Frame-Based Editing: Easing the Transition from Blocks to Text-Based Programming

Block-based programming systems, such as Scratch or Alice, are the most popular environments for introducing young children to programming. However, mastery of text-based programming continues to be the educational goal for stu- dents who continue to program into their teenage years and beyond. Transitioning across the significant gap between the two editing styles presents a difficult challenge in school- level teaching of programming. We propose a new style of program manipulation to bridge the gap: frame-based edit- ing. Frame-based editing has the resistance to errors and approachability of block-based programming while retaining the flexibility and more conventional programming seman- tics of text-based programming languages. In this paper, we analyse the issues involved in the transition from blocks to text and argue that they can be overcome by using frame- based editing as an intermediate step. A design and imple- mentation of a frame-based editor is provided

Blackbox: A Large Scale Repository of Novice Programmers’ Activity

Automatically observing and recording the programming be- haviour of novices is an established computing education research technique. However, prior studies have been con- ducted at a single institution on a small or medium scale, without the possibility of data re-use. Now, the widespread availability of always-on Internet access allows for data col- lection at a much larger, global scale. In this paper we re- port on the Blackbox project, begun in June 2013. Black- box is a perpetual data collection project that collects data from worldwide users of the BlueJ IDE – a programming environment designed for novice programmers. Over one hundred thousand users have already opted-in to Blackbox. The collected data is anonymous and is available to other researchers for use in their own studies, thus benefitting the larger research community. In this paper, we describe the data available via Blackbox, show some examples of analyses that can be performed using the collected data, and discuss some of the analysis challenges that lie ahead

Motor Task Processing After Constraint- Induced Movement Therapy in Children With Cerebral Palsy: A Case Series

Constraint-induced movement therapy (CIMT) has shown positive results in children with hemiplegic cerebral palsy (CP). However, studies on neural basis of such functional gains are limited. This study reports the event-related potential (ERP) changes in two children with hemiplegic CP after receiving CIMT for three weeks. Both cases were nine years old, had a diagnosis of left hemiplegic CP, had normal intelligence, and were able to extend the wrist at least 20° and the metacarpophalangeal joint at least 10° from full flexion. Before and after the three-week intervention, the children participated in ERP sessions with a choice reaction task to capture the changes in neural mechanism after intervention. Both children exhibited improvement in reaction time (RT) in both hand tasks after the intervention. The improvement was larger in the affected hand than the unaffected hand. Improved accuracy rate (AC) and shortened P300 latencies in the affected hand were also demonstrated in both cases. Topographical maps showed that in centro-parietal regions, patterns shifted from central and left-lateralized to more central and right-lateralized. CMIT was a useful method in improving upper limb function in our cases

Evaluation of a Frame-based Programming Editor

Frame-based editing is a novel way to edit programs, which claims to combine the benefits of textual and block-based programming. It combines structured ‘frames’ of preformatted code, designed to reduce the burden of syntax, with ‘slots’ that allow for efficient textual entry of expressions. We present an empirical evaluation of Stride, a frame-based language used in the Greenfoot IDE. We compare two groups of middle school students who worked on a short programming activity in Greenfoot, one using the original Java editor, and one using the Stride editor. We found that the two groups reported similarly low levels of frustration and high levels of satisfaction, but students using Stride progressed through the activity more quickly and completed more objectives. The Stride group also spent significantly less time making purely syntactic edits to their code and significantly less time with non-compilable code

Inconsistency of set theory via evaluation

We introduce in an axiomatic way the categorical theory PR of primitive recursion as the initial cartesian category with Natural Numbers Object. This theory has an extension into constructive set theory S of primitive recursion with abstraction of predicates into subsets and two-valued (boolean) truth algebra. Within the framework of (typical) classical, quantified set theory T we construct an evaluation of arithmetised theory PR via Complexity Controlled Iteration with witnessed termination of the iteration, witnessed termination by availability of Hilbert s iota operator in set theory. Objectivity of that evaluation yields inconsistency of set theory T by a liar (anti)diagonal argument

Targeting alphas can make coyote control more effective and socially acceptable

Research at the UC Hopland Research and Extension Center (HREC) has improved our understanding of how to reduce sheep depredation while minimizing the impact on coyotes. Analysis of a 14-year data set of HREC coyote-control efforts found that sheep depredation losses were not correlated with the number of coyotes removed in any of three time scales analyzed (yearly, seasonally and monthly) during corresponding intervals for the next 2 years. Field research using radiotelemetry to track coyotes supported and explained this finding. For example, in 1995, dominant “alphas” from four territories were associated with 89% of 74 coyote-killed lambs; “betas” and transients were not associated with any of these kills. Relatively few coyotes were killing sheep, and these animals were difficult to capture by conventional methods at the time of year when depredation was highest. However, selective removal of only the problem alpha coyotes effectively reduced losses at HREC

Targeting alphas can make coyote control more effective and socially acceptable

Research at the UC Hopland Research and Extension Center (HREC) has improved our understanding of how to reduce sheep depredation while minimizing the impact on coyotes. Analysis of a 14-year data set of HREC coyote-control efforts found that sheep depredation losses were not correlated with the number of coyotes removed in any of three time scales analyzed (yearly, seasonally and monthly) during corresponding intervals for the next 2 years. Field research using radiotelemetry to track coyotes supported and explained this finding. For example, in 1995, dominant “alphas” from four territories were associated with 89% of 74 coyote-killed lambs; “betas” and transients were not associated with any of these kills. Relatively few coyotes were killing sheep, and these animals were difficult to capture by conventional methods at the time of year when depredation was highest. However, selective removal of only the problem alpha coyotes effectively reduced losses at HREC

Estimating the feasibility of transition paths in extended finite state machines

There has been significant interest in automating testing on the basis of an extended finite state machine (EFSM) model of the required behaviour of the implementation under test (IUT). Many test criteria require that certain parts of the EFSM are executed. For example, we may want to execute every transition of the EFSM. In order to find a test suite (set of input sequences) that achieves this we might first derive a set of paths through the EFSM that satisfy the criterion using, for example, algorithms from graph theory. We then attempt to produce input sequences that trigger these paths. Unfortunately, however, the EFSM might have infeasible paths and the problem of determining whether a path is feasible is generally undecidable. This paper describes an approach in which a fitness function is used to estimate how easy it is to find an input sequence to trigger a given path through an EFSM. Such a fitness function could be used in a search-based approach in which we search for a path with good fitness that achieves a test objective, such as executing a particular transition, and then search for an input sequence that triggers the path. If this second search fails then we search for another path with good fitness and repeat the process. We give a computationally inexpensive approach (fitness function) that estimates the feasibility of a path. In order to evaluate this fitness function we compared the fitness of a path with the ease with which an input sequence can be produced using search to trigger the path and we used random sampling in order to estimate this. The empirical evidence suggests that a reasonably good correlation (0.72 and 0.62) exists between the fitness of a path, produced using the proposed fitness function, and an estimate of the ease with which we can randomly generate an input sequence to trigger the path

Protein Corona over Mesoporous Silica Nanoparticles: Influence of the Pore Diameter on Competitive Adsorption and Application to Prostate Cancer Diagnostics

[EN] Diagnostic tests based on proteomics analysis can have significant advantages over more traditional biochemical tests. However, low molecular weight (MW) protein biomarkers are difficult to identify by standard mass spectrometric analysis, as they are usually present at low concentrations and are masked by more abundant resident proteins. We have previously shown that mesoporous silica nanoparticles are able to capture a predominantly low MW protein fraction from the serum, as compared to the protein corona (PC) adsorbed onto dense silica nanoparticles. In this study, we begin by further investigating this effect using liquid chromatography-mass spectrometry (LC-MS)/MS and thermogravimetric analysis (TGA) to compare the MW of the proteins in the coronas of mesoporous silica nanoparticles with the same particle size but different pore diameters. Next, we examine the process by which two proteins, one small and one large, adsorb onto these mesoporous silica nanoparticles to establish a theory of why the corona becomes enriched in low MW proteins. Finally, we use this information to develop a novel system for the diagnosis of prostate cancer. An elastic net statistical model was applied to LC-MS/MS protein coronas from the serum of 22 cancer patients, identifying proteins specific to each patient group. These studies help to explain why low MW proteins predominate in the coronas of mesoporous silica nanoparticles, and they illustrate the ability of this information to supplement more traditional diagnostic tests.Financial support from the University of Vermont, the Spanish Ministry of Economy and Competitiveness (projects TEC2016-80976-R and SEV-2016-0683), and the Generalitat Valenciana (project PROMETEO/2017/060), is gratefully acknowledged. We thank Dr. Jaime Font de Mora for his assistance in the clinical sample collection and Dr. David Herva ' s for the statistical study supervision. We also appreciate the assistance of the electron microscopy service of the Universitat Politecnica de Valencia.Vidaurre Agut, CM.; Rivero-Buceta, EM.; Romaní-Cubells, E.; Clemments, AM.; Vera Donoso, CD.; Landry, C.; Botella Asuncion, P. (2019). Protein Corona over Mesoporous Silica Nanoparticles: Influence of the Pore Diameter on Competitive Adsorption and Application to Prostate Cancer Diagnostics. ACS Omega. 4(5):8852-8861. https://doi.org/10.1021/acsomega.9b00460S885288614