E4D-Compare Software for Dental Analysis

E4D-Compare Software for Dental Analysis ABSTRACT Aim: The E4D-Compare software is an innovative tool that provides immediate feedback to students’ projects and competencies. It should provide consistent scores even when different scanners are used which may have inherent subtle differences in calibration. This study aimed to evaluate potential discrepancies in evaluation using the E4D Compare software based on four different NEVO scanners in dental anatomy projects. Additionally, correlation between digital and visual scores was evaluated. Methods: Thirty-five projects of maxillary left central incisors were evaluated. Among these, thirty wax-ups were performed by four operators and five consisted of standard dentoform teeth. Five scores were obtained for each project: one from an instructor that visually graded the project and from four different NEVO scanners. A faculty involved in teaching the dental anatomy course blindly scored the thirty-five projects. One operator scanned all projects to four NEVO scanners (D4D Technologies, Richardson, TX, USA). The images were aligned to the gold standard, and tolerance set at 0.3 mm to generate a score. The score reflected percentage match between the project and the gold standard. One-way ANOVA with repeated measures was used to determine whether there was a significant difference in scores among the four NEVO scanners. Paired-sample t-test was used to detect any difference between visual scores and the average scores of the four NEVO scanners. Pearson’s correlation t est was used to assess the relationship between visual and average scores of NEVO scanners. Results: There was no significant difference in scores among four different NEVO scanners (F(3, 102)=2.27, p=0.0852 one-way ANOVA with repeated measures). Moreover, the data provided strong evidence that a significant difference existed between visual and digital scores (p=0.0217; a paired-sample t-test). Mean visual scores were significantly lower than digital scores (72.4 vs. 75.1). Pearson’s correlation coefficient of 0.85 indicated a strong correlation between visual and digital scores (p Conclusion: The E4D Compare software provides consistent scores even when different scanners are used and correlates well with visual scores. KEYWORDS Computer-assisted learning/computer-assisted simulation (CAL/CAS), Dental anatomy, E4D Compare software CLINICAL SIGNIFICANCE The use of innovative digital assessment tools in dental education is promising with the E4D Compare software correlating well with visual scores and providing consistent scores even when different scanners are used SHORT RUNNING TITLE Innovative Digital Assessment Tool INTRODUCTION Dental anatomy is a course given to the first year dental students at the University of Iowa College of Dentistry Dental Clinics (UICOD) with the purpose of providing students with basic knowledge on dental anatomy and dental terminology to serve as a solid foundation for the following courses throughout their school years. It is designed to develop the psychomotor skills necessary to proficiently reproduce tooth contours in wax to be able to apply these skills in their future clinical practice. Students are challenged with four waxing projects during the course. Evaluation of these projects and providing proper feedback for self-assessment to establish life-long learning are still major issues that need to be addressed in the dental anatomy course. Traditionally faculty members involved in the course have used a pre-established checklist (Table 1) to provide ongoing feedback during the course, and also to determine the grade by adding points related to specific criteria. This visua l evaluation is time consuming and limited by grader fatigue, subjectivity, and inconsistency.1 The inconsistency among different faculty members is also the most frequently noted concern from student feedback after the course that may negatively affect students’ learning process and performance.2 Computer assisted learning and grading tools have been introduced recently and have shown great promise in providing not only objectivity to the grading system, but also reducing the workload of faculty.3 A digital device using blue laser technology (Nevo scanner, D4D Technologies, Richardson, TX, USA) offers high scanning image quality at a fast video-rate speed and ease of use. A laptop computer connected to the E4D Design Center provides rapid processing of the scans. Through this new technology, students can generate a high quality 3-D virtual model of their project and receive immediate feedback on discrepancies by comparing it to the gold standard determined by the course director.4 An ideal ratio in a dental classroom setting is to accommodate one scanner for every ten students.3 Therefore multiple scanners are usually used to facilitate proper teaching and learning experience for all students. It is expected that consistent scores will be obtained even when different scanners are used which may have inherent subtle differences in calibration. However, with the recent introduction of this digital technology, there is a lack of information on how accurately different scanners relate to each other, as well as lack of evidence on how well visual scores by faculty correlate to scores generated by the digital assessment technique. This study aimed to explore potential discrepancies in evaluation in dental anatomy projects using the E4D Compare software based on four different NEVO scanners. Additionally, correlation between digital and visual scores was evaluated. The hypotheses tested were that: first, the E4D Compare software will provide consistent grades even wh en different scanners are used, and second, there will be no correlation between visual and digital scores. MATERIALS AND METHODS The study was determined to be a non-human subject research project by the Institutional Review Board of the University of Iowa. Dental Anatomy Wax-Up of Tooth #9: The maxillary left central incisor (#9) was used for the evaluation of this study. Four operators (Junior dental students) independently waxed up a total of thirty projects based on the wax-addition technique described in the UICOD Dental Anatomy Manual. The maximum time allowed for the wax-up was 3 hours, which is also the time allotted to students during their waxing competency in the Dental Anatomy course. Additionally five dentoform teeth of tooth #9 (Kilgore model, Nissin Dental Corp., Tokyo, Japan) were included for evaluation. The original Kilgore typodont tooth also served as the gold standard for evaluation purposes. Five scores were obtained for each project: one from an instructor and four from NEVO scanners 1 to 4 Visual Evaluation of Wax-ups and Typodont Teeth: A faculty member involved in teaching the dental anatomy course was blinded and scored all thirty-five projects based on the check-list of the UICOD Dental Anatomy Course (Table 1). The check-list consisted of three categories including: contact areas, embrasure and line angles; facial and lingual contour; incisal edge and surface finish, adding up to a total of 23 criteria. Based on the addition of correct criteria the final score was converted to a percentage score for evaluation purposes. Scanning and Digital Evaluation: One operator started the set-up of the files and scanned all projects to four NEVO scanners (NEVO 1 to 4, D4D Technologies, Richardson, TX, USA). The images were checked for proper data density and then aligned to the gold standard, with the tolerance level set at 0.3 mm to generate a general score (Figs 1-6). This score reflected the percentage match between the project and the gold standard as calculated by the software. Data Analysis: One-way ANOVA with repeated measures was used to determine any significant differences in scores among four NEVO scanners. Paired-sample t-test was conducted to detect any difference between visual grades and the average grades of four NEVO scanners. Pearson’s correlation test was used to assess the relationship between visual grades and average grades of NEVO scanners. All tests utilized a 0.05 level of significance, and statistical analyses were performed using the statistical package SASÂ ® System version 9.3 (SAS Institute Inc., Cary, NC, USA). RESULTS Thirty-five teeth were used for this study. Five scores were obtained from each tooth with five different methods; one from an instructor and four from the NEVO scanners. Table 2 presents a summary of descriptive statistics on scores by the five evaluation methods. (1) Detecting the difference in scores among the four NEVO scanners The data were analyzed using the one-way ANOVA with repeated measures. This analysis revealed no significant difference in scores among the four scanners (p=0.0852). (2) Detecting the difference in scores between visual and NEVO evaluation methods There was a significant difference in scores between visual and NEVO evaluation methods (p=0.0217; a paired-sample t-test). The data revealed that the mean scores from visual evaluation method were significantly lower than those obtained from the NEVO evaluation method (mean score: 72.4 vs. 75.1) (Table 2). Note that the average scores of four scanners (NEVO_AVE) were used for the comparisons. (3) Assessing the correlation between visual and NEVO grading scores Based on both Pearson’s correlation test, the data provided strong evidence that there was a significant correlation between visual and NEVO evaluation scores (p DISCUSSION Digitization through innovative technology has become an integral part of contemporary dental practice. This trend is manifested by the increased use of computer-aided design and computer-aided manufacturing (CAD/CAM) technology that promotes the same day preparation and same day delivery concept. Despite intense initial debate, the adoption of restorations fabricated using this approach has profoundly benefited both clinical dentistry and dental laboratories, and epitomizes one of the earliest successes of digital dentistry.5,6 Given the success of CAD/CAM approaches in the clinical setting, many dental institutions are currently striving to incorporate computer-assisted learning and computer-assisted simulation (CAL/CAS) systems into their curriculum. This is to teach dental students to be abreast with the latest technology and keep them prepared for the dynamic changing environment they may face in their future practice. At the UICOD, active incorporation of new technology has bee n perceived to be of high priority. A Technology Committee has been established to plan for active implementation of digital dentistry into the curriculum to provide appropriate vertical and horizontal integration of these concepts as students progress from freshmen to senior years. As part of the planning process, importance has been placed on accumulating evidence on the validity and benefits of using digital technology in the pre-clinic simulation clinic. The study reported here attempted to address these issues, and was designed to evaluate the validity of using multiple scanners and the correlation between visual evaluation performed by faculty and the evaluation by the digital assessment tool. Based on the results, our first hypothesis was accepted: the E4D Compare software provided consistent scores even when different scanners were used. This reflects that the four NEVO scanners used were properly calibrated and the operator was able to create good data density virtual models that generated consistent scores for each project evaluated. This is relevant to other studies that evaluated the repeatability of digital evaluation with the use of the same scanner at different time points and showed excellent intra class correlation of 0.93 to 0.98.3,4 However, excellent repeatability does not necessarily indicate valid evaluation as good samples from the visual paradigm could consistently be graded as poor samples in the digital paradigm and vice versa. Therefore, the correlation of visual and digital evaluation scores was used to examine this possibility. Based on the results, our second hypothesis was rejected; there was strong correlation between the visual and digital scores . This partly supports the validity of the use of digital technology in assessing students’ projects and suggests that this tool could also be used for official grading in competencies as high grades were consistently graded as high and low grades as low across the two methods. It is important to note that there was a significant difference in scores between visual and NEVO evaluation methods with scores from the visual evaluation being lower than that obtained from the digital evaluation method. Changing the tolerance level and giving more leeway for the digital evaluation method could compensate for this difference. Implementation of digital assessment tools in the dental pre-clinic seems promising. However, there are still many issues to be addressed to justify the financial investment and time needed to introduce this system into the curriculum. A systematic review of the effectiveness of computer-aided, self-instructional programs in dental education has revealed disparate outcomes, with some studies finding no difference between CAL and other learning strategies, and others indicating the opposite thus that CAL provided a significant advantage in terms of knowledge gain.7 This is an important issue that needs to be explored in future studies with regards to the use of digital assessment tools as a self directed learning tool. Will the use of these devices indeed increase the technical performance of students? Furthermore, in order to integrate new technology into the curriculum, institutions need to formulate a strategic plan and find resources for proper faculty training so that instructors involved with teaching this new technology can share a positive enthusiasm, and not perceive this as an additional burden in terms of their efforts and time. Lastly, it is critical that students are encouraged to take responsibility for their own learning.8 As such, students’ perspective in new technology implementation is vital and should be taken into consideration. Therefore, more information on whether students regard this technology helpful in preparing them for their future professional life and contributes significantly to their development remains to be probed. CONCLUSION Within the limitations of this study it can be concluded that the E4D Compare Software provides consistent grades even when different scanners are used and correlates well with visual scores.

Effect of Temperature on Enzyme Catalase Activity in a Potato

Effect of Temperature ( C ? ) on Enzyme Catalase Activity in potato Aim: To investigate the Effect of temperature (10, 37, 60) Celsius (C ? ) on enzyme catalase activity in potato using 2% of hydrogen peroxide (H202) as the substrate measuring the height (cm) of oxygen gas (bubbles) and calculating the volume of oxygen bubbles produced (cm3) Introduction: Enzymes are biological catalysts that speed up metabolic reactions without being affected. They lower the activation energy needed to start a reaction. Enzymes are affected by several factors including PH, Substrate concentration; Temperature & other factors.Each enzyme has an optimum temperature at which its activity is the highest, below this optimum temp, the kinetic energy of molecules decrease , therefore the collisions between the active site of the enzyme and substrate decreases , as a result the enzyme activity will decrease , so decreasing the rate of the reaction If the temp. Exceeds the optimum temp. The kinetic energy be tween molecules increase therefore collisions increase leading to the change in the tertiary structure of the enzyme and in this case active site is lost and the enzymes will be denatured so the reaction will slow down &stops.Catalase is an enzyme, found basically in all living cells. It breaks down hydrogen peroxide (waste product) into water and oxygen. 2H? O? 2H2O+O2 As predicted, the enzyme catalase activity would be the highest at 37c ? (Optimum temp. )if increased to 60c ? then the enzyme would be denatured and if decreased to 10c ? (very low temp. ) then the reaction would be slow. Variables: Dependent: Height of oxygen bubbles (cm) using a ruler. Independent: Temperature (10c ? , 37c ? , 60c ? ) using three different water baths each adjusted to a specific temp . Controlled: 1.Number of potato cubes: 3 cubes of potatoes were used in each trial at each different temp. If changed, whether decrease or increase, then the number of enzymes (active site) available would change, th erefore affecting the rate of the reaction. 2. Size of potato cubes with dimensions 1cmx1cmx1. 5cm . This is controlled by cutting all potato cubes with same dimensions using a ruler & a cutter. If changed, then this would affect the rate of enzyme activity, therefore affecting the results. 3. Volume of hydrogen peroxide: 15cm3 of hydrogen peroxide was measured using graduated cylinder for each trial at different temp.If changed then the rate of enzyme activity would change, therefore results won’t be accurate. 4. Concentration of hydrogen peroxide: 2% of hydrogen peroxide was used through all trials this is prepared by adding 20cm3 of H2o2 to 1000cm3 of water. If changed it would affect the rate of enzyme activity since substrate concentration is one of the factors that affect enzyme activity. 5. Volume of liquid detergent: 2drops of liquid detergent were added to each test tube throughout the experiment. If changed, then this will affect the height of oxygen bubbles measure d cm3 therefore the results won’t be accurate. . Time: time was recorded for 2 minutes; if changed this will affect the results. Materials: * 27 cubes of potato each with dimensions 1cmx1cmx1. 5cm. * 15cm3 of 2% hydrogen peroxide for each trial. * 9 test tubes * Water adjusted to (60c ? ,37c ? &10c ? adding ice) * 2drops of liquid detergent in each test tube * Cutter * Ruler * 100cm3 graduated cylinder * Stopwatch * 1000cm3 volumetric flask * 50cm3 beaker Procedure: 1. Use the cutter, and ruler to cut 27 cubes of potato with dimensions 1cmx1cmx1. 5cm 2. Adjust the water bath temp one at 60c ? , the other one at 37c ? amp; last one at 10c ? adding ice. 3. Place 3 potato cubes in each of the three test tubes placed at 10c ?. 4. Leave the test tubes at 10c ? for 10min. 5. Add 2 drops of detergent for each test tube. 6. Measure 15cm3 of 2% hydrogen peroxide for each test tube using graduated cylinder. 7. Add 15cm3 of 2% H2o2 to each test tube, and immediately start the stop watch recording time for 2 min. 8. After 2 min exactly, use the ruler to measure the height of oxygen bubbles (cm). 9. Repeat steps 3 to 8 at a different temp (60c ? ,70c ? ). 10. Record all data in an organized table. Processing and Presenting Data: Table (1): Shows the height of oxygen bubbles produced (cm) at different temp. (C ? ) TemperatureC ?  ± 0. 05| Height of oxygen bubbles produced after 2 minutes (cm)| | Trial 1| Trial 2| Trial 3| 10. 00| 2. 00| 6. 00| 2. 00| 37. 00| 3. 00| 4. 50| 1. 50| 60. 00| 3. 00| 2. 00| 2. 00| Table (2): Shows mean height in (cm) for oxygen bubbles  ± 0. 05 and volume of oxygen bubbles (cm3) ±0. 05 at different temp (C ? ) Temperature C ?  ± 0. 05| Mean height (cm) for oxygen bubbles  ± 0. 05| Volume of mean height of oxygen bubbles cm3 0. 05| 10. 0| 3. 33| 16. 34| 37. 00| 4. 86| 23. 84| 60. 00| 2. 06| 10. 11| * Sample calculations 10c ? 1. Mean height of oxygen bubbles in cm. T1+T2+T33= 2+6+23= 3. 33cm 2. Volume of oxygen bubbles cm3 Volume o f cylinder: ? r2xh 3. 14x (1. 25)2Ãâ€"3. 33=16. 34cm3 Discussion: As shown in table (2) as temperature increased from 10c ? to 37c ? , the mean height in cm of oxygen bubbles increased from 3. 33cm to 4. 86cm. Aa temperature increase from 37c ? to 60c ? the mean height cm of oxygen bubbles decreased from 4. 86cm to 2. 06cm. Reffering to the table (2) and graph , as temp. ncreased from 10c ? to 37c ? the volume of oxygen bubbles (cm3) increased from 16. 34cm3 to 23. 84cm3. As temp increased from 37c ? to 60c ? the volume of oxygen bubbles produced (cm3) decreased from 23. 84cm3 to 10. 11cm3. Each enzyme has an optimum temp. at which the rate of enzyme activity is the highest. Above the optimum temp the kinetic energy of molecules increases therefore the collisions between the active site and the substrate increase and as a result the enzyme would lose its 3D structure and active site and the enzyme would be denatured.This is shown in the graph, as the volume of oxygen bubbles cm3 de creased from 23. 84cm3 to 10. 11cm3 at 60c ?. Below the optimum temp the kinetic energy of molecules decreases ,therefore the collisions decrease and the enzyme would slow down and the rate of energy decreases as it’s shown in table (2) the volume of oxygen bubble decrease from 37c ? to 10c ?. According to our results in table (2) and graph, the optimum temp was 37c ? at which rate of enzyme catalase activity was the highest as the highest volume of oxygen bubbles was produced 23. 84cm3.The results obtained matched the hypothesis which stated that 37c ? is the optimum temp for enzyme catalase to break hydrogen peroxide which is a toxic product into water & oxygen. Evaluation & Improvements: 1. Size of potato cubes . Potato cubes were cut into cubes of dimensions 1cmx1cmx1. 5cm using a ruler and a blade which was a source of error since all cubes vary slightly in size which means the concentration of catalase enzyme is different. A potato cutter that cut the potato into equal sizes . 2. Height of oxygen bubbles measured by a ruler. This was inaccurate method.Volume could be measured instead in height using gas Syringe which will give more accurate results 3. Volume of detergent. 2 drops of detergent were measured using a dropper. A pipette can be used which will give more accurate results. Done BY: JIHAN AL-BUKHARI 9A ——————————————– [ 1 ]. [ (Jones, 2009) ] [ 2 ]. â€Å"Introduction to Enzymes. †Ã‚  Factors Affecting Enzyme Activity (). N. p. , n. d. Web. 16 Nov. 2012. . [ 3 ]. â€Å"Effect of Temperature on Enzyme Activity. †Ã‚  Effect of Temperature on Enzyme Activity. N. p. , n. d. Web. 16 Nov. 2012. .

Gilbert’s short story “The yellow wallpaper” Essay

Gilbert’s chronical of her own descent into madness is set in a remote, isolated older home, with very beautiful surroundings, and more in particular and old nursery in which Gilbert is imprisoned for her own â€Å"sanity†. The ironic point is that it is the cure for her † insanity† that creates the insanity she ultimately adopts. The narrator is a repressed woman with nowhere to go except madness. As a parallel to Kate Chopin†s † Story of an Hour† in which death was the escape to freedom, Gilbert emphasizes that the narrators only escape to freedom was madness. The story is divided into time frames with each period detailling her descent into madness. In the first section it is wise to note that both John and her brother are prominent physicians and believe that she needs to be unstimulated in order to overcome post-partum depression, as was practiced by such prominent theorist as Sels Weir Mitchell, who was in fact Gilbert’s own physician at the time the story was written. ( as a side note: It is of interest to note that after reading Gilbert’s account of her own feelings in this short story, Wier Mitchell discontinued the use of â€Å"rest therapy†.) We discover in later time frames that John is in denial of his wife’s deteriorating medical condition, mainly as a result of the societal stigma’s of mental illness and the affluence of his status. The room that is the primary setting is very institutionalized and unstimulating. There is this dilapitated, detoriorating, smelly, yellow wall paper with a design representative of Gilbert’s madness, that eventually becomes her savior. As she succumbs to dymentia, the narrator has hallucinations of a women behind the wallpaper. The narrator becomes convinced this woman is â€Å"trapped† by the wallpaper but yet, manages to successfully â€Å"escape† even if only to slink around the shrubbery. The narrator identifies with the delusions, eventually forging with the delusion, making the separation of one from the other impossible. She describes in detail the horror of those around her as they become to realise the extent of the mental illness hidden in the narrator. The speaker  makes reference to feelings of paranoia that John and Jenny are going to somehow intrude on the relationship she has with the wallpaper, and admits that she liked the room inspite of the wallpaper, no because of the wallpaper. The wallpaper represent to the narrator., a chance for freedom and the cost was insanity, just as the intricate design that was a crime against all the rules of design that had been implied upon first consideration.

Personal Response- Forrest Gump (Film) - 1528 Words

TITLE: Forest Gump DIRECTED BY: Robert Zemeckis TEXT TYPE: Film DATE FINISHED: 06-04-14 *Note: Read all quotes in a thick, Alabama accent. This film follows the life of Forest Gump who struggles to live outside the barriers that society has given him. Forrest is a little slow; although his mental impairment doesnt seem to bother him. In fact, the naivetà © that comes from his limited understanding of the world around him gives Forrest a uniquely positive perspective of life. Forest overcomes the challenges in his life, becoming a star football player, a war hero, a successful businessman, and something of a pop icon. Through it all, however, there is one defining element in his life: his love for Jenny. She is never far from his†¦show more content†¦I believe that the character Forrest Gump teaches me to treasure the moments in my life and to understand why Im doing what Im doing. Especially in scenarios that can affect other people. He is some sort of inspiration to me; this is however not in the usual context. He inspires me to never enter situations where I do not fully comprehend nor understand the consequ ences of my actions, he inspires me to never let someone take advantage of me and he inspires me to just simply, be me. Throughout the entire film we see Forest Gumps tragic life; nearly everyone he holds most dear to him dies. Life can be brutal at times, I found myself crying during the moments when Forrests life seemed painfully hard. In some ways I could see that with every loved one that hed lost a part of him had died with them. I can understand this feeling as my best friends father passed away only three years ago this month. As she is growing up, she is realising the disadvantages of not having him with her, knowing that he is not there to teach her how to drive or help her get her first job. I see her pain and I know that there is nothing I can do to stop it, I am powerless. 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