Recognition without identification, erroneous familiarity, and déjà vu

Déjà vu is characterized by the recognition of a situation concurrent with the awareness that this recognition is inappropriate. Although forms of déjà vu resolve in favor of the inappropriate recognition and therefore have behavioral consequences, typical déjà vu experiences resolve in favor of the awareness that the sensation of recognition is inappropriate. The resultant lack of behavioral modification associated with typical déjà vu means that clinicians and experimenters rely heavily on self-report when observing the experience. In this review, we focus on recent déjà vu research. We consider issues facing neuropsychological, neuroscientific, and cognitive experimental frameworks attempting to explore and experimentally generate the experience. In doing this, we suggest the need for more experimentation and amore cautious interpretation of research findings, particularly as many techniques being used to explore déjà vu are in the early stages of development.PostprintPeer reviewe

Applying blockchain to improve the integrity of the software development process

Software development is a complex endeavor that encompasses application and implementation layers with functional (refers to what is done) and non-functional (how is done) aspects. The efforts to scale agile software development practices are not wholly able to address issues such as integrity, which is a crucial non-functional aspect of the software development process. However, if we consider most software failures are Byzantine failures (i.e., where components may fail and there is imperfect information on which a component has failed.) that might impair the operation but do not completely disable the production line. In this paper, we assume software practitioners who cause defects as Byzantine participants and claim that most software failures can be mitigated by viewing software development as the Byzantine Generals Problem. Consequently, we propose a test-driven incentive mechanism based on a blockchain concept to orchestrate the software development process where production is controlled by a similar infrastructure based on the working principles of blockchain. We discuss the model that integrates blockchain with the software development process, and provide some recommendations for future work to address the issues while orchestrating software productio

The holistic phase model of early adult crisis

The objective of the current study was to explore the structural, temporal and experiential manifestations of crisis episodes in early adulthood, using a holistic-systemic theoretical framework. Based on an analysis of 50 interviews with individuals about a crisis episode between the ages of 25 and 35, a holistic model was developed. The model comprises four phases: (1) Locked-in, (2) Separation/Time-out, (3) Exploration and (4) Rebuilding, which in turn have characteristic features at four levels—person-in-environment, identity, motivation and affect-cognition. A crisis starts out with a commitment at work or home that has been made but is no longer desired, and this is followed by an emotionally volatile period of change as that commitment is terminated. The positive trajectory of crisis involves movement through an exploratory period towards active rebuilding of a new commitment, but ‘fast-forward’ and ‘relapse’ loops can interrupt Phases 3 and 4 and make a positive resolution of the episode less likely. The model shows conceptual links with life stage theories of emerging adulthood and early adulthood, and it extends current understandings of the transitional developmental challenges that young adults encounter

Testing in the incremental design and development of complex products

Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested

Challenges of one-year longitudinal follow-up of a prospective, observational cohort study using an anonymised database:Recommendations for trainee research collaboratives

Background: trainee research collaboratives (TRCs) have pioneered high quality, prospective ‘snap-shot’ surgical cohort studies in the UK. Outcomes After Kidney injury in Surgery (OAKS) was the first TRC cohort study to attempt to collect one-year follow-up data. The aims of this study were to evaluate one-year follow-up and data completion rates, and to identify factors associated with improved follow-up rates. Methods: in this multicentre study, patients undergoing major gastrointestinal surgery were prospectively identified and followed up at one-year following surgery for six clinical outcomes. The primary outcome for this report was the follow-up rate for mortality at 1 year. The secondary outcome was the data completeness rate in those patients who were followed-up. An electronic survey was disseminated to investigators to identify strategies associated with improved follow-up. Results: of the 173 centres that collected baseline data, 126 centres registered to participate in one-year follow-up. Overall 62.3% (3482/5585) of patients were followed-up at 1 year; in centres registered to collect one-year outcomes, the follow-up rate was 82.6% (3482/4213). There were no differences in sex, comorbidity, operative urgency, or 7-day postoperative AKI rate between patients who were lost to follow-up and those who were successfully followed-up. In centres registered to collect one-year follow-up outcomes, overall data completeness was 83.1%, with 57.9% (73/126) of centres having ≥95% data completeness. Factors associated with increased likelihood of achieving ≥95% data completeness were total number of patients to be followed-up (77.4% in centres with < 15 patients, 59.0% with 15–29 patients, 51.4% with 30–59 patients, and 36.8% with > 60 patients, p = 0.030), and central versus local storage of patient identifiers (72.5% vs 48.0%, respectively, p = 0.006). Conclusions: TRC methodology can be used to follow-up patients identified in prospective cohort studies at one-year. Follow-up rates are maximized by central storage of patient identifiers

Monitoring symptoms at home: What methods would cancer patients be comfortable using?

PURPOSE: This study aimed to determine which methods of remote symptom assessment cancer outpatients would be comfortable using, including those involving information technology, and whether this varied with age and gender. METHODS: A questionnaire survey of 477 outpatients attending the Edinburgh Cancer Centre in Edinburgh, UK. RESULTS: Most patients reported that they would not feel comfortable using methods involving technology such as a secure website, email, mobile phone text message, or a computer voice on the telephone but that they would be more comfortable using more traditional methods such as a paper questionnaire, speaking to a nurse on the telephone, or giving information in person. CONCLUSIONS: The uptake of new, potentially cost-effective technology-based methods of monitoring patients' symptoms at home might be limited by patients' initial discomfort with the idea of using them. It will be important to develop methods of addressing this potential barrier (such as detailed explanation and supervised practice) if these methods are to be successfully implemented

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students