There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

textPrior studies have emphasized that structural attributes are crucial to simultaneously pursuing exploration and exploitation, yet our understanding of antecedents of ambidexterity is still limited. Structural differentiation can help ambidextrous organizations to maintain multiple inconsistent and conflicting demands; however, differentiated exploratory and exploitative activities need to mobilized, coordinated, integrated, and applied. Based on this idea, we delineate formal and informal senior team integration mechanisms (i.e. contingency rewards and social integration) and formal and informal organizational integration mechanisms (i.e. cross-functional interfaces and connectedness) and examine how they mediate the relationship between structural differentiation and ambidexterity. Overall, our findings suggest that the previously asserted direct effect of structural differentiation on ambidexterity operates through informal senior team (i.e. senior team social integration) and formal organizational (i.e. cross-functional interfaces) integration mechanisms. Through this richer explanation and empirical assessment, we contribute to a greater clarity and better understanding of how organizations may effectively pursue exploration and exploitation simultaneously to achieve ambidexterity.

/pdf/structural-differentiation-and-ambidexterity-the-mediating-4tfwksgx8f.pdf

Structural Differentiation and Ambidexterity: The Mediating Role of Integration Mechanisms

A prospective study was undertaken in 606 healthy women during pregnancy to evaluate the changes occurring in maternal thyroid economy as a result of 1) the increased thyroid hormone-binding capacity of serum, 2) the effects of increased levels of hCG on TSH and on the thyroid, and 3) a marginally low iodine intake in the population (50-75 micrograms/day). Four main features were observed. First, thyroidal activity adjusted to the marked increase in serum T4-binding globulin: pregnancy was accompanied by an overall reduction in the T4/T4-binding globulin ratio, with lower free T4 and T3 levels, although in most cases free hormone levels remained within the normal range. The adjustment of thyroidal output of T4 and T3 did not occur similarly in all subjects. In approximately one third of the women, there was relative hypothyroxinemia, higher T3/T4 ratios (presumably indicating preferential T3 secretion), and higher, although normal, serum TSH concentrations. Second, high hCG levels were associated with thyroid stimulation, both functionally (lower serum TSH) and anatomically (increased thyroid size). The data are consistent with a TSH-like effect of hCG on the thyroid. Hence, regulation of the maternal thyroid is complex, resulting from both elevated hCG (mainly in the first half of gestation) and increasing TSH (mainly in the second half of gestation). Third, a significant increase in serum thyroglobulin levels was observed throughout gestation, especially during the last trimester. Fourth, increased thyroid volume was common, and goiter formation not uncommon (goiter was found in 9% of women at delivery). In conclusion, the alterations in maternal thyroid function during gestation are intricate and far from fully understood. In areas of marginally low iodine intake, gestation is associated in a significant number of women with relative hypothyroxinemia, increased thyroglobulin, and enlarged thyroid.

/pdf/regulation-of-maternal-thyroid-during-pregnancy-2om3s5f4qz.pdf

Regulation of Maternal Thyroid during Pregnancy

Recurrent neural networks RNNs are useful tools for learning nonlinear relationships between time-varying inputs and outputs with complex temporal dependencies. Recently developed algorithms have been successful at training RNNs to perform a wide variety of tasks, but the resulting networks have been treated as black boxes: their mechanism of operation remains unknown. Here we explore the hypothesis that fixed points, both stable and unstable, and the linearized dynamics around them, can reveal crucial aspects of how RNNs implement their computations. Further, we explore the utility of linearization in areas of phase space that are not true fixed points but merely points of very slow movement. We present a simple optimization technique that is applied to trained RNNs to find the fixed and slow points of their dynamics. Linearization around these slow regions can be used to explore, or reverse-engineer, the behavior of the RNN. We describe the technique, illustrate it using simple examples, and finally showcase it on three high-dimensional RNN examples: a 3-bit flip-flop device, an input-dependent sine wave generator, and a two-point moving average. In all cases, the mechanisms of trained networks could be inferred from the sets of fixed and slow points and the linearized dynamics around them.

https://barak.net.technion.ac.il/files/2012/11/sussillo_barak-neco.pdf

Opening the black box: Low-dimensional dynamics in high-dimensional recurrent neural networks

Corrosion and surface modification on biocompatible metals: A review.

Collaborative diversity in a nanotechnology innovation system: Evidence from the EU Framework Programme

Regulation for nanomaterials is urgently needed, and the drive to adopt an intelligent testing strategy is evident. Such a strategy will not only provide economic benefits but will also reduce moral and ethical concerns arising from animal testing. For regulatory purposes, such an approach is promoted by REACH, particularly the use of quantitative structure-activity relationships [(Q)SAR] as a tool for the categorisation of compounds according to their physicochemical and toxicological properties. In addition to compounds, (Q)SAR has also been applied to nanomaterials in the form of nano(Q)SAR. Although (Q)SAR in chemicals is well established, nano(Q)SAR is still in early stages of development and its successful uptake is far from reality. This article aims to identify some of the pitfalls and challenges associated with nano-(Q)SARs in relation to the categorisation of nanomaterials. Our findings show clear gaps in the research framework that must be addressed if we are to have reliable predictions from such models. Three major barriers were identified: the need to improve quality of experimental data in which the models are developed from, the need to have practical guidelines for the development of the nano(Q)SAR models and the need to standardise and harmonise activities for the purpose of regulation. Of these three, the first, i.e. the need to improve data quality requires immediate attention, as it underpins activities associated with the latter two. It should be noted that the usefulness of data in the context of nano-(Q)SAR modelling is not only about the quantity of data but also about the quality, consistency and accessibility of those data.

/pdf/nano-q-sar-challenges-pitfalls-and-perspectives-12gxru8400.pdf

Nano(Q)SAR: Challenges, pitfalls and perspectives.

(Q)SAR Modelling of Nanomaterial Toxicity - A Critical Review

Sensitive test for thyroid hormone autoantibodies in serum.

A central challenge for the safe design of nanomaterials (NMs) is the inherent variability of NM properties, both as produced and as they interact with and evolve in, their surroundings. This has led to uncertainty in the literature regarding whether the biological and toxicological effects reported for NMs are related to specific NM properties themselves, or rather to the presence of impurities or physical effects such as agglomeration of particles. Thus, there is a strong need for systematic evaluation of the synthesis and processing parameters that lead to potential variability of different NM batches and the reproducible production of commonly utilized NMs. The work described here represents over three years of effort across 14 European laboratories to assess the reproducibility of nanoparticle properties produced by the same and modified synthesis routes for four of the OECD priority NMs (silica dioxide, zinc oxide, cerium dioxide and titanium dioxide) as well as amine-modified polystyrene NMs, which are frequently employed as positive controls for nanotoxicity studies. For 46 different batches of the selected NMs, all physicochemical descriptors as prioritized by the OECD have been fully characterized. The study represents the most complete assessment of NMs batch-to-batch variability performed to date and provides numerous important insights into the potential sources of variability of NMs and how these might be reduced.

/pdf/characterization-of-nanoparticle-batch-to-batch-variability-26c9up21db.pdf

T A Wilkins

Papers

Collaborative diversity in a nanotechnology innovation system: Evidence from the EU Framework Programme

Nano(Q)SAR: Challenges, pitfalls and perspectives.

(Q)SAR Modelling of Nanomaterial Toxicity - A Critical Review

Sensitive test for thyroid hormone autoantibodies in serum.

Characterization of Nanoparticle Batch-To-Batch Variability.