Membrane scaling and prevention techniques during seawater desalination by air gap membrane distillation

Membrane scaling and mitigation techniques during air gap membrane distillation (AGMD) of seawater were investigated. The results showed a strong influence of AGMD operating temperature on not only the process water flux but also membrane scaling and subsequent cleaning efficiency. Elevating feed/coolant temperature from 35/25 to 60/50 °C increased water flux, but also exacerbated membrane scaling of the AGMD process. Membrane scaling was more severe, and occurred at a lower water recovery (68%) when operating at 60/50 °C compared to 35/25 °C (78%) due to increased concentration polarisation effect. Operating temperature also affected the efficiency of the subsequent membrane cleaning. Membrane scaling that occurred at low temperature (i.e. 35/25 °C) was more efficiently cleaned than at high temperature (i.e. 60/50 °C). In addition, membrane cleaning using vinegar was much more efficient than fresh water. Nevertheless, vinegar cleaning could not completely restore the membrane surface to the original condition. Traces of residual scalants on the membrane surface accelerated scaling in the next operation cycle. On the other hand, anti-scalant addition could effectively control scaling. Membrane scaling during AGMD of seawater at 70% water recovery and 60/50 °C was effectively controlled by anti-scalant addition

Membrane distillation and membrane electrolysis of coal seam gas reverse osmosis brine for clean water extraction and NaOH production

Membrane distillation (MD) and membrane electrolysis (ME) were evaluated for simultaneous fresh water extraction and NaOH production from a mixture of NaCl and NaHCO3 to simulate the composition of coal seam gas (CSG) reverse osmosis (RO) brine. Experimental results demonstrate the potential of MD for producing fresh water and simultaneously concentrating CSG RO brine prior to the ME process. MD water flux was slightly reduced by the increased feed salinity and the decomposition of bicarbonate to CO2 during the concentration of CSG RO brine. MD operation of CSG RO brine at a concentration factor of 10 (90% water recovery) was achieved with distillate conductivity as low as 18 μS/cm, and without any observable membrane scaling. Exceeding the concentration factor of 10 could lead to deterioration in both water flux and distillate quality due to the precipitation of NaCl, NaHCO3, and Na2CO3 on the membrane. With respect to ME, current density and water circulation rates exerted strong influences on the ME process performance. Combining ME with MD reduced the thermal energy requirement of ME by 3 MJ per kg of NaOH produced and the thermal energy consumption of MD by 22 MJ per m3 of clean water extracted

E-cadherin and cell adhesion: a role in architecture and function in the pancreatic islet

Background/Aims: The efficient secretion of insulin from beta-cells requires extensive intra-islet communication. The cell surface adhesion protein epithelial (E)-cadherin (ECAD) establishes and maintains epithelial tissues such as the islets of Langerhans. In this study, the role of ECAD in regulating insulin secretion from pseudoislets was investigated. Methods: The effect of an immuno-neutralising ECAD on gross morphology, cytosolic calcium signalling, direct cell-to-cell communication and insulin secretion was assessed by fura-2 microfluorimetry, Lucifer Yellow dye injection and insulin ELISA in an insulin-secreting model system. Results: Antibody blockade of ECAD reduces glucose-evoked changes in [Ca2+](i) and insulin secretion. Neutralisation of ECAD causes a breakdown in the glucose-stimulated synchronicity of calcium oscillations between discrete regions within the pseudoislet, and the transfer of dye from an individual cell within a cell cluster is attenuated in the absence of ECAD ligation, demonstrating that gap junction communication is disrupted. The functional consequence of neutralising ECAD is a significant reduction in insulin secretion. Conclusion: Cell adhesion via ECAD has distinct roles in the regulation of intercellular communication between beta-cells within islets, with potential repercussions for insulin secretion. Copyright (C) 2007 S. Karger AG, Basel

Simulation-based analysis of micro-robots swimming at the center and near the wall of circular mini-channels

Swimming micro robots have great potential in biomedical applications such as targeted drug delivery, medical diagnosis, and destroying blood clots in arteries. Inspired by swimming micro organisms, micro robots can move in biofluids with helical tails attached to their bodies. In order to design and navigate micro robots, hydrodynamic characteristics of the flow field must be understood well. This work presents computational fluid dynamics (CFD) modeling and analysis of the flow due to the motion of micro robots that consist of magnetic heads and helical tails inside fluid-filled channels akin to bodily conduits; special emphasis is on the effects of the radial position of the robot. Time-averaged velocities, forces, torques, and efficiency of the micro robots placed in the channels are analyzed as functions of rotation frequency, helical pitch (wavelength) and helical radius (amplitude) of the tail. Results indicate that robots move faster and more efficiently near the wall than at the center of the channel. Forces acting on micro robots are asymmetrical due to the chirality of the robot’s tail and its motion. Moreover, robots placed near the wall have a different flow pattern around the head when compared to in-center and unbounded swimmers. According to simulation results, time-averaged for-ward velocity of the robot agrees well with the experimental values measured previously for a robot with almost the same dimensions

Deep forecasting of translational impact in medical research.

The value of biomedical research-a $1.7 trillion annual investment-is ultimately determined by its downstream, real-world impact, whose predictability from simple citation metrics remains unquantified. Here we sought to determine the comparative predictability of future real-world translation-as indexed by inclusion in patents, guidelines, or policy documents-from complex models of title/abstract-level content versus citations and metadata alone. We quantify predictive performance out of sample, ahead of time, across major domains, using the entire corpus of biomedical research captured by Microsoft Academic Graph from 1990-2019, encompassing 43.3 million papers. We show that citations are only moderately predictive of translational impact. In contrast, high-dimensional models of titles, abstracts, and metadata exhibit high fidelity (area under the receiver operating curve [AUROC] > 0.9), generalize across time and domain, and transfer to recognizing papers of Nobel laureates. We argue that content-based impact models are superior to conventional, citation-based measures and sustain a stronger evidence-based claim to the objective measurement of translational potential

Dimensionality and dynamics in the behavior of C. elegans

A major challenge in analyzing animal behavior is to discover some underlying simplicity in complex motor actions. Here we show that the space of shapes adopted by the nematode C. elegans is surprisingly low dimensional, with just four dimensions accounting for 95% of the shape variance, and we partially reconstruct "equations of motion" for the dynamics in this space. These dynamics have multiple attractors, and we find that the worm visits these in a rapid and almost completely deterministic response to weak thermal stimuli. Stimulus-dependent correlations among the different modes suggest that one can generate more reliable behaviors by synchronizing stimuli to the state of the worm in shape space. We confirm this prediction, effectively "steering" the worm in real time.Comment: 9 pages, 6 figures, minor correction

Information transmission in oscillatory neural activity

Periodic neural activity not locked to the stimulus or to motor responses is usually ignored. Here, we present new tools for modeling and quantifying the information transmission based on periodic neural activity that occurs with quasi-random phase relative to the stimulus. We propose a model to reproduce characteristic features of oscillatory spike trains, such as histograms of inter-spike intervals and phase locking of spikes to an oscillatory influence. The proposed model is based on an inhomogeneous Gamma process governed by a density function that is a product of the usual stimulus-dependent rate and a quasi-periodic function. Further, we present an analysis method generalizing the direct method (Rieke et al, 1999; Brenner et al, 2000) to assess the information content in such data. We demonstrate these tools on recordings from relay cells in the lateral geniculate nucleus of the cat.Comment: 18 pages, 8 figures, to appear in Biological Cybernetic

Quantum physics meets biology

Quantum physics and biology have long been regarded as unrelated disciplines, describing nature at the inanimate microlevel on the one hand and living species on the other hand. Over the last decades the life sciences have succeeded in providing ever more and refined explanations of macroscopic phenomena that were based on an improved understanding of molecular structures and mechanisms. Simultaneously, quantum physics, originally rooted in a world view of quantum coherences, entanglement and other non-classical effects, has been heading towards systems of increasing complexity. The present perspective article shall serve as a pedestrian guide to the growing interconnections between the two fields. We recapitulate the generic and sometimes unintuitive characteristics of quantum physics and point to a number of applications in the life sciences. We discuss our criteria for a future quantum biology, its current status, recent experimental progress and also the restrictions that nature imposes on bold extrapolations of quantum theory to macroscopic phenomena.Comment: 26 pages, 4 figures, Perspective article for the HFSP Journa

Secondary contact and admixture between independently invading populations of the Western corn rootworm, diabrotica virgifera virgifera in Europe

The western corn rootworm, Diabrotica virgifera virgifera (Coleoptera: Chrysomelidae), is one of the most destructive pests of corn in North America and is currently invading Europe. The two major invasive outbreaks of rootworm in Europe have occurred, in North-West Italy and in Central and South-Eastern Europe. These two outbreaks originated from independent introductions from North America. Secondary contact probably occurred in North Italy between these two outbreaks, in 2008. We used 13 microsatellite markers to conduct a population genetics study, to demonstrate that this geographic contact resulted in a zone of admixture in the Italian region of Veneto. We show that i) genetic variation is greater in the contact zone than in the parental outbreaks; ii) several signs of admixture were detected in some Venetian samples, in a Bayesian analysis of the population structure and in an approximate Bayesian computation analysis of historical scenarios and, finally, iii) allelic frequency clines were observed at microsatellite loci. The contact between the invasive outbreaks in North-West Italy and Central and South-Eastern Europe resulted in a zone of admixture, with particular characteristics. The evolutionary implications of the existence of a zone of admixture in Northern Italy and their possible impact on the invasion success of the western corn rootworm are discussed