Dielectrophoresis: An Approach to Increase Sensitivity, Reduce Response Time and to Suppress Nonspecific Binding in Biosensors?

The performance of receptor-based biosensors is often limited by either diffusion of the analyte causing unreasonable long assay times or a lack of specificity limiting the sensitivity due to the noise of nonspecific binding. Alternating current (AC) electrokinetics and its effect on biosensing is an increasing field of research dedicated to address this issue and can improve mass transfer of the analyte by electrothermal effects, electroosmosis, or dielectrophoresis (DEP). Accordingly, several works have shown improved sensitivity and lowered assay times by order of magnitude thanks to the improved mass transfer with these techniques. To realize high sensitivity in real samples with realistic sample matrix avoiding nonspecific binding is critical and the improved mass transfer should ideally be specific to the target analyte. In this paper we cover recent approaches to combine biosensors with DEP, which is the AC kinetic approach with the highest selectivity. We conclude that while associated with many challenges, for several applications the approach could be beneficial, especially if more work is dedicated to minimizing nonspecific bindings, for which DEP offers interesting perspectives

Low dose X-ray speckle visibility spectroscopy reveals nanoscale dynamics in radiation sensitive ionic liquids

X-ray radiation damage provides a serious bottle neck for investigating {\mu}s to s dynamics on nanometer length scales employing X-ray photon correlation spectroscopy. This limitation hinders the investigation of real time dynamics in most soft matter and biological materials which can tolerate only X-ray doses of kGy and below. Here, we show that this bottleneck can be overcome by low dose X-ray speckle visibility spectroscopy. Employing X-ray doses of 22 kGy to 438 kGy and analyzing the sparse speckle pattern of count rates as low as 6.7x10-3 per pixel we follow the slow nanoscale dynamics of an ionic liquid (IL) at the glass transition. At the pre-peak of nanoscale order in the IL we observe complex dynamics upon approaching the glass transition temperature TG with a freezing in of the alpha relaxation and a multitude of milli-second local relaxations existing well below TG. We identify this fast relaxation as being responsible for the increasing development of nanoscale order observed in ILs at temperatures below TG.Comment: 7 pages, 5 figure

Climatic windows for human migration out of Africa in the past 300,000 years.

Whilst an African origin of modern humans is well established, the timings and routes of their expansions into Eurasia are the subject of heated debate, due to the scarcity of fossils and the lack of suitably old ancient DNA. Here, we use high-resolution palaeoclimate reconstructions to estimate how difficult it would have been for humans in terms of rainfall availability to leave the African continent in the past 300k years. We then combine these results with an anthropologically and ecologically motivated estimate of the minimum level of rainfall required by hunter-gatherers to survive, allowing us to reconstruct when, and along which geographic paths, expansions out of Africa would have been climatically feasible. The estimated timings and routes of potential contact with Eurasia are compatible with archaeological and genetic evidence of human expansions out of Africa, highlighting the key role of palaeoclimate variability for modern human dispersals

Smart Urban simulation tools for planning decision support need smart data and smart data gathering methods

Urban growth is a challenge for most cities all over the world, especially in less developed countries. This tendency calls for smart/innovative instruments to foster sustainable urban development. Decision support for urban planning is required in order to reduce costs and resources to better accommodate new population, willing to move into urban areas. Latin American countries e.g. went from being predominantly rural to predominantly urban within a few decades, leading to high concentrations of urban population. This urban growth is expected to continue leading to severe financial stress for city budgets by providing the required infrastructure. AIT - Austrian Institute of Technology has been contracted by the Inter-American Development Bank (IDB) to develop a smart “Urban Infrastructure Development Simulator” (UIDS) – a tool to performe urban growth simulation and related infrastructure cost estimations, which can be used effordless to support urban planning decissions. Therefore an Agent-based simulation model representing the urban growth by estimating dwelling behavior of the cities’ today’s residents and future residents from outside the urban region was developed. This urban growth simulation tool is based on input data with different spatial and temporal resolution. Data from Geographical Information Systems, Remote Sensing as well as statistical data are used to simulate scenarios for future development paths. To support the urban planning process such kind of tools need to have a high flexibility in data management, e.g., the import of new (e.g., more accurate) data to calculate new scenarios. But beyond this common need, what if the data is not or only partially available, how can a data gathering process be supported by new tools and methods. The paper will introduce different innovative ways urban planners can be supported to gain new data, which can be used in tools as the UIDS. The approaches developed enable the urban planners to easily introduce important tacit knowledge about the city into the simulation tool. Another method will depict how citizens participation for data collection can be enabled. The paper will further elaborate in general which challenges have been encountered and which solutions reduce the problems using different temporal and spatial data. The results discussed are based on experiences gathered whithin several urban growth simulation projects performed for different regions in Europe and Latin America

Cerebral connectivity and psychotic personality traits: A diffusion tensor imaging study

This study aims to investigate the relationship between regional connectivity in the brain white matter and the presence of psychotic personality traits, in healthy subjects with psychotic traits. Thirteen healthy controls were administered the MMPI-2, to assess psychotic traits and, according to MMPI results, a dichotomization into a group of "high-psychotic” and "low-psychotic” was performed. Diffusion tensor imaging (DTI) was used as a non-invasive measure, in order to obtain information about the fractional anisotropy (FA), an intravoxel index of local connectivity and, by means of a voxelwise approach, the between-group differences of the FA values were calculated. The "high-psychotic” group showed higher FA in the left arcuate fasciculus. Subjects with low scores for psychotic traits had significantly higher FA in the corpus callosum, right arcuate fasciculus, and fronto-parietal fibers. In line with previous brain imaging studies of schizophrenia spectrum disorders, our results suggest that psychotic personality traits are related to altered connectivity and brain asymmetr

Impact of Monthly Radioxenon Source Time-Resolution on Atmospheric Concentration Predictions

n/

Spectral Strong Motion Attenuation in Central America

A bayesian regression analysis of response spectral ordinates based on 218 digitized strong ground motion accelerograms (largest horizontal component) from Central America, augmented by 62 similar, high-magnitude observations from Guerrero, Mexico, has been performed using the simple linearized ground motion model: lnA = c1 + c2M + c3lnr +c4r = c5S + ln e where M is moment magnitude, r is hypocentral distance, S is zero for rock sites and 1 for soil sites and In£ is a normally distributed error term with zero mean and standard deviation sigma i.e. ln e = N (0, sigma) .Universidad de Costa Rica/[]/UCR/Costa RicaNorwegian Agency for International Cooperation/[]/NORAD/OsloInstituto Costarricense de Electricidad/[]/ICE/Costa RicaInstituto Nicaragüense de Estudios Territoriales/[]/INETER/NicaraguaCentro de Investigaciones Geotecnicas/[]/CIG/El SalvadorUniversidad Autónoma de México/[]/UNAM/MéxicoUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Instituto Investigaciones en Ingeniería (INII

What should European nephrology do with the new CKD-EPI equation?

Nephrology; CKD-EPI equationNefrologia; Equació CKD-EPINefrología; Ecuación CKD-EP

Improved root cause analysis supporting resilient production systems

Manufacturing companies struggle to be efficient and effective when conducting root cause analyses of production disturbances; a fact which hinders them from creating and developing resilient production systems. This article aims to describe the challenges and enablers identified in current research relating to the different phases of root cause analysis. A systematic literature review was conducted, in which a total of 14 challenges and 17 enablers are identified and described. These correlate to the different phases of root cause analysis. Examples of challenges are “need for expertise”, “employee bias”, “poor data quality” and “lack of data integration”, among others. Examples of enablers are “visualisation tools”, “collaborative platforms”, “thesaurus” and “machine learning techniques”. Based on these findings, the authors also propose potential areas for further research and then design inputs for new solutions to improve root cause analysis. This article provides a theoretical contribution in that it describes the challenges and enablers of root cause analysis and their correlation to the creation of resilient production systems. The article also provides practical contributions, with an overview of current research to support practitioners in gaining insights into potential solutions to be implemented and further developed, with the aim of improving root cause analysis in production systems