Addendum no. 1 to final development report

Pseudo-linearity concept impact on linear filters designed to ease pulse crowding effects at high bit densitie

A computer simulation of digital recording Final development progress report, 29 Dec. 1966 - 29 Dec. 1967

Fourier series digital computer simulation of tape recording process - signal detection in prescence of white Gaussian nois

Microcrystals coating the wing membranes of a living insect (Psocoptera: Psyllipsocidae) from a Brazilian cave

Two specimens of Psyllipsocus yucatan with black wings were found with normal individuals of this species on guano piles produced by the common vampire bat Desmodus rotundus. These specimens have both pairs of wings dorsally and ventrally covered by a black crystalline layer. They did not exhibit any signs of reduced vitality in the field and their morphology is completely normal. This ultrathin (1.5 µm) crystalline layer, naturally deposited on a biological membrane, is documented by photographs, SEM micrographs, energy dispersive spectroscopy (EDS) and X-ray diffractometry (XRD). The crystalline deposit contains iron, carbon and oxygen, but the mineral species could not be identified. Guano probably played a role in its formation; the presence of iron may be a consequence of the excretion of iron by the common vampire bat. This enigmatic phenomenon lacks obvious biological significance but may inspire bionic applications. Nothing similar has ever been observed in terrestrial arthropods

New and extended parameterization of the thermodynamic model AIOMFAC: calculation of activity coefficients for organic-inorganic mixtures containing carboxyl, hydroxyl, carbonyl, ether, ester, alkenyl, alkyl, and aromatic functional groups

We present a new and considerably extended parameterization of the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients) at room temperature. AIOMFAC combines a Pitzer-like electrolyte solution model with a UNIFAC-based group-contribution approach and explicitly accounts for interactions between organic functional groups and inorganic ions. Such interactions constitute the salt-effect, may cause liquid-liquid phase separation, and affect the gas-particle partitioning of aerosols. The previous AIOMFAC version was parameterized for alkyl and hydroxyl functional groups of alcohols and polyols. With the goal to describe a wide variety of organic compounds found in atmospheric aerosols, we extend here the parameterization of AIOMFAC to include the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkenyl, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon. Thermodynamic equilibrium data of organic-inorganic systems from the literature are critically assessed and complemented with new measurements to establish a comprehensive database. The database is used to determine simultaneously the AIOMFAC parameters describing interactions of organic functional groups with the ions H^+, Li^+, Na^+, K^+, NH_(4)^+, Mg^(2+), Ca^(2+), Cl^−, Br^−, NO_(3)^−, HSO_(4)^−, and SO_(4)^(2−). Detailed descriptions of different types of thermodynamic data, such as vapor-liquid, solid-liquid, and liquid-liquid equilibria, and their use for the model parameterization are provided. Issues regarding deficiencies of the database, types and uncertainties of experimental data, and limitations of the model, are discussed. The challenging parameter optimization problem is solved with a novel combination of powerful global minimization algorithms. A number of exemplary calculations for systems containing atmospherically relevant aerosol components are shown. Amongst others, we discuss aqueous mixtures of ammonium sulfate with dicarboxylic acids and with levoglucosan. Overall, the new parameterization of AIOMFAC agrees well with a large number of experimental datasets. However, due to various reasons, for certain mixtures important deviations can occur. The new parameterization makes AIOMFAC a versatile thermodynamic tool. It enables the calculation of activity coefficients of thousands of different organic compounds in organic-inorganic mixtures of numerous components. Models based on AIOMFAC can be used to compute deliquescence relative humidities, liquid-liquid phase separations, and gas-particle partitioning of multicomponent mixtures of relevance for atmospheric chemistry or in other scientific fields

Principles in the Design of Mobile Medical Apps: Guidance for Those who Care

The promises of mobile technology in healthcare have led to a great many mobile apps in public app stores that target patients with specific illnesses. Medical experts have criticized the status quo of mobile medical apps owing to the low level of professional medical involvement in mobile app design, leading to weak clinical performance and a poor integration of these tools into clinical practice. Grounded in an action design research study, we build and evaluate a mobile app for elderly patients with age-related macular degeneration. We formalize our learnings and provide a set of design principles to guide the effective and feasible construction of mobile medical apps. Our study systematically develops design knowledge that helps to bridge the current gap between the rapid advances in mobile technology and the specific needs of the healthcare sector

On Real Fluid Flow Over Yawed Circular Cylinders

The equations for both the boundary layer and the outer potential flow over a yawed cylinder can be resolved into equations for the crosswise and spanwise velocity components. These components of the boundary layer are evaluated using Sears’ method, and the separation point is found to be uninfluenced by the yaw angle. The potential-flow solutions for the spanwise and crosswise flows are added together to determine vortex patterns behind the cylinder. The approximate direct dependence of the Strouhal number upon the cosine of the yaw angle and/or the drag coefficient upon the square of the cosine, are verified. Experimental determinations of the Strouhal number and visualization of the flow pattern are consistent with the analysis

Large-scale literature mining to assess the relation between anti-cancer drugs and cancer types

Background:There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually.Methods:In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data.Results:We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap.Conclusions:Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the inter-active knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs

Simultaneous position and mass determination of a nanoscale-thickness cantilever sensor in viscous fluids

We report simultaneous determination of the mass and position of micro-beads attached to a nanoscale-thickness cantilever sensor by analyzing wave propagations along the cantilever while taking into account viscous and inertial loading due to a surrounding fluid. The fluid-structure interaction was identified by measuring the change in the wavenumber under different fluid conditions. The predicted positions and masses agreed with actual measurements. Even at large mass ratios (6%-21%) of the beads to the cantilever, this wave approach enabled accurate determination of the mass and position, demonstrating the potential for highly accurate cantilever sensing of particle-based bio-analytes such as bacteria. © 2015 AIP Publishing LLCopen0

Novel nanomaterials for water desalination technology

Water desalination has a central role to play in the global challenge for sustainable water supply in the 21st century. But while the membranes employed in reverse osmosis (RO) have benefited from substantial improvements over the past 25 years, several recent advances in materials suggest that new membranes with dramatically higher water permeability will become available in the future. After providing an overview of the importance of membranes for sustainable water production, we describe some of the most exciting novel approaches for water desalination based on nanomaterials. In particular, graphene, a single-layer sheet of carbon with remarkable mechanical and electronic properties, can be patterned with nanometer-sized pores, to act as an ultra-thin filtration membrane. Drawing from our group's research at MIT, we will share some of our key findings about the potential impact of nanomaterials as membranes for water desalination in the 21st century.MIT Energy InitiativeNational Science Foundation (U.S.)MIT Energy Initiative. Seed Fund ProgramJohn S. Hennessy Fellowshi

Quantifying the potential of ultra-permeable membranes for water desalination

In the face of growing water scarcity, it is critical to understand the potential of saltwater desalination as a long-term water supply option. Recent studies have highlighted the promise of new membrane materials that could desalinate water while exhibiting far greater permeability than conventional reverse osmosis (RO) membranes, but the question remains whether higher permeability can translate into significant reductions in the cost of desalinating water. Here, we address a critical question by evaluating the potential of such ultra-permeable membranes (UPMs) to improve the performance and cost of RO. By modeling the mass transport inside RO pressure vessels, we quantify how much a tripling in the water permeability of a membrane would reduce the energy consumption or the number of required pressure vessels for a given RO plant. We find that a tripling in permeability would allow for 44% fewer pressure vessels or 15% less energy for a seawater RO plant with a given capacity and recovery ratio. Moreover, a tripling in permeability would result in 63% fewer pressure vessels or 46% less energy for brackish water RO. However, we also find that the energy savings of UPMs exhibit a law of diminishing returns due to thermodynamics and concentration polarization at the membrane surface.National Science Foundation (U.S.). Graduate Research FellowshipMIT Energy Initiative (Seed Grant Program)Fulbright Program (International Science and Technology Award Program)International Desalination Association (Channabasappa Memorial Scholarship)Martin Family Fellowship for Sustainabilit