Supporting Peer Help and Collaboration in Distributed Workplace Environments

Special Issue on Computer Supported Collaborative LearningIncreasingly, organizations are geographically distributed with activities coordinated and integrated through the use of information technology. Such organizations face constant change and the corresponding need for continual learning and renewal of their workers. In this paper we describe a prototype system called PHelpS (Peer Help System) that facilitates workers in carrying out such "life long learning". PHelpS supports workers as they perform their tasks, offers assistance in finding peer helpers when required, and mediates communication on task-related topics. When a worker runs into difficulty in carrying out a task, PHelpS provides a list of other workers who are ready, willing and able to help him or her. The worker then selects a particular helper with PHelpS supporting the subsequent help interaction. The PHelpS system acts as a facilitator to stimulate learning and collaboration, rather than as a directive agent imposing its perspectives on the workers. In this way PHelpS facilitates the creation of extensive informal peer help networks, where workers help one another with tasks and opens up new research avenues for further exploration of AI-based computer-supported collaborative learning. (http://aied.inf.ed.ac.uk/members98/archive/vol_9/greer/full.html

The Effect of Travel Burden on Depression and Anxiety in African American Women Living with Systemic Lupus

The United States has a deficit of rheumatology specialists. This leads to an increased burden in accessing care for patients requiring specialized care. Given that most rheumatologists are located in urban centers at large hospitals, many lupus patients must travel long distances for routine appointments. The present work aims to determine whether travel burden is associated with increased levels of depression and anxiety among these patients. Data for this study were collected from baseline visits of patients participating in a lupus study at MUSC. A travel/economic burden survey was assessed as well as the 8-item Patient Health Questionnaire (PHQ-8) and the 7-item Generalized Anxiety Disorder (GAD-7) survey as measures of depression and anxiety, respectively. Linear regression models were used to assess the relationship between travel burden and depression and anxiety. Frequency of healthcare visits was significantly associated with increased depression (β = 1.3, p = 0.02). Significant relationships were identified between anxiety and requiring time off from work for healthcare appointments (β = 4, p = 0.02), and anxiety and perceived difficulty in traveling to primary care providers (β = 3.1, p = 0.04). Results from this study provide evidence that travel burden can have an effect on lupus patients’ anxiety and depression levels

Comparing genotyping algorithms for Illumina's Infinium whole-genome SNP BeadChips

The Brassica napus 60K Illumina Infinium™ SNP array has had huge international uptake in the rapeseed community due to the revolutionary speed of acquisition and ease of analysis of this high-throughput genotyping data, particularly when coupled with the newly available reference genome sequence. However, further utilization of this valuable resource can be optimized by better understanding the promises and pitfalls of SNP arrays. We outline how best to analyze Brassica SNP marker array data for diverse applications, including linkage and association mapping, genetic diversity and genomic introgression studies. We present data on which SNPs are locus-specific in winter, semi-winter and spring B. napus germplasm pools, rather than amplifying both an A-genome and a C-genome locus or multiple loci. Common issues that arise when analyzing array data will be discussed, particularly those unique to SNP markers and how to deal with these for practical applications in Brassica breeding applications

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

The DUNE Far Detector Interim Design Report, Volume 3: Dual-Phase Module

The DUNE IDR describes the proposed physics program and technical designs of the DUNE far detector modules in preparation for the full TDR to be published in 2019. It is intended as an intermediate milestone on the path to a full TDR, justifying the technical choices that flow down from the high-level physics goals through requirements at all levels of the Project. These design choices will enable the DUNE experiment to make the ground-breaking discoveries that will help to answer fundamental physics questions. Volume 3 describes the dual-phase module's subsystems, the technical coordination required for its design, construction, installation, and integration, and its organizational structure

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

Supporting the Learning of Recursive Problem Solving

: This research is about the problem solving activities of novice programmers as they learn to create recursive LISP programs. Their problem solving not only includes the issue of mental models, but also how to use these mental models in conjunction with other problem solving techniques. In fact, at various stages of their learning, learners seem to use different packages of problem solving methods. Each of these packages we call a mental method. In this paper, we discuss the PETAL learning environment which assists learners in the use of three of these mental methods: the syntactic method, the analytic method and the analysis/synthesis method. PETAL externalizes each mental method through its own customized interface, called a programming environment tool (PET). Such externalization helps learners internalize concepts, and organize relevant knowledge and generally leads to improved learning. The PETAL System itself is presented. Next we discuss a study where one group of students used..

Evaluation Methodologies for Intelligent Tutoring Systems

As intelligent tutoring system (ITS) issues are investigated and intelligent tutoring systems are developed, evaluation methodology becomes important. Basic researchers, system developers, and educators working with ITS all have motives for becoming involved in ITS evaluation. In formative evaluation, researchers examine a system under development, to identify problems and guide modifications. By contrast, summative evaluation is carried out to support formal claims about the construction, behaviour of, or outcomes associated with a completed system. Different methodologies are suitable for different types of evaluation, some focusing on internal considerations, such as architecture and behaviour, others on external considerations, such as educational impact. This paper draws upon the areas of intelligent tutoring systems research, expert systems design, computer-based instruction, education, and psychology to identify techniques for the formative and summative evaluation of ITS. Evalu..