Big Data, Cognitive Computing and the future of learning managements Systems

Since the early years, when they started to enter the market, Learning Management Systems (LMSs) demonstrated their utility inside learning environments, contributing to the diffusion of e-learning especially in those Institutions with a low budget or no internal knowledge for developing e-learning initiatives. Today, they have reached a high maturity level, providing professional solutions to almost any educational need referring to distance learning. However, in our opinion, there are two important evolutions that should profoundly change the architecture of these pillar software tools. First, the acquisition of an enormous amount of data related to educational tasks will be very interesting for all the actors involved in educational processes (teachers, students, researchers, administrative personnel), and this will be particularly evident when standards like Experience-API (xAPI) will help to provide a more pervasive experience for learners. Second, we are observing the rise of new era for software platforms, characterized by machine learning, deep learning, cognitive computing and many other technologies that substantially give the computer a much more active role in the respective processes. We believe that this new paradigm will apply to education too. What this will entail is mainly related to exponential learning, a process of exponential growth of training demand because new knowledge and skills must be delivered at a speed never seen before, and where big data contexts are fundamental. In this paper, we present an analysis of how LMSs should evolve in the future, in our opinion and according to our experience, in terms of functionalities and services provided to users. We believe that current LMSs and their software architectures, mainly based on traditional multi-tier, relational database-oriented architectures will not be enough to stand the impact of these two new paradigms for modern learning environments. We are in the process of re-designing a virtual community platform that we have created and developed along the years, used in our universities and in several public and private organizations. The platform is oriented towards the support of collaborative processes, where of course e-learning is one of the most important, but not the only one, and where we are adding new services supporting collaboration in different ways. In this paper we will present the software architectural changes and evolution according to the advent of big data and cognitive computing

A Novel null homozygous mutation confirms <i>CACNA2D2</i> as a gene mutated in epileptic encephalopathy

Contribution to epileptic encephalopathy (EE) of mutations in CACNA2D2, encoding α2δ-2 subunit of Voltage Dependent Calcium Channels, is unclear. To date only one CACNA2D2 mutation altering channel functionality has been identified in a single family. In the same family, a rare CELSR3 polymorphism also segregated with disease. Involvement of CACNA2D2 in EE is therefore not confirmed, while that of CELSR3 is questionable. In a patient with epilepsy, dyskinesia, cerebellar atrophy, psychomotor delay and dysmorphic features, offspring to consanguineous parents, we performed whole exome sequencing (WES) for homozygosity mapping and mutation detection. WES identified extended autozygosity on chromosome 3, containing two novel homozygous candidate mutations: c.1295delA (p.Asn432fs) in CACNA2D2 and c.G6407A (p.Gly2136Asp) in CELSR3. Gene prioritization pointed to CACNA2D2 as the most prominent candidate gene. The WES finding in CACNA2D2 resulted to be statistically significant (p = 0.032), unlike that in CELSR3. CACNA2D2 homozygous c.1295delA essentially abolished α2δ-2 expression. In summary, we identified a novel null CACNA2D2 mutation associated to a clinical phenotype strikingly similar to the Cacna2d2 null mouse model. Molecular and statistical analyses together argued in favor of a causal contribution of CACNA2D2 mutations to EE, while suggested that finding in CELSR3, although potentially damaging, is likely incidental

Inhibition of the alpha- and beta-carbonic anhydrases from the gastric pathogen Helycobacter pylori with anions

The gastric pathogen Helicobacter pylori encodes two carbonic anhydrases (CAs, EC 4.2.1.1), an α- and a β-class one, hpαCA and hpβCA, crucial for its survival in the acidic environment from the stomach. Sulfonamides, strong inhibitors of these enzymes, block the growth of the pathogen, in vitro and in vivo. Here we report the inhibition of the two H. pylori CAs with inorganic and complex anions and other molecules interacting with zinc proteins. hpαCA was inhibited in the low micromolar range by diethyldithiocarbamate, sulfamide, sulfamic acid, phenylboronic acid, and in the submillimolar one by cyanide, cyanate, hydrogen sulfide, divanadate, tellurate, perruthenate, selenocyanide, trithiocarbonate, iminodisulfonate. hpβCA generally showed a stronger inhibition with most of these anions, with several low micromolar and many submillimolar inhibitors detected. These inhibitors may be used as leads for developing anti-H. pylori agents with a diverse mechanism of action compared to clinically used antibiotics

Inhibition of the β-class carbonic anhydrases from Mycobacterium tuberculosis with carboxylic acids

The growth of Mycobacterium tuberculosis is strongly inhibited by weak acids although the mechanism by which these compounds act is not completely understood. A series of substituted benzoic acids, nipecotic acid, ortho- and para-coumaric acid, caffeic acid and ferulic acid were investigated as inhibitors of three β-class carbonic anhydrases (CAs, EC 4.2.1.1) from this pathogen, mtCA 1 (Rv1284), mtCA 2 (Rv3588c) and mtCA 3 (Rv3273). All three enzymes were inhibited with efficacies between the submicromolar to the micromolar one, depending on the scaffold present in the carboxylic acid. mtCA 3 was the isoform mostly inhibited by these compounds (K(I)s in the range of 0.11-0.97 µM); followed by mtCA 2 (K(I)s in the range of 0.59-8.10 µM), whereas against mtCA 1, these carboxylic acids showed inhibition constants in the range of 2.25-7.13 µM. This class of relatively underexplored β-CA inhibitors warrant further in vivo studies, as they may have the potential for developing antimycobacterial agents with a diverse mechanism of action compared to the clinically used drugs for which many strains exhibit multi-drug or extensive multi-drug resistance

A comprehensive study of the short-circuit ruggedness of silicon carbide power MOSFETs

The behavior of Silicon Carbide Power MOSFETs under stressful short circuit conditions is investigated in this paper. Illustration of two different short-circuit failure phenomena for Silicon Carbide Power MOSFETs are thoroughly reported. Experimental evidences and TCAD electro-thermal simulations are exploited to describe and discriminate the failure sources. Physical causes are finally investigated and explained by means of properly calibrated numerical investigations, and are reported along with their effects on devices short-circuit capability

Glycosyl Coumarin Carbonic Anhydrase IX and XII Inhibitors Strongly Attenuate the Growth of Primary Breast Tumors.

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