sensitive attribute say A. When the research is conducted on the disgraceful or ignominious characteristics of persons like rash driving, tax elusion, induced abortion, testing HIV (human immunodeficiency virus) positive etc., RR techniques are used to make sure that the estimates obtained are efficient and unbiased. During these types of surveys, privacy of the respondent is also managed. Among others, the conflict between efficiency and protection of privacy was also discussed by Nayak in 1994. In RR-related techniques, the SRS (simple random sampling) is statistically used in the sample selection. In this paper, RR procedure is used that allows us to estimate the population proportion in addition to the probability of providing a truthful answer. This study also quantifies a method for the estimation of the model having one variable (univariate) while studying logistic regression, where the dependent variables are subject to RR. In addition, an efficiency comparison is carried out to investigate the performance of the proposed technique. It is also assumed that during the study, the respondents will respond keeping in view the instructions of the RR design. The general idea about findings of current study, though, is so as to perform RR techniques comparatively fine

Acute-on-chronic Liver Failure: MELD Score 30-day Mortality Predictability and Etiology in a Pakistani Population

Background: Cirrhosis is a pathological condition that ultimately leads to liver failure. Acute on chronic liver failure (ACLF) has a high short term mortality rate. Viral hepatitis is the most common cause of liver failure in our local population. We carried out this study to identity the 30-day mortality and etiology of patients presenting with ACLF using Model for End-Stage Liver Disease (MELD) score predictability. Methodology: This was a descriptive case series, conducted at Sheikh Zayed Hospital, Lahore, Pakistan from January 31, 2018 to July 30, 2018. One hundred and eighty five patients who met the inclusion criteria were enrolled using 95% confidence level and 4% margin of error. Data was entered and analyzed with SPSS version 23.0. Numerical variables including age was presented by Mean ± S.D. Categorical variables i.e. gender, etiology of acute-on-chronic liver failure and 30-day mortality were presented by frequency and percentage. Data was stratified for age, gender, duration of chronic liver disease and MELD grade to address the effect modifiers. Post-stratification chi-square test was calculated using 95% significance (p≤0.05). Results: Majority of the enrolled patients were male (74.6%) while only 25.4% of the patients were female. One hundred and thirty patients (70.3%) had underlying viral hepatitis while twelve patients (6.5%) and forty three patients (23.2%) presented with alcoholic liver disease and drug-induced ACLF, respectively. Eighty patients (43.2%) died within 30 days of admission.The 30-day mortality with respect to MELD grade was statistically significant (p<0.001) with the highest mortality noted in grade-IV and thirty five patients (43.8%) dying within 30 days of admission (p<0.001). Grade-II and III MELD scores also contributed to the 30-day mortality with twenty three patients (28.8%) and nineteen patients (23.8%) dying within 30 days of admission (p<0.001). Conclusion: MELD scores are able to accurately predict the short-term mortality in patients with ACLF and viral hepatitis was the most common etiology in our population. Early detection and use of appropriate prognostic models may alleviate mortality and morbidity in paitents with ACLF