Ergodicity-breaking reveals time optimal decision making in humans

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimise wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theories. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximise the time average growth of in-game wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations

A scoping review on occupational science research in European contexts

Background A survey showed European occupational scientists cover a broad range in occupational science (OS) research, however, no contemporary overviews of European OS research exists, and current research may provide valuable information for OS and occupational therapy. Aim The aim was to provide an overview of contemporary European OS research. Materials and method A scoping review was performed, including studies conducted in Europe and published in the British Journal of Occupational Therapy (BJOT), the Scandinavian Journal of Occupational Therapy (SJOT) or the Journal of Occupational Science (JOS) between 2015 and 2020. The journals were systematically searched, and quality assessment and thematic analysis were undertaken. Results Findings from 93 articles identified many studies from the Nordic countries. Most studies applied qualitative research methods. Theoretical concepts from OS were used in data generating and discussions. A wide range of demographics, and living conditions were explored. Recent articles took a reflexive stance on the positionality of the researcher/s. Conclusions This review highlights the diversity of OS research, suggesting a solid theoretical knowledge base within European OS research. Significance The results contribute to further development and maturation of the discipline of OS in Europe and internationally

Ergodicity-breaking reveals time optimal decision making in humans

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimise wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theory. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximise the time average growth of wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.Comment: 43 pages including supplementary methods & material

Search for weakly interacting sub-eV particles with the OSQAR laser-based experiment: results and perspectives

Recent theoretical and experimental studies highlight the possibility of new fundamental particle physics beyond the Standard Model that can be probed by sub-eV energy experiments. The OSQAR photon regeneration experiment looks for "Light Shining through a Wall" (LSW) from the quantum oscillation of optical photons into "Weakly Interacting Sub-eV Particles" (WISPs), like axion or axion-like particles (ALPs), in a 9 T transverse magnetic field over the unprecedented length of $2 \times 14.3$ m. No excess of events has been detected over the background. The di-photon couplings of possible new light scalar and pseudo-scalar particles can be constrained in the massless limit to be less than $8.0\times10^{-8}$ GeV$^{-1}$. These results are very close to the most stringent laboratory constraints obtained for the coupling of ALPs to two photons. Plans for further improving the sensitivity of the OSQAR experiment are presented.Comment: 7 pages, 7 figure

Latest Results of the OSQAR Photon Regeneration Experiment for Axion-Like Particle Search

The OSQAR photon regeneration experiment searches for pseudoscalar and scalar axion-like particles by the method of "Light Shining Through a Wall", based on the assumption that these weakly interacting sub-eV particles couple to two photons to give rise to quantum oscillations with optical photons in strong magnetic field. No excess of events has been observed, which constrains the di-photon coupling strength of both pseudoscalar and scalar particles down to $5.7 \cdot 10^{-8}$ GeV$^{-1}$ in the massless limit. This result is the most stringent constraint on the di-photon coupling strength ever achieved in laboratory experiments.Comment: 6 pages, 5 figures. appears in Proceedings of the 10th PATRAS Workshop on Axions, WIMPs and WISPs (2014

Patient profiling for success after weight loss surgery (GO Bypass study): an interdisciplinary study protocol

Despite substantial research efforts, the mechanisms proposed to explain weight loss after gastric bypass (RYGB) and sleeve gastrectomy (SL) do not explain the large individual variation seen after these treatments. A complex set of factors are involved in the onset and development of obesity and these may also be relevant for the understanding of why success with treatments vary considerably between individuals. This calls for explanatory models that take into account not only biological determinants but also behavioral, affective and contextual factors. In this prospective study, we recruited 47 women and 8 men, aged 25–56 years old, with a BMI of 45.8 ± 7.1 kg/m2 from the waiting list for RYGB and SL at Køge hospital, Denmark. Pre-surgery and 1.5, 6 and 18 months after surgery we assessed various endpoints spanning multiple domains. Endpoints were selected on basis of previous studies and include: physiological measures: anthropometrics, vital signs, biochemical measures and appetite hormones, genetics, gut microbiota, appetite sensation, food and taste preferences, neural sensitivity, sensory perception and movement behaviors; psychological measures: general psychiatric symptom-load, depression, eating disorders, ADHD, personality disorder, impulsivity, emotion regulation, attachment pattern, general self-efficacy, alexithymia, internalization of weight bias, addiction, quality of life and trauma; and sociological and anthropological measures: sociodemographic measures, eating behavior, weight control practices and psycho-social factors. Joining these many endpoints and methodologies from different scientific disciplines and creating a multi-dimensional predictive model has not previously been attempted. Data on the primary endpoint are expected to be published in 2018

New games, new rules: big data and the changing context of strategy

Big data and the mechanisms by which it is produced and disseminated introduce important changes in the ways information is generated and made relevant for organizations. Big data often represents miscellaneous records of the whereabouts of large and shifting online crowds. It is frequently agnostic, in the sense of being produced for generic purposes or purposes different from those sought by big data crunching. It is based on varying formats and modes of communication (e.g., texts, image and sound), raising severe problems of semiotic translation and meaning compatibility. Crucially, the usefulness of big data rests on their steady updatability, a condition that reduces the time span within which this data is useful or relevant. Jointly, these attributes challenge established rules of strategy making as these are manifested in the canons of procuring structured information of lasting value that addresses specific and long-term organizational objectives. The developments underlying big data thus seem to carry important implications for strategy making, and the data and information practices with which strategy has been associated. We conclude by placing the understanding of these changes within the wider social and institutional context of longstanding data practices and the significance they carry for management and organizations

Modeling of Ti-W Solidification Microstructures Under Additive Manufacturing Conditions

Additive manufacturing (AM) processes have many benefits for the fabrication of alloy parts, including the potential for greater microstructural control and targeted properties than traditional metallurgy processes. To accelerate utilization of this process to produce such parts, an effective computational modeling approach to identify the relationships between material and process parameters, microstructure, and part properties is essential. Development of such a model requires accounting for the many factors in play during this process, including laser absorption, material addition and melting, fluid flow, various modes of heat transport, and solidification. In this paper, we start with a more modest goal, to create a multiscale model for a specific AM process, Laser Engineered Net Shaping (LENS™), which couples a continuum-level description of a simplified beam melting problem (coupling heat absorption, heat transport, and fluid flow) with a Lattice Boltzmann-cellular automata (LB-CA) microscale model of combined fluid flow, solute transport, and solidification. We apply this model to a binary Ti-5.5 wt pct W alloy and compare calculated quantities, such as dendrite arm spacing, with experimental results reported in a companion paper

Laser spectroscopy for breath analysis : towards clinical implementation

Detection and analysis of volatile compounds in exhaled breath represents an attractive tool for monitoring the metabolic status of a patient and disease diagnosis, since it is non-invasive and fast. Numerous studies have already demonstrated the benefit of breath analysis in clinical settings/applications and encouraged multidisciplinary research to reveal new insights regarding the origins, pathways, and pathophysiological roles of breath components. Many breath analysis methods are currently available to help explore these directions, ranging from mass spectrometry to laser-based spectroscopy and sensor arrays. This review presents an update of the current status of optical methods, using near and mid-infrared sources, for clinical breath gas analysis over the last decade and describes recent technological developments and their applications. The review includes: tunable diode laser absorption spectroscopy, cavity ring-down spectroscopy, integrated cavity output spectroscopy, cavity-enhanced absorption spectroscopy, photoacoustic spectroscopy, quartz-enhanced photoacoustic spectroscopy, and optical frequency comb spectroscopy. A SWOT analysis (strengths, weaknesses, opportunities, and threats) is presented that describes the laser-based techniques within the clinical framework of breath research and their appealing features for clinical use.Peer reviewe

Retrieving haystacks: a data driven information needs model for faceted search.

The research aim was to develop an understanding of information need characteristics for word co-occurrence-based search result filters (facets). No prior research has been identified into what enterprise searchers may find useful for exploratory search and why. Various word co-occurrence techniques were applied to results from sample queries performed on industry membership content. The results were used in an international survey of 54 practising petroleum engineers from 32 organizations. Subject familiarity, job role, personality and query specificity are possible causes for survey response variation. An information needs model is presented: Broad, Rich, Intriguing, Descriptive, General, Expert and Situational (BRIDGES). This may help professionals to more effectively meet their information needs and stimulate new needs, improving a systems ability to facilitate serendipity. This research has implications for faceted search in enterprise search and digital library deployments