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Block-based programming environments are increasingly used to introduce computing concepts to beginners. However, novice students often struggle in these environments, given the conceptual and open-ended nature of programming tasks. To effectively support a student struggling to solve a given task, it is important to provide adaptive scaffolding that guides the student towards a solution. We introduce a scaffolding framework based on pop quizzes presented as multi-choice programming tasks. To automatically generate these pop quizzes, we propose a novel algorithm, PQUIZSYN. More formally, given a reference task with a solution code and the student's current attempt, PQUIZSYN synthesizes new tasks for pop quizzes with the following features: (a) Adaptive (i.e., individualized to the student's current attempt), (b) Comprehensible (i.e., easy to comprehend and solve), and (c) Concealing (i.e., do not reveal the solution code). Our algorithm synthesizes these tasks using techniques based on symbolic reasoning and graphbased code representations. We show that our algorithm can generate hundreds of pop quizzes for different student attempts on reference tasks from Hour of Code: Maze Challenge [11] and Karel [9]. We assess the quality of these pop quizzes through expert ratings using an evaluation rubric. Further, we have built an online platform for practicing block-based programming tasks empowered via pop quiz based feedback, and report results from an initial user study.

Objectives: The incidence of acute limb ischemia (ALI) has increased since the emergence of coronavirus disease 2019 (COVID-19) and has been linked to the serum level of cross-linked fibrin degradation products (D-dimer). The purpose of this study is to understand arterial thromboembolic architecture in patients with ALI and how this is altered by COVID-19 infection. Methods: Arterial thromboembolic specimens were prospectively collected at a single institution, stored in an IRB-approved tissue bank at -80°C for preservation of architecture. Liquid chromatography mass spectrometry (LC-MS/MS) was used to identify in-vivo Factor XIII (FXIII) generated cross-links, critical determinants of clot stability and strength. Protein composition of thromboemboli was compared between COVID and non-COVID patients. Results: Arterial thromboemboli were obtained from four patients. Patient #1 had COVID pneumonia and a D-dimer of 14,690 ng/mL FEU and developed ALI secondary to embolization of an aortic thrombus. Patients #2-4 did not have COVID and developed ALI secondary to synthetic graft thrombosis, septic embolization from endocarditis, and embolization during aortic arch replacement. COVID thromboemboli demonstrated a higher abundance of immune response proteins compared to non-COVID thromboemboli. Eighty-one cross-links were identified across the four specimens (Fig 1). A six-fold greater degree of Fibrinogen Alpha Chain (FibA-FibA) cross-linking was present in the COVID specimen (Mean: 295,100) compared to the mean of the three non-COVID specimens (Mean: 52,973) (Figure 2). Conclusions: A higher degree of cross-linking and increased levels of innate and adaptive immune response proteins appear to be features of arterial thromboemboli in COVID-induced ALI. This supports a virus-associated hypercoagulable state in COVID-19 patients with ALI.

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Cement is the largest mass manufactured man made product on earth. The demand for cement is on a continual rise, as more and more developing countries strive for better infrastructure. This demand has, however, entailed an unacceptable increase in the carbon emissions as the cement manufacturing industry is one of the most carbon releasing industries in the world; responsible for more than 5% of the global carbon emissions. The dangerously high levels of Carbon Dioxide have contributed to a large scale climate change which has global repercussions. The need of the hour is an effective yet inexpensive mechanism to trim down the carbon emissions from the cement factories. In this paper, the main industrial as well as the governmental strategies for alleviating the carbon emissions of the cement industry are reviewed, focusing on the carbon taxation for the latter. This review has observed a comprehensive literature in term of the peer reviewed journals, research papers, industry reports, authentic websites etc on the cement industry and the strategies to reduce the carbon emissions.

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In this paper we propose using the compression method, Shannon-Fano-Elias coding, for encryption. ShannonFano-Elias codes lend themselves for encryption because codewords depend on the order in which the symbols that need to be coded are written and it does not matter if the probability mass function of the symbols is known to everyone. If there are n symbols then there are n! orderings, each leading to a new code. Using an ordering as a key for encryption for small n leads to a weak encryption scheme. We therefore propose a new scheme called adaptive Shannon-Fano-Elias code that makes the complexity of attacks exponential in m, where m is the length of the string being compressed. Since m is usually very large (> 2 20 ), the security of our scheme is very high. The main reason why our scheme's security depends on m is the fact that all attacks require the ciphertext to be scanned from left to right.