Summary of Common Misunderstandings

This study implemented a data-driven approach to identify Chinese high school students’ common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students’ error-related behaviors were also analyzed, and their relationships to success in introductory programming were investigated. This study identified 15 common compilation errors and 6 common test errors. The results showed that these common errors accounted for a large proportion of all errors, so identifying the common errors is important to help students succeed in introductory programming courses. Based on these common errors, five underlying student difficulties were identified and are discussed. In addition, after analyzing existing measures of students’ error-related behaviors, we developed a measure called improvement rate to quantify students’ success in fixing errors. The results of our study suggest that students’ competence of improving code is important to their success in introductory programming. We recommend researchers design and develop automated assessment tools that provide feedback messages for common student errors and instructors who explicitly teach knowledge and skills of improving code in class.

Metabolic state of the nation: Results of the national family health survey-4.

To investigate common TBI misconceptions among ethnic minorities with TBI. Cross-sectional study. Level I trauma center. Fifty-eight persons with TBI (28 black and 30 Hispanic) discharged from the neurosurgery unit and living in the community. Forty-item Common Misconceptions about Traumatic Brain Injury Questionnaire (CM-TBI). Participants displayed misconceptions about approximately one-third of the 40 items, most regarding amnesia and recovery. Fewer misconceptions were found in the brain damage/injury and sequelae categories. A greater percentage of TBI misconceptions was associated with having lower education, actively practicing religion, being Spanish-speaking and non-US born. After controlling for education and actively practicing religion, Spanish-speaking Hispanics reported a greater percentage of misconceptions than English-speaking Hispanics and blacks. Understanding common TBI misconceptions can assist rehabilitation staff in tailoring education programs for racial/ethnic minorities including those who are Spanish-speaking. Educational attainment and cultural factors should be considered when developing educational interventions for persons with TBI from diverse backgrounds. Inaccurate information regarding TBI, especially the recovery process, may hinder treatment planning by rehabilitation professionals and may result in disappointment and the setting of unrealistic goals for persons with injury and their families.

Sugar intake in infancy in early childhood is an area of investigation with surprisingly few studies, with most of the research done in adults. The aim of this study was to determine whether early vs. late introduction of solid foods and commercially prepared (CP) vs. parents choice (PC) of solid foods affects sugar intake. Based on adult data, we hypothesized that children with high sugar intakes will compensate their total calorie intake with lower fat; high sugar will be weakly correlated with high lean mass, and a high early sugar intake will result in a high intake later. Term infants (n=175) were recruited prior to 3 mo and randomly assigned to receive: 1) CP from 3-12 mo 2) CP from 6-12 mo 3) PC from 3-12 mo or 4) PC from 6-12 mo. Body composition, anthropometrics and 3-d diet records (Univ of Mn Nutrient Database) were completed at 3, 6, 12 and 24 mo. At 12 mo, total sugar intake was greater in late vs. early group when adjusted for weight (84.0 + 2.5g vs. 75.7 + 2.4g, p=0.02), but this effect did not persist to 24 mo. There was no difference in total sugar intake between CP and PC at either 12 or 24 mo (both p≥.05). At 12 and 24 mo, total sugar intake was correlated with total fat intake (both p≤.001) even when adjusted for weight. Total sugar intake at 12 and 24 mo was correlated with lean mass (p=.9 and p=.06). Additionally, 24 mo sugar intake/kg was positively correlated with total sugar intake/kg at 12 mo, p≤.001. Unlike adult data that shows a calorie compensation effect (an inverse relationship between consumption of calories from sugar and fat) the 12 and 24 mo data show positive correlations between high sugar and high fat intake. In addition, there was no correlation between sugar intake and lean mass at 12 or 24 mo. High sugar intake/kg at 12 mo is positively correlated with high sugar intake/kg at 24 mo suggesting a developing pattern of sweet preference. Infants developing a sweet preference may “pattern” their eating habits for later in the toddler years for sugar and fat intake.

To investigate the relationships between children's food and drink choices at school lunch for children who consume high and low sugar intakes at home. Children's food and drink consumption at home was assessed using diet diaries over three consecutive days. Children were classified as 'high' or 'low' sugar consumers at home using the WHO recommendation that free sugars should be less than 10 % of their daily total energy intake. A purposive sample of children was then selected and observed during school lunch, recording food selections, food left on plates and content of packed lunches. Six primary schools in Newham and Kent, England. Parents and children aged 6-7 years. Seventy-one parents completed diet diaries. From the seventy-one, thirty-nine children were observed during school lunch. Twenty children were high sugar consumers, nineteen children were low sugar consumers; thirty-one children had a school meal. Eleven of the fifteen children (73 %) who had school meals and who were high sugar consumers selected a high-sugar dessert rather than fruit. Only five of the sixteen (31 %) children who had school meals and were low sugar consumers at home chose a high-sugar dessert. Most of the children who had packed lunches had sweet items, despite school policies. Children who consumed high sugar intake at home tended to select foods high in sugar for school meals or had packed lunches containing high-sugar foods. The implications for public health programmes include healthy eating workshops and implementing school food policies.

Employees working at night are at increased risk of diabetes. A possible mechanism is related to differences in glucose regulation at night. Laboratory simulated night work studies show regulation of blood glucose is impaired at night. Regular exposure to high glucose levels at night may explain the observed relationship between night work and diabetes. We performed a field study of 19 nonsmoking women from the health-care sector to investigate how night work and the composition of meals affect post-prandial blood glucose levels. Blood glucose levels were self-assessed by finger-prick blood sampling using the Beurer blood glucose monitoring system. Measurements were done before and 15, 30, 60, and 120 min after different test meals: a nighttime high sugar meal during a night shift and during a day shift, and a reference (low sugar) meal under these same two conditions. There was a statistically significant difference in blood glucose concentration between the four test meal conditions (P = .0086). Post-meal blood glucose levels following the night-shift meals, compared to following daytime meals, rose faster and remained elevated for longer a duration of time. At the 15 min time point following the high sugar test meal, the blood glucose concentration was 8.3 mmol/L when consumed at night vs. 7.3 mmol/L when consumed during the day. We found no difference in area under the blood glucose concentration–time curve (AUC) after consumption of the high or low sugar test meals during the night shift compared with consumption of them during the day. Our findings indicate the glucose levels in response to food intake by female night working healthcare assistants are higher following the nighttime compared with daytime consumption of a high sugar content meal. However, we did not find a difference in total glucose exposure across time (assessed as AUC) after eating a high vs. low sugar meal during the night shift.

The near-infrared (NIR) spectral properties of cereal products containing high fat or high sugar can differ substantially from the spectral properties of other cereal products. An existing NIR model, using preprocessed reflectance spectra and partial least-squares analysis, for the prediction of total dietary fiber in cereal products was expanded to two new models called (1) the “fat-expanded” model and (2) the “fat- and sugar-expanded” model. The fat-expanded model enlarges the existing model with high-fat-content products as calibration samples, and the “fat- and sugar- expanded” model also includes products with high sugar and high crystalline sugar content. The dry milled cereal and grain products were analyzed in the laboratory according to AOAC method 991.43 for the determination of total dietary fiber, and NIR reflectance spectra were collected with a scanning monochromator. Data analysis and selection of representative high-fat and high-sugar samples were performed with a commercial analysis program. The two expanded models had standard errors of cross-validation and R2 similar to those of the existing model, with acceptable standard error of performance and r2 when tested with independent validation samples. The existing model was, thus, expanded to include high-fat, high-sugar, and high crystalline sugar cereal products while maintaining prediction accuracy. Keywords: Dietary fiber; near-infrared; chemometrics; cereal

Novices tend to make unnecessary errors when they write programming code. Many of these errors can be attributed to the novices’ fragile knowledge of basic programming concepts. Programming instructors also find it challenging to develop teaching and learning strategies that are aimed at addressing the specific programming challenges experienced by their students. This paper reports on a study aimed at (1) identifying the common programming errors made by a select group of novice programmers, and (2) analyzing how these common errors changed at different stages during an academic semester. This exploratory study employed a mixed-methods approach based on the Framework of Integrated Methodologies (FraIM). Manual, structured content analysis of 684 programming artefacts, created by 38 participants and collected over an entire semester, lead to the identification of 21 common programming errors. The identified errors were classified into four categories: syntax, semantic, logic, and type errors. The results indicate that semantic and type errors occurred most frequently. Although common error categories are likely to remain the same from one assignment to the next, the introduction of more complex programming concepts towards the end of the semester could lead to an unexpected change in the most common error category. Knowledge of these common errors and error categories could assist programming instructors in adjusting their teaching and learning approaches for novice programmers.KeywordsNovice programmerCommon programming errorsCS1Computer Science education

A novel free C-12 higher carbon sugar: asymmetric synthesis and reactivity with nucleophiles

INTRODUCTION: Inflammatory Bowel disease (IBD) management involves a delicate balance between medications, diet, and psychosocial care. Dietary factors like sugar consumption have been associated with disease onset. However, it is unknown how sugar intake complicates the medical regimen necessary to induce and maintain disease remission. We sought to characterize differences in IBD treatment regimens among patients with high and low sugar consumption and if medication patterns exist within subgroups that are in remission. METHODS: Using a longitudinal, prospective natural history of consented IBD patients, we meticulously tracked consented IBD patients at a large tertiary referral hospital. Sugar consumption was prospectively assessed using the 2005 National Health Interview Survey Diet and Questionnaire. Patients completed these questionnaires at routine outpatient appointments. The USDA estimates that the average American consumes 73 grams of added sugars on a daily basis. Patients who consumed above this average figure, were allocated to the high consumption group and those below comprised the low sugar consumption group. The primary outcome, medication use, was approximated using prescription data harvested from the electronic medical records. We focused on standard medications used in the management of IBD. We also conducted subgroup analyses to identify potential subpopulations with treatment patterns. Remission was defined as a score of ≤ 3 on the Harvey-Bradshaw index or ≤4 on the Ulcerative Colitis Activity Index. RESULTS: The study population consisted of 1259 adult IBD patients (70%CD, 30%UC, 57% Female). The median age was 40 years old. The mean sugar consumption of this study cohort was 71 grams. About 66% of patients had low sugar consumption while 34% of patients had high sugar consumption. High sugar consumption was associated with increased anti-TNF medication use, higher combination therapy use, and lower 5-ASA use. Among the subgroup of high sugar consumers, those not in remission used more adalimumab and steroids. Deeper analysis with only patients with Crohn’s Disease (CD), revealed differences in Azathioprine, 5-ASA, and steroid use. CONCLUSION: IBD patients consuming high sugar diets require more immunomodulator, biologic and combination therapy. These data suggest that optimal IBD treatment may benefit from incorporating nutritional counseling for healthy diet with low added sugar.Table 1Table 2Table 3

Application-oriented evaluated nuclear data libraries such as ENDF and JEFF contain not only recommended values but also uncertainty information in the form of “covariance” or “error files.” These can neither be constructed nor utilized properly without a thorough understanding of uncertainties and correlations. It is shown how incomplete information about errors is described by multivariate probability distributions or, more summarily, by covariance matrices, and how correlations are caused by incompletely known common errors. Parameter estimation for the practically most important case of the Gaussian distribution with common errors is developed in close analogy to the more familiar case without. The formalism shows that, contrary to widespread belief, common (“systematic”) and uncorrelated (“random” or “statistical”) errors are to be added in quadrature. It also shows explicitly that repetition of a measurement reduces mainly the statistical uncertainties but not the systematic ones. While statistical uncertainties are readily estimated from the scatter of repeatedly measured data, systematic uncertainties can only be inferred from prior information about common errors and their propagation. The optimal way to handle error-affected auxiliary quantities (“nuisance parameters”) in data fitting and parameter estimation is to adjust them on the same footing as the parameters of interest and to integrate (marginalize) them out of the joint posterior distribution afterward.

For many years scientists studied the piosphere concept- a grazing gradient around a natural/artificial watering point. As is the case for other kinds of ecological studies, the method of statistical analyses applied in many publications is not always appropriate. We note there are many statistical errors and misapplication of data analysis techniques. We reviewed 875 piosphere-related publications between 1915-2018 to find the common statistical methods and common statistical errors in the design of the study, data analyses, presentation of results, and interpretation of study findings. One-way ANOVA, multiple linear regression, Pearson correlation coefficient, permutational multivariate analysis of variance, canonical correspondence analysis, and mean were the most frequent statistical methods applied. Seventy-one common statistical errors in piosphere publications were found. The most common errors were not choosing the proper or appropriate statistical techniques, not checking the assumptions and diagnostics of statistical methods, partial and wrong interpretation of results, and not using informative figures and tables to help readers. Negligence to the proper application of statistics by researchers results in inaccurate interpretation and spurious conclusions. It is recommended researchers seek advice from statisticians at the early stages of research to save resources, time, and labor and to provide increased trust in recommendations and findings.

Research publications on the ketogenic diet have experienced an exponential increase in recent years, driving clinical interest, which has expanded along with media interest. The ketogenic diet, originally developed as an epilepsy treatment, has a broad range of applications that include metabolic disorders such as obesity, insulin resistance, and type 2 diabetes, and extends to a range of neurometabolic conditions such as neurodegenerative disorders and mental health conditions. The ketogenic diet promotes a state of nutritional ketosis that has unique benefits via multiple mechanisms. Heightened awareness of the potential benefits of a ketogenic diet has led to an increase in clinicians using this approach, and patients who are keen to explore this option may present having self-administered ketogenic diet therapy. Common misconceptions about the ketogenic diet abound on social media, causing confusion and distracting from its potential benefits, where nuance around diet quality and personalisation are key features of a successful implementation. By selecting common questions and misconceptions about the ketogenic diet from a social media platform, this article seeks to provide a concise, evidence-based guide to address these questions and support clinicians seeking to implement ketogenic diets in their practice.

Code completion problems are an effective type of formative assessment; especially, when used to practice newly learned concepts or topics. While there is a growing body of research in computing education on the use of large language models (LLMs) to support learning content development, the use of LLMs for producing high-quality code completion problems has not yet been explored. In this paper, we analyze the capability of LLMs to generate effective distractors (i.e., plausible but incorrect options) and explanations for completion problems. We utilize common student misconceptions to improve the quality of the generated distractors. Our study suggests that LLMs are capable of generating reasonable distractors and explanations. At the same time, we identify a lack of a sufficiently granular taxonomy of common student misconceptions that would be needed for aligning the generated distractors with the common misconceptions and errors -- a gap that should be addressed in future work.

The effect of high fat, high sugar, and combined high fat-high sugar diets on spatial learning and memory in rodents: A meta-analysis