Dynamic patterns of flow in the workplace: characterizing within-individual variability using a complexity science approach

As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).

The dynamics of biofilm bacterial communities is driven by flow wax and wane in a temporary stream

Biofilm communities are exposed to long periods of desiccation in temporary streams. We investigated how water flow intermittency affected the bacterial community structure colonizing three different streambed compartments in a Mediterranean stream. Massive parallel sequencing revealed different bacterial communities in biofilms from sand sediments and cobbles. Bacterial communities were similar (62% of shared operational taxonomic units) in the epipsammic and hyporheic biofilms, and more diverse than those in the epilithic biofilms. The non-flow phase caused a decrease of bacterial diversity in the biofilms, when communities included only bacterial taxa assumed to be adapted to water stress. The most sensitive bacterial communities to flow intermittency were in the epilithic, where the exposure to physical stress was the highest. In sand sediments a wide group of bacterial taxa was tolerant to desiccation. During non-flow the proliferation of opportunistic taxa in the superficial compartments evidenced the biological link with the terrestrial environment. Bacterial communities better tolerate rewetting than desiccation, since a major number of taxa tolerant to rewetting occurred in all biofilms. Overall, bacterial communities in sandy compartments showed higher resistance to flow intermittency than those in epilithic biofilms

Comparison of a deterministic and a data driven model to describe MBR fouling

Membrane bioreactors (MBRs) are a combination of activated sludge bioreactors and membrane filtration, enabling high quality effluent with a small footprint. However, they can be beset by fouling, which causes an increase in transmembrane pressure (TMP). Modelling and simulation of changes in TMP could be useful to describe fouling through the identification of the most relevant operating conditions. Using experimental data from a MBR pilot plant operated for 462days, two different models were developed: a deterministic model using activated sludge model n°2d (ASM2d) for the biological component and a resistance in-series model for the filtration component as well as a data-driven model based on multivariable regressions. Once validated, these models were used to describe membrane fouling (as changes in TMP over time) under different operating conditions. The deterministic model performed better at higher temperatures (>20°C), constant operating conditions (DO set-point, membrane air-flow, pH and ORP), and high mixed liquor suspended solids (>6.9gL-1) and flux changes. At low pH (<7) or periods with higher pH changes, the data-driven model was more accurate. Changes in the DO set-point of the aerobic reactor that affected the TMP were also better described by the data-driven model. By combining the use of both models, a better description of fouling can be achieved under different operating conditions

Excitation modes of vortices in submicron magnetic disks

Classical and quantum theory of spin waves in the vortex state of a mesoscopic submicron magnetic disk have been developed with account of the finite mass density of the vortex. Oscillations of the vortex core resemble oscillations of a charged string in a potential well in the presence of the magnetic field. A conventional gyrotropic frequency appears as a gap in the spectrum of spin waves of the vortex. The mass of the vortex has been computed, and the result agrees with experimental findings. The finite vortex mass generates a high-frequency branch of spin waves. The effects of an external magnetic field and dissipation have been addressed.

River Conservation: Going against the Flow to Meet Global Challenges

Rivers are among the most diverse and threatened ecosystems on Earth, as they are impacted by increasing human pressures. Because rivers provide essential goods and services, conservation of these ecosystems is a requisite for sustainable development. Therefore, we must seek ways to conserve healthy rivers and to restore degraded ones