Code Generation Based Grading: Evaluating an Auto-grading Mechanism for "Explain-in-Plain-English" Questions

Comprehending and elucidating the purpose of code is often cited as being a key learning objective within introductory programming courses. To address this objective ``Explain-in-Plain-English'' questions, in which students are shown a segment of code and asked to provide an abstract description of the code's purpose, have been adopted. However, given EiPE questions require a natural language response, they often require manual grading which is time-consuming for course staff and delays feedback for students. With the advent of large language models (LLMs) capable of generating code, responses to EiPE questions can be used to generate code segments, the correctness of which can then be easily verified using test cases. We refer to this approach as "Code Generation Based Grading" (CGBG) and in this paper we explore its agreement with human graders using EiPE responses from past exams in an introductory programming course taught in Python. Overall, we find that CGBG achieves moderate agreement with human graders with the primary area of disagreement being its leniency with respect to low-level and line-by-line descriptions of code

Investigating the Essential of Meaningful Automated Formative Feedback for Programming Assignments

This study investigated the essential of meaningful automated feedback for programming assignments. Three different types of feedback were tested, including (a) What's wrong - what test cases were testing and which failed, (b) Gap - comparisons between expected and actual outputs, and (c) Hint - hints on how to fix problems if test cases failed. 46 students taking a CS2 participated in this study. They were divided into three groups, and the feedback configurations for each group were different: (1) Group One - What's wrong, (2) Group Two - What's wrong + Gap, (3) Group Three - What's wrong + Gap + Hint. This study found that simply knowing what failed did not help students sufficiently, and might stimulate system gaming behavior. Hints were not found to be impactful on student performance or their usage of automated feedback. Based on the findings, this study provides practical guidance on the design of automated feedback

A Comparative Study of the ReCell® Device and Autologous Spit-Thickness Meshed Skin Graft in the Treatment of Acute Burn Injuries.

Early excision and autografting are standard care for deeper burns. However, donor sites are a source of significant morbidity. To address this, the ReCell® Autologous Cell Harvesting Device (ReCell) was designed for use at the point-of-care to prepare a noncultured, autologous skin cell suspension (ASCS) capable of epidermal regeneration using minimal donor skin. A prospective study was conducted to evaluate the clinical performance of ReCell vs meshed split-thickness skin grafts (STSG, Control) for the treatment of deep partial-thickness burns. Effectiveness measures were assessed to 1 year for both ASCS and Control treatment sites and donor sites, including the incidence of healing, scarring, and pain. At 4 weeks, 98% of the ASCS-treated sites were healed compared with 100% of the Controls. Pain and assessments of scarring at the treatment sites were reported to be similar between groups. Significant differences were observed between ReCell and Control donor sites. The mean ReCell donor area was approximately 40 times smaller than that of the Control (P < .0001), and after 1 week, significantly more ReCell donor sites were healed than Controls (P = .04). Over the first 16 weeks, patients reported significantly less pain at the ReCell donor sites compared with Controls (P ≤ .05 at each time point). Long-term patients reported higher satisfaction with ReCell donor site outcomes compared with the Controls. This study provides evidence that the treatment of deep partial-thickness burns with ASCS results in comparable healing, with significantly reduced donor site size and pain and improved appearance relative to STSG

Interactions with Prompt Problems: A New Way to Teach Programming with Large Language Models

Large Language Models (LLMs) have upended decades of pedagogy in computing education. Students previously learned to code through \textit{writing} many small problems with less emphasis on code reading and comprehension. Recent research has shown that free code generation tools powered by LLMs can solve introductory programming problems presented in natural language with ease. In this paper, we propose a new way to teach programming with Prompt Problems. Students receive a problem visually, indicating how input should be transformed to output, and must translate that to a prompt for an LLM to decipher. The problem is considered correct when the code that is generated by the student prompt can pass all test cases. In this paper we present the design of this tool, discuss student interactions with it as they learn, and provide insights into this new class of programming problems as well as the design tools that integrate LLMs.Comment: accepted for CHI 202

The role of childhood social position in adult type 2 diabetes: Evidence from the English Longitudinal Study of Ageing

Copyright @ 2014 Pikhartova et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background: Socioeconomic circumstances in childhood and early adulthood may influence the later onset of chronic disease, although such research is limited for type 2 diabetes and its risk factors at the different stages of life. The main aim of the present study is to examine the role of childhood social position and later inflammatory markers and health behaviours in developing type 2 diabetes at older ages using a pathway analytic approach. Methods. Data on childhood and adult life circumstances of 2,994 men and 4,021 women from English Longitudinal Study of Ageing (ELSA) were used to evaluate their association with diabetes at age 50 years and more. The cases of diabetes were based on having increased blood levels of glycated haemoglobin and/or self-reported medication for diabetes and/or being diagnosed with type 2 diabetes. Father's job when ELSA participants were aged 14 years was used as the measure of childhood social position. Current social characteristics, health behaviours and inflammatory biomarkers were used as potential mediators in the statistical analysis to assess direct and indirect effects of childhood circumstances on diabetes in later life. Results: 12.6 per cent of participants were classified as having diabetes. A disadvantaged social position in childhood, as measured by father's manual occupation, was associated at conventional levels of statistical significance with an increased risk of type 2 diabetes in adulthood, both directly and indirectly through inflammation, adulthood social position and a risk score constructed from adult health behaviours including tobacco smoking and limited physical activity. The direct effect of childhood social position was reduced by mediation analysis (standardised coefficient decreased from 0.089 to 0.043) but remained statistically significant (p = 0.035). All three indirect pathways made a statistically significantly contribution to the overall effect of childhood social position on adulthood type 2 diabetes. Conclusions: Childhood social position influences adult diabetes directly and indirectly through inflammatory markers, adulthood social position and adult health behaviours. © 2014Pikhartova et al.; licensee BioMed Central Ltd.Economic and Social Research Council-funded International Centre for Life Course Studies in Society and Health (RES-596-28-0001)

Simultaneous noninvasive recording of skin sympathetic nerve activity and electrocardiogram

BACKGROUND: Sympathetic nerve activity is important to cardiac arrhythmogenesis. OBJECTIVE: The purpose of this study was to develop a method for simultaneous noninvasive recording of skin sympathetic nerve activity (SKNA) and electrocardiogram (ECG) using conventional ECG electrodes. This method (neuECG) can be used to adequately estimate sympathetic tone. METHODS: We recorded neuECG signals from the skin of 56 human subjects. The signals were low-pass filtered to show the ECG and high-pass filtered to show nerve activity. Protocol 1 included 12 healthy volunteers who underwent cold water pressor test and Valsalva maneuver. Protocol 2 included 19 inpatients with epilepsy but without known heart diseases monitored for 24 hours. Protocol 3 included 22 patients admitted with electrical storm and monitored for 39.0 ± 28.2 hours. Protocol 4 included 3 patients who underwent bilateral stellate ganglion blockade with lidocaine injection. RESULTS: In patients without heart diseases, spontaneous nerve discharges were frequently observed at baseline and were associated with heart rate acceleration. SKNA recorded from chest leads (V1-V6) during cold water pressor test and Valsalva maneuver (protocol 1) was invariably higher than during baseline and recovery periods (P < .001). In protocol 2, the average SKNA correlated with heart rate acceleration (r = 0.73 ± 0.14, P < .05) and shortening of QT interval (P < .001). Among 146 spontaneous ventricular tachycardia episodes recorded in 9 patients of protocol 3, 106 episodes (73%) were preceded by SKNA within 30 seconds of onset. Protocol 4 showed that bilateral stellate ganglia blockade by lidocaine inhibited SKNA. CONCLUSION: SKNA is detectable using conventional ECG electrodes in humans and may be useful in estimating sympathetic tone

Fungal iron availability during deep seated candidiasis is defined by a complex interplay involving systemic and local events

Peer reviewedPublisher PD

Genome-Wide Analysis of Effectors of Peroxisome Biogenesis

Peroxisomes are intracellular organelles that house a number of diverse metabolic processes, notably those required for β-oxidation of fatty acids. Peroxisomes biogenesis can be induced by the presence of peroxisome proliferators, including fatty acids, which activate complex cellular programs that underlie the induction process. Here, we used multi-parameter quantitative phenotype analyses of an arrayed mutant collection of yeast cells induced to proliferate peroxisomes, to establish a comprehensive inventory of genes required for peroxisome induction and function. The assays employed include growth in the presence of fatty acids, and confocal imaging and flow cytometry through the induction process. In addition to the classical phenotypes associated with loss of peroxisomal functions, these studies identified 169 genes required for robust signaling, transcription, normal peroxisomal development and morphologies, and transmission of peroxisomes to daughter cells. These gene products are localized throughout the cell, and many have indirect connections to peroxisome function. By integration with extant data sets, we present a total of 211 genes linked to peroxisome biogenesis and highlight the complex networks through which information flows during peroxisome biogenesis and function

Transduction of Brain Dopamine Neurons by Adenoviral Vectors Is Modulated by CAR Expression: Rationale for Tropism Modified Vectors in PD Gene Therapy

Gene-based therapy is a new paradigm for the treatment of Parkinson disease (PD) and offers considerable promise for precise targeting and flexibility to impact multiple pathobiological processes for which small molecule agents are not available. Some success has been achieved utilizing adeno-associated virus for this approach, but it is likely that the characteristics of this vector system will ultimately create barriers to progress in clinical therapy. Adenovirus (Ad) vector overcomes limitations in payload size and targeting. The cellular tropism of Ad serotype 5 (Ad5)-based vectors is regulated by the Ad attachment protein binding to its primary cellular receptor, the coxsackie and adenovirus receptor (CAR). Many clinically relevant tissues are refractory to Ad5 infection due to negligible CAR levels but can be targeted by tropism-modified, CAR-independent forms of Ad. Our objective was to evaluate the role of CAR protein in transduction of dopamine (DA) neurons in vivo.Ad5 was delivered to the substantia nigra (SN) in wild type (wt) and CAR transgenic animals. Cellular tropism was assessed by immunohistochemistry (IHC) in the SN and striatal terminals. CAR expression was assessed by western blot and IHC. We found in wt animals, Ad5 results in robust transgene expression in astrocytes and other non-neuronal cells but poor infection of DA neurons. In contrast, in transgenic animals, Ad5 infects SNc neurons resulting in expression of transduced protein in their striatal terminals. Western blot showed low CAR expression in the ventral midbrain of wt animals compared to transgenic animals. Interestingly, hCAR protein localizes with markers of post-synaptic structures, suggesting synapses are the point of entry into dopaminergic neurons in transgenic animals.These findings demonstrate that CAR deficiency limits infection of wild type DA neurons by Ad5 and provide a rationale for the development of tropism-modified, CAR-independent Ad-vectors for use in gene therapy of human PD

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected