Improved Runtime for the Synchronous Multi-door Filling

In this paper, a particular type of dispersion is further investigated, which is called Filling. In this problem, robots are injected one by one into an a priori not known area and have to travel across until the whole area is covered. The coverage is achieved by a robotic team whose hardware capabilities are restricted in order to maintain low production costs. This includes limited viewing and communication ranges. In this work, we present an algorithm solving the synchronous Filling problem in O((k + ∆)·n) time steps by n robots with a viewing range of 1 hop, where k is the number of doors, n is the number of vertices of the graph, and ∆ is the maximum degree of the graph. This improves the best previously known running time bound of O(k · ∆ · n). Furthermore, we remove the constraint from the previous algorithm that the door vertices need to have a degree of 1

An Innovative Model for Adaptive Learning Utilizing Biofeedback and Item Response Theory

Measuring and providing efficiency of educational applications is a serious, open problem, which impacts the future of this expanding industry greatly. Reaching player engagement is a complex challenge, as it also depends on the given task and the mental state of the player. Researches answer this by using adaptive educational games. To reach the goal, however, knowledge about more parameters is required about the game tasks, the abilities of the player, his actual physiological state and performance as well. In this paper we present our results, which use a biofeedback based adaptive algorithm, and based on this, an innovative psychometric model to take a step towards maximizing user engagement

Mobile platforms and multi-mobile platform development

Mobile devices and mobile applications have a significant effect on the present and on the future of the software industry. The diversity of mobile platforms necessitates the development of the same mobile application for all major mobile platforms, which requires considerable development effort. Mobile application developers are multiplatform developers, but they prioritize the platforms, therefore, not all platforms are equally important for them. Appropriate methods, processes and tools are required to support the development in order to achieve better productivity. The main motivation of our research activity is to provide a method, which increases the development productivity and the quality of the applications and also reduces the time to market. The paper discusses our model-driven results on the field of multi-mobile platform development

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination

Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

While germline copy-number variants (CNVs) contribute to schizophrenia (SCZ) risk, the contribution of somatic CNVs (sCNVs)—present in some but not all cells—remains unknown. We identified sCNVs using blood-derived genotype arrays from 12,834 SCZ cases and 11,648 controls, filtering sCNVs at loci recurrently mutated in clonal blood disorders. Likely early-developmental sCNVs were more common in cases (0.91%) than controls (0.51%, p = 2.68e−4), with recurrent somatic deletions of exons 1–5 of the NRXN1 gene in five SCZ cases. Hi-C maps revealed ectopic, allele-specific loops forming between a potential cryptic promoter and non-coding cis-regulatory elements upon 5′ deletions in NRXN1. We also observed recurrent intragenic deletions of ABCB11, encoding a transporter implicated in anti-psychotic response, in five treatment-resistant SCZ cases and showed that ABCB11 is specifically enriched in neurons forming mesocortical and mesolimbic dopaminergic projections. Our results indicate potential roles of sCNVs in SCZ risk