Adolescent Literacy Programs: Costs of Implementation

Reviews the literature on implementation of educational reforms and compares implementation processes and costs at schools that have adopted one of three literacy reforms. Includes recommendations for detailed resource planning and cost accounting

Revisiting Multi-Step Nonlinearity Compensation with Machine Learning

For the efficient compensation of fiber nonlinearity, one of the guiding principles appears to be: fewer steps are better and more efficient. We challenge this assumption and show that carefully designed multi-step approaches can lead to better performance-complexity trade-offs than their few-step counterparts.Comment: 4 pages, 3 figures, This is a preprint of a paper submitted to the 2019 European Conference on Optical Communicatio

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

In this paper, we propose a model-based machine-learning approach for dual-polarization systems by parameterizing the split-step Fourier method for the Manakov-PMD equation. The resulting method combines hardware-friendly time-domain nonlinearity mitigation via the recently proposed learned digital backpropagation (LDBP) with distributed compensation of polarization-mode dispersion (PMD). We refer to the resulting approach as LDBP-PMD. We train LDBP-PMD on multiple PMD realizations and show that it converges within 1% of its peak dB performance after 428 training iterations on average, yielding a peak effective signal-to-noise ratio of only 0.30 dB below the PMD-free case. Similar to state-of-the-art lumped PMD compensation algorithms in practical systems, our approach does not assume any knowledge about the particular PMD realization along the link, nor any knowledge about the total accumulated PMD. This is a significant improvement compared to prior work on distributed PMD compensation, where knowledge about the accumulated PMD is typically assumed. We also compare different parameterization choices in terms of performance, complexity, and convergence behavior. Lastly, we demonstrate that the learned models can be successfully retrained after an abrupt change of the PMD realization along the fiber.Comment: 10 pages, 11 figures, to appear in the IEEE/OSA Journal of Lightwave Technolog

Model-Based Machine Learning for Joint Digital Backpropagation and PMD Compensation

We propose a model-based machine-learning approach for polarization-multiplexed systems by parameterizing the split-step method for the Manakov-PMD equation. This approach performs hardware-friendly DBP and distributed PMD compensation with performance close to the PMD-free case.Comment: 3 pages, 2 figure

A chemical genetic approach reveals distinct EphB signaling mechanisms during brain development.

EphB receptor tyrosine kinases control multiple steps in nervous system development. However, it remains unclear whether EphBs regulate these different developmental processes directly or indirectly. In addition, given that EphBs signal through multiple mechanisms, it has been challenging to define which signaling functions of EphBs regulate particular developmental events. To address these issues, we engineered triple knock-in mice in which the kinase activity of three neuronally expressed EphBs can be rapidly, reversibly and specifically blocked. We found that the tyrosine kinase activity of EphBs was required for axon guidance in vivo. In contrast, EphB-mediated synaptogenesis occurred normally when the kinase activity of EphBs was inhibited, suggesting that EphBs mediate synapse development by an EphB tyrosine kinase-independent mechanism. Taken together, our data indicate that EphBs control axon guidance and synaptogenesis by distinct mechanisms and provide a new mouse model for dissecting EphB function in development and disease

Efficient plant regeneration protocol for finger millet [Eleusine coracana (L.) Gaertn.] via somatic embryogenesis

In the present study, an efficient protocol for somatic embryogenesis and plant regeneration was established in six finger millet varieties (GBK-043137, GBK-043128, GBK-043124, GBK-043122, GBK- 043094 and GBK-043050). Shoot tips from 3 days in vitro grown plants were inoculated on MS supplemented with various concentrations and combinations of α-naphthaleneacetic acid (NAA), 2,4- Dichlorophenoxyacetic acid (2,4-D), benzylaminopurine (BAP) and kinetin for callus induction and somatic embryogenesis. For shoot regeneration, somatic embryos were cultured on various concentrations of BAP, while root induction was done using different concentrations and combinations of NAA, kinetin, BAP and 2,4-D. Acclimatization of regenerated plants was tested using forest soil, cocopeat, manure, sand and fertilizer either singly or in combination. Best callus formation was achieved on 2.5 mg/l of 2,4-D and 1.5 mg/l BAP with a mean of 12.33±0.33 on variety GBK-043128 while shooting and rooting were best on 1.75 mg/l BAP with a mean of 25.07±0.64 and 1.0 BAP+0.25 NAA with a mean of 15.00±2.2, respectively. Best acclimatization was attained using soil, sand and fertilizer on GBK-043094. Plants regenerated were morphologically similar to in vivo plants with 97% survival rate. Moreover, they were fertile and able to set viable seeds. This efficient protocol has the potential for crop improvement and genomic studies