Digital environments as third spaces : analyses of simple artefacts in the rooms of the MOdE

With the spread of digital environments that allow the user to design and produce contents, we have asked ourselves whether digital museums can be considered as ‘third spaces’ in which it is possible to exhibit, research, aggregate and re-elaborate, in a shared narrative, materials and experiences coming from different contexts. Conceiving the digital museum as a third space of contamination between formal and informal, presence and distance, real and digital presupposes the rethinking of the functions of the museum itself, capable of connecting both the demands for safeguards and those of accessibility to the cultural heritage, for an access to knowledge that is increasingly open. Starting from these premises, this contribution references the digital museum Museo Officina dell’Educazione (MOdE) as a third space by specifically analysing the digital settings produced by students of the upper secondary schools and by university students

An Exact Algorithm for Semi-supervised Minimum Sum-of-Squares Clustering

The minimum sum-of-squares clustering (MSSC), or k-means type clustering, is traditionally considered an unsupervised learning task. In recent years, the use of background knowledge to improve the cluster quality and promote interpretability of the clustering process has become a hot research topic at the intersection of mathematical optimization and machine learning research. The problem of taking advantage of background information in data clustering is called semi-supervised or constrained clustering. In this paper, we present a branch-and-cut algorithm for semi-supervised MSSC, where background knowledge is incorporated as pairwise must-link and cannot-link constraints. For the lower bound procedure, we solve the semidefinite programming relaxation of the MSSC discrete optimization model, and we use a cutting-plane procedure for strengthening the bound. For the upper bound, instead, by using integer programming tools, we use an adaptation of the k-means algorithm to the constrained case. For the first time, the proposed global optimization algorithm efficiently manages to solve real-world instances up to 800 data points with different combinations of must-link and cannot-link constraints and with a generic number of features. This problem size is about four times larger than the one of the instances solved by state-of-the-art exact algorithms

Modelling and Contractivity of Neural-Synaptic Networks with Hebbian Learning

This paper is concerned with the modelling and analysis of two of the most commonly used recurrent neural network models (i.e., Hopfield neural network and firing-rate neural network) with dynamic recurrent connections undergoing Hebbian learning rules. To capture the synaptic sparsity of neural circuits we propose a low dimensional formulation. We then characterize certain key dynamical properties. First, we give biologically-inspired forward invariance results. Then, we give sufficient conditions for the non-Euclidean contractivity of the models. Our contraction analysis leads to stability and robustness of time-varying trajectories -- for networks with both excitatory and inhibitory synapses governed by both Hebbian and anti-Hebbian rules. For each model, we propose a contractivity test based upon biologically meaningful quantities, e.g., neural and synaptic decay rate, maximum in-degree, and the maximum synaptic strength. Then, we show that the models satisfy Dale's Principle. Finally, we illustrate the effectiveness of our results via a numerical example.Comment: 24 pages, 4 figure

Associative and repetition priming with the repeated masked prime technique: No priming found

Wentura and Frings (2005) reported evidence of subliminal categorical priming on a lexical decision task, using a new method of visual masking in which the prime string consisted of the prime word flanked by random consonants and random letter masks alternated with the prime string on successive refresh cycles. We investigated associative and repetition priming on lexical decision, using the same method of visual masking. Three experiments failed to show any evidence of associative priming, (1) when the prime string was fixed at 10 characters (three to six flanking letters) and (2) when the number of flanking letters were reduced or absent. In all cases, prime detection was at chance level. Strong associative priming was observed with visible unmasked primes, but the addition of flanking letters restricted priming even though prime detection was still high. With repetition priming, no priming effects were found with the repeated masked technique, and prime detection was poor but just above chance levels. We conclude that with repeated masked primes, there is effective visual masking but that associative priming and repetition priming do not occur with experiment-unique prime-target pairs. Explanations for this apparent discrepancy across priming paradigms are discussed. The priming stimuli and prime-target pairs used in this study may be downloaded as supplemental materials from mc.psychonomic-journals.org/content/supplemental. © 2009 The Psychonomic Society, Inc

Scuola e lavoro nella formazione dei giovani: il museo come spazio di orientamento

The paper explores the educational value of the school-work experiences at the museum focusing on the choice of the context by the student. Specifically, it describes the role of the museum as a space of career guidance for the development of skills and self-determination. Some results of an exploratory research are going to be showned below that presents the experience carried out by students in the museums of Emilia Romagna.Il contributo approfondisce le valenze educative dei percorsi scuola-lavoro al museo ponendo lo sguardo sulla scelta del contesto da parte dello studente. Nello specifico il contributo analizza il ruolo del museo come spazio di orientamento per lo sviluppo di competenze e di autodeterminazione. A seguire si presentano alcuni risultati di una ricerca esplorativa che restituisce, attraverso la voce degli studenti, la loro esperienza nei musei dell’Emilia-Romagna

Comparison between soluble ST2 and high-sensitivity troponin I in predicting short-term mortality for patients presenting to the Emergency Department with chest pain

Background: High-sensitivity cardiac troponin I (hs-cTnI) and the soluble isoform of suppression of tumorigenicity 2 (sST2) are useful prognostic biomarkers in acute coronary syndrome (ACS). The aim of this study was to test the short term prognostic value of sST2 compared with hs-cTnI in patients with chest pain. Methods: Assays for hs-cTnI and sST2 were performed in 157 patients admitted to the Emergency Department (ED) for chest pain at arrival. In-hospital and 30-day follow-up mortalities were assessed. Results: The incidence of ACS was 37%; 33 patients were diagnosed with ST elevation myocardial infarction (STEMI), and 25 were diagnosed with non-ST elevation myocardial infarction (NSTEMI). Compared with the no acute coronary syndrome (NO ACS) group, the median level of hs-cTnI was higher in ACS patients: 7.22 (5.24-14) pg/mL vs 68 (15.33-163.50) pg/mL (P35 ng/mL at ED arrival died during the 30-day follow-up. Conclusions: sST2 has a greater prognostic value for 30-day cardiac mortality after discharge in patients presenting to the ED for chest pain compared with hs-cTnI. In STEMI patients, an sST2 value > 35 ng/mL at ED arrival showed the highest predictive power for short-term mortality

Monomolecular G-quadruplex structures with inversion of polarity sites: new topologies and potentiality

In this paper, we report investigations, based on circular dichroism, nuclear magnetic resonance spectroscopy and electrophoresis methods, on three oligonucleotide sequences, each containing one 3- 3 and two 5-5 inversion of polarity sites, and four G-runs with a variable number of residues, namely two, three and four (mTG2T, mTG3T andmTG4T with sequence 3-TGnT-5-5-TGnT-3-3-TGnT-5-5-TGnT-3 in which n = 2, 3 and 4, respectively), in comparison with their canonical counterparts (TGnT)4 (n = 2, 3 and 4). Oligonucleotides mTG3T and mTG4 T have been proven to form very stable unprecedented monomolecular parallel G-quadruplex structures, characterized by three side loops containing the inversion of polarity sites. Both G-quadruplexes have shown an all-syn G-tetrad, while the other guanosines adopt anti glycosidic conformations. All oligonucleotides investigated have shown a noteworthy antiproliferative activity against lung cancer cell line Calu 6 and colorectal cancer cell line HCT-116 p53−/−. Interestingly, mTG3T andmTG4T have proven to be mostly resistant to nucleases in a fetal bovine serum assay. The whole of the data suggest the involvement of specific pathways and targets for the biological activity

Exploring New Potential Anticancer Activities of the G-Quadruplexes Formed by [(GTG2T(G3T)3] and Its Derivatives with an Abasic Site Replacing Single Thymidine

In this paper, we report our investigations on five T30175 analogues, prepared by replacing sequence thymidines with abasic sites (S) one at a time, in comparison to their natural counterpart in order to evaluate their antiproliferative potential and the involvement of the residues not belonging to the central core of stacked guanosines in biological activity. The collected NMR (Nuclear Magnetic Resonance), CD (Circular Dichroism), and PAGE (Polyacrylamide Gel Electrophoresis) data strongly suggest that all of them adopt G-quadruplex (G4) structures strictly similar to that of the parent aptamer with the ability to fold into a dimeric structure composed of two identical G-quadruplexes, each characterized by parallel strands, three all-anti-G-tetrads and four one-thymidine loops (one bulge and three propeller loops). Furthermore, their antiproliferative (MTT assay) and anti-motility (wound healing assay) properties against lung and colorectal cancer cells were tested. Although all of the oligodeoxynucleotides (ODNs) investigated here exhibited anti-proliferative activity, the unmodified T30175 aptamer showed the greatest effect on cell growth, suggesting that both its characteristic folding in dimeric form and its presence in the sequence of all thymidines are crucial elements for antiproliferative activity. This straightforward approach is suitable for understanding the critical requirements of the G-quadruplex structures that affect antiproliferative potential and suggests its application as a starting point to facilitate the reasonable development of G-quadruplexes with improved anticancer properties

Today’s University Students and Their Need to Connect

Higher education is rapidly changing and university instructors are presented with new types of students for whom technology is a significant influence. They perceive technology as a way of life and express a need to feel connected at all times. With increasingly diverse university classroom, technology integration is both a challenge and an opportunity. Supportive communication is important in the promotion of relationships and essential in a university classroom. A convenience sample of 390 students was surveyed to investigate the perceived influences of technology on relationships, including preferences, usage and time with technologies. Results indicated that technology makes communication easier, allows students to stay in touch with more people, and have relationships that would otherwise not be possible. Implications of this study suggest positive influences of technology on academic work, performance and maintenance of relationships. However, disadvantages with using technology such as increased stress, addictive feelings toward technologies, and increased misunderstandings in relationships and conflict also exist

Euclidean Contractivity of Neural Networks with Symmetric Weights

This paper investigates stability conditions of continuous-time Hopfield and firing-rate neural networks by leveraging contraction theory. First, we present a number of useful general algebraic results on matrix polytopes and products of symmetric matrices. Then, we give sufficient conditions for strong and weak Euclidean contractivity, i.e., contractivity with respect to the $\ell_2$ norm, of both models with symmetric weights and (possibly) non-smooth activation functions. Our contraction analysis leads to contraction rates which are log-optimal in almost all symmetric synaptic matrices. Finally, we use our results to propose a firing-rate neural network model to solve a quadratic optimization problem with box constraints.Comment: 16 pages, 2 figure