Bubble size distribution and bubble ellipticity were measured as a function of axial position in a vertically oriented semi-batch gas-liquid Taylor vortex reactor with varying gas flow rate and inner cylinder rotation speed producing axial Reynolds numbers in the range 23.8-119 and azimuthal Reynolds numbers up to 4.2×104. The mean bubble size increases monotonically with axial distance from the bottom of the reactor at the location of gas injection. The functional form of the growth of the mean bubble size with axial position depends upon the azimuthal Reynolds number. Specifically, when the azimuthal Reynolds number is less than 1.3×104, the mean bubble size increases linearly with axial distance from the bubble injection point. In contrast, for azimuthal Reynolds numbers greater than this critical value, the mean bubble size increases with axial distance in a sigmoidal manner.
Informative/Abstract:Estimating streamflow is time and labour intensive due to the necessity of developing a rating curve. The development of a rating curve involves acquiring at least thirty in-field measurements of streamflow across a wide range of flow levels, which can be costly and impractical in remote regions with limited seasonal access. Here we showcase an automated system which accurately estimates streamflow multiple times each day, greatly facilitating the development of rating curves for remote or seasonally inaccessible sites. The system uses an emerging technique referred to as particle image velocimetry (PIV) to track the movement of objects and flow structure features on the mobile water surface to generate velocity vector grids. Velocity grids were used to calculate streamflow and facilitate the development of a rating curve. This represents the first use of an automated PIV system to estimate streamflow in small streams (< 5 m wide) and the first system to automatically distribute particles for facilitated PIV analysis.Keywords: Particle Image Velocimetry, Streamflow Monitoring, Automated Systems, Particle TracerFunding: This research was funded through the Ministry of Natural Resources and Forestry, the Canada-Ontario Agreement Fund, and the Queen Elizabeth II Graduate Scholarship in Science and Technology.
A self-wiping co-rotating twin-screw extruder (TSE) is operated in a starved state where the screws are partially filled with resin. Understanding resin distribution on the screw surface is essential for the design, operation, and maintenance of the twin-screw extrusion process. In this study, the circumferential and axial distribution of pressure, temperature, and resin in a TSE are calculated using a novel method combining the mathematical formulation of Hele–Shaw flow, the finite element method, and a newly developed down-wind pressure update scheme. The experimental results were in good agreement with the measured results. This calculation method enables us to visualize, in detail, the resin distribution, pressure, and temperature for the entire axial and circumferential direction over the TSE.
In the biopharmaceutical industry, Raman spectroscopy is now a proven PAT tool that enables in-line simultaneous monitoring of several CPPs and CQAs in real-time. However, as Raman monitoring requires multivariate modeling, variabilities unknown by models can impact the monitoring prediction accuracy. With the widespread use of Raman PAT tools, it is necessary to fix instrumental variability impacts, encountered for instance during a device replacement. In this work, we investigated the impact of instrumental variability between probes inside a multi-channel analyzer and between two analyzers, and explored solutions to correct them on model prediction errors in cell cultures. We found that the Kennard Stone Piecewise Direct Standardization (KS PDS) method enables to lower model prediction errors and that only one batch with the unknown device in the calibration dataset was sufficient to correct the prediction gap induced by instrumental variability. As a matter of fact, during device replacement a first cell culture monitoring can be performed with the KS PDS method. Then, the new data obtained can be inserted in the calibration dataset to integrate instrumental variability in the chemometric model. This methodology provides good multivariate calibration model prediction errors throughout the instrumental changes.
Seasonal suspended sediment transfer in glaciated catchments is responsive to meteorological, geomorphological, and glacio-fluvial conditions, and thus is a useful indicator of environmental system dynamics. Knowledge of multifaceted fluvial sediment-transfer processes is limited in the Arctic–a region sensitive to contemporary environmental change. For two glaciated sub-catchments at Lake Peters, northeast Brooks Range, Alaska, we conducted a two-year endeavor to monitor the hydrology and meteorology, and used the data to derive multiple-regression models of suspended sediment load. Statistical selection of the best models shows that incorporating meteorological or temporal explanatory variables improves performances of turbidity- and discharge-based sediment models. The resulting modeled specific suspended sediment yields to Lake Peters are: 33 (20-60) Mg km-2 yr-1 in 2015, and 79 (50-140) Mg km-2 yr-1 in 2016 (95% confidence band estimates). In contrast to previous studies in Arctic Alaska, fluvial suspended sediment transfer to Lake Peters was primarily influenced by rainfall, and secondarily influenced by temperature-driven melt processes associated with clockwise diurnal hysteresis. Despite different sub-catchment glacier coverage, specific yields were the same order of magnitude from the two primary inflows to Lake Peters, which are Carnivore Creek (128 km2; 10% glacier coverage) and Chamberlin Creek (8 km2; 23% glacier coverage). Seasonal to longer term sediment exhaustion and/or contrasting glacier dynamics may explain the lower than expected relative specific sediment yield from the more heavily glacierized Chamberlin Creek catchment. Absolute suspended sediment yield (Mg yr-1) from Carnivore Creek to Lake Peters was 28 times greater than from Chamberlin Creek, which we attribute to catchment size and sediment supply differences. Our results are useful for predicting changes in fluvial sediment transport in glaciated Arctic catchments.
Functional traits are becoming more common in the analysis of marine zooplankton community dynamics associated with environmental change. We use zooplankton groups with common functional properties to assess long-term trends in the zooplankton caused by certain environmental conditions in a highly eutrophicated gulf. Time series of zooplankton traits were collected since 1960 in the Gulf of Riga, Baltic Sea and were analysed using general additive model, principal component analysis, and multivariate model. One of the most significant changes was the considerable increase in the amount of the zooplankton functional groups (FGR) in coastal springtime communities, and dominance shifts from more complex to simpler organism groups – cladocerans and rotifers. The results also show that the functional trait organism complexity (body size) decreased considerably due to cladoceran and rotifer increase following elevated water temperature. Salinity and oxygen had negligible effects on the zooplankton community.
We present a numerical method for simulating 2D flow through a channel with deformable walls. The fluid is assumed to be incompressible and viscous. We consider the highly viscous regime, where fluid dynamics are described by the Stokes equations, and the less viscous regime described by the Navier-Stokes equations. The model is formulated as an immersed boundary problem, with the channel defined by compliant walls that are immersed in a larger computational fluid domain. The channel traverses through the computational domain, and the walls do not form a closed region. When the walls deviate from their equilibrium position, they exert singular forces on the underlying fluid. We compute the numerical solution to the model equations using the immersed interface method, which preserves sharp jumps in the solution and its derivatives. The immersed interface method typically requires a closed immersed interface, a condition that is not met by the present configuration. Thus, a contribution of the present work is the extension of the immersed interface method to immersed boundary problems with open interfaces. Numerical results indicate that this new method converges with second-order accuracy in both space and time, and can sharply capture discontinuities in the fluid solution.
This is a fundamental study addressing the articulation of knowledge from the context of the fourth industrial revolution (Industry 4.0). Industry 4.0 employs embedded systems (e.g., cyber-physical systems) to perform cognitive tasks. These systems cannot work without applying digitized knowledge. As a result, the digitization of knowledge-intensive activities (knowledge acquisition, representation, dissemination, utilization, and management) is critical for Industry 4.0. Before digitizing the knowledge and knowledge-intensive activities, a fundamental question arises: What is knowledge in Industry 4.0? This study answers this question. In doing so, this study first reviews the definitions of knowledge reported in the extant literature of epistemology, engineering design, manufacturing, organization science, information science, and education science. This study then defines that a piece of knowledge consists of three elements, namely, claim, provenance, and inference. Such a definition helps overcome the circularity and ambiguity in the definitions of knowledge reported so far. This definition results in four types of knowledge, namely, definitional, deductive, inductive, and creative knowledge. These types of knowledge are exemplified using some real-life scenarios relevant to engineering design and manufacturing. The exemplified pieces of knowledge are also represented by using knowledge graphs (concept maps) so that the contents can easily be digitized for human and machine learning. The outcomes of this study are the fundamentals based on which more sophisticated methods and tools can be developed to perform the cognitive tasks relevant to Industry 4.0.
The young water fraction (Fyw), the proportion of water younger than 2-3 months, was investigated in soil-, ground- and stream waters in the 0.56 Km2 sub-humid Mediterranean Can Vila catchment. Rain water was sampled at 5-mm rainfall intervals. Mobile soil water and groundwater were sampled fortnightly, using suction lysimeters and two shallow wells, respectively. Stream water was dynamically sampled at variable time intervals (30 minutes to 1 week), depending on flow. A total of 1,529 18O determinations obtained during 58 months were used. The usual hypothesis of rapid evapotranspiration of summer rainfall could not be maintained, leading to discard the use of an “effective precipitation” model. Soil mobile waters had Fyw up to 34%, while in ground and stream were strongly related to water table and discharge variations, respectively. In stream waters, due to the highly skewed flow duration curve, the flow-averaged young water fraction (F*yw) was 22.6%, whereas the time-averaged Fyw was 6.2%. Nevertheless, both F*yw and its exponential discharge sensitivity (Sd) showed relevant changes when different 12-month sampling periods were investigated. The availability of Sd and a detailed flow record allowed us to simulate the young water fraction that would be obtained with a virtual thorough sampling (F**yw). This showed that underestimation of F*yw is associated with missing the sampling of highest discharges and revealed underestimations of F*yw by 25% for the dynamic sampling and 66% for the weekly sampling. These results confirm that the young water fraction and its discharge sensitivity are metrics that depend more on precipitation forcing than on physiographic characteristics, so the comparisons between catchments should be based on mean annual values and inter-annual variability. They also support the dependence of the young water fraction on the sampling rate and show the advantages of flow-weighted F*yw. Water age investigations should be accompanied by the analysis of flow duration curves. In addition, the simulation of F**yw is proposed as a method for checking the adequacy of the sampling rate used.
In this article, a highly robust antenna is proposed for omnidirectional circular polarized communications in harsh environments at 2.45 GHz industrial, scientific, and medical frequency band. Circular polarization is realized by utilizing a combination of two magnetic and electric dipoles. The proposed antenna is based on a transparent structure and covered by a quarter wavelength thick layer of plexiglass to achieve desired robustness and visible light transparency.Meanwhile, because of the high transparency of the glass, it can integrate with solar cells to simultaneously propagate signals and harvest energy. The average gain and bandwidth of the antenna are 1.7 dBic and 300 MHz, respectively. The antenna’s axial ratio is achieved less than 3 dB within the bandwidth, showing circular polarization behavior. The proposed compact antenna is numerically and experimentally analyzed and the results have a great agreement. In another viewpoint, the structure delivers promising possibilities to improve the propagating and radiating properties, which bring in significant advantages for real-world multifunctional applications.
Hypertension is a major risk factor for cardiovascular diseases, with high prevalence in low- and high-income countries. Among the various antihypertensive therapeutic strategies, synthetic Angiotensin I-converting enzyme inhibitors (ACEI) are one of the most used pharmacological agents. However, their use in hypertension therapy has been linked to various side effects. In recent years considerable research has been performed on the use of food-derived ACEI peptides (ACEIp) as antihypertensive agents. Although promising, the industrial production of these ACEIp through conventional methods, such as chemical synthesis and enzymatic hydrolysis of food proteins, has been proven troublesome and expensive. Limitations to the large-scale production of ACEIp for functional foods and supplements can be overcome by producing the precursors of these peptides in heterologous hosts. Bacterial hosts have been the privileged choice, particularly to test the success of the genetic engineering strategies, but new platforms based on plants and microalgae have also been emerging. This work provides an overview of the state of antihypertensive therapy, focusing on ACEI, illustrates the latest advances on ACEIp research, and describes current genetic engineer-based approaches for the heterologous production of ACEIp for antihypertensive therapy.
There is a rich amount of information in co-occurrence data that could be used to understand community assembly. This proposition first envisioned by Forbes (1907) and then Diamond (1975) prompted the development of numerous modelling approaches (e.g. null model analysis, co-occurrence networks and, more recently, joint species distribution models). Both theory and experimental evidence support the idea that ecological interactions may affect co-occurrence, but it remains unclear to what extent the signal of interaction can be captured in observational data. The time is now ripe to step back from the statistical developments and critically assess whether co-occurrence data really is a proxy for ecological interactions. In this paper we present a series of arguments based on probability, sampling, food web and coexistence theories supporting that significant spatial associations between species (or the lack of) is a poor proxy for ecological interactions. We discuss appropriate interpretations of co-occurrence, along with potential avenues to extract as much information as possible from such data.
Models of surface enhancement of molecular electronic response properties are challenging for two reasons: (1) molecule-surface interactions require the simultaneous solution of the molecular and the surface dynamic response (a daunting task); (2) when solving for the electronic structure of the combined molecule+surface system, it is not trivial to single out the particular physical effects responsible for enhancement. To attack this problem, in this work we apply a formally exact decomposition of the system’s response function into subsystem contributions by employing subsystem DFT which grants access to dynamic polarizabilities and optical spectra. In order to access information about the interactions between the subsystems, we extend a previously developed subsystem-based adiabatic connection fluctuation-dissipation theorem of DFT to separate the additive from the nonadditive correlation energy and identify the nonadditive correlation as the van der Waals interactions. As an example, we choose benzene adsorbed on monolayer MoS2. We isolate the contributions to the benzene’s dynamic response arising from the interaction with the surface and for the first time, we evaluate the enhancements to the effective C6 coefficients as a function of benzene-MoS2 distance and adsorption site. We also quantify the spectral broadening of the benzene’s electronic excited states due to their interaction with the surface. We find that the broadening has a similar decay law with the molecule-surface distance as the leading van der Waals interactions (i.e., R-6) and that the surface enhancement of dispersion interactions between benzene molecules is less than 5\%, but still large enough (0.5 kcal/mol) to likely play a role in the prediction of interface morphologies.
Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods can infer the history of ecological niche evolution inaccurately because (1) species’ niches are often poorly characterized; and (2) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species’ environmental tolerances. Here we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol.
In this study, we used two common ant species (Lasius niger and L. neoniger) to assay how they translate variation in the diet (both in composition and frequency) into growth. We measured colony development for over 8 months and measured several phenotypic traits of the worker caste, and examined whether forager preference corresponded with diet quality. Individuals (workers) and colonies (superorganisms) increased in size with increasing amounts of protein in the diet, and as a function of how much food was available. Optimal colony growth was a balance between survival and growth, and each of these were maximized with different nutrient regimes. Interestingly, forager preference was not totally aligned with the diet that maximized colony growth. Our results highlight that: 1) organism and superorganism size are controlled by the same nutrients, and this may reflect a common molecular basis for size across life’s organizational levels, 2) there are nutrient trade-offs that are associated with life-history trade-offs, likely leading to selection for a balanced diet, and 3) the connection between the preference of foragers for different nutrients and how nutrient combinations affect colony success and demographics are complex and only beginning to be understood.
Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modelling assumptions. Deadwood-dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales and they utilize distinct substrates. We tested how the projected large scale occupancies of species with differing landscape-scale occupancies are affected over the coming century by different modelling assumptions. We compared projections based on occupancy models against colonization-extinction models, conducting the modelling at alternative spatial scales, and using fine or coarse resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization-extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonisation-extinction models, with greater difference for the species with lower occupancy, colonization rate and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modelling scale and resource resolution. We encourage using colonisation-extinction models over occupancy models, modelling the process at the finest resource-unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality and spatial connectivity.
Scale and tempo of brain expansion in the course of human evolution implies that this process was driven by a positive feedback. The ‘cultural drive’ hypothesis suggests a possible mechanism for the runaway brain-culture coevolution wherein high-fidelity social learning results in accumulation of cultural traditions which, in turn, promote selection for still more efficient social learning. Here we explore this evolutionary mechanism by means of computer modeling. Simulations confirm its plausibility in a social species in a socio-ecological situation that makes the sporadic invention of new beneficial and cognitively demanding behaviours possible. The chances for the runaway brain-culture coevolution increase when some of the culturally transmitted behaviours are individually beneficial while the others are group-beneficial. In this case, ‘cultural drive’ is possible under varying levels of between-group competition and migration. Modeling implies that brain expansion can receive additional boost if the evolving mechanisms of social learning are costly in terms of brain expansion (e.g., rely on complex neuronal curcuits) and tolerant to the complexity of information transferred, that is, make it possible to transfer complex skills and concepts easily. Human language presumably fits this description. Modeling also confirms that the runaway brain-culture coevolution can be accelerated by additional positive feedback loops via population growth and lifespan extension, and that between-group competition and cultural group selection can facilitate the propagation of group-beneficial behaviours and remove maladaptive cultural traditions from the population’s culture, which individual selection is unable to do.
The mechanisms of Cp*Rh(OAc)2-catalyzed coupling reaction of N-methoxybenzamide with alkyl-terminated enyne have been investigated by density functional theory (DFT) calculations. With the addition of NaOAc and changing solvent, the product transforms from lactam P1 in reaction A to iminolactone P2 in reaction B, due to the formed stable OAc- coordinated intermediate. The electronic effect and steric effect account for the observed regioselectivity in reaction B collectively.