Bestowing the Blessing: Practical Strategies for Christian Educators

Christian teachers in the public schools who wish to improve student motivation and outcomes can effectively apply the strategies suggested by Smalley and Trent (1986) in The Blessing. Smalley and Trent set forth a five-fold plan for parents to bless their children with unconditional love and acceptance. The techniques of using meaningful touch, speaking words of honor, encouragement, and affirmation, and making an active commitment to student success are supported both by Scripture and research in educational best practices

Allyl isothiocyanate inhibits actin mediated intracellular transport in Arabidopsis thaliana.

Volatile allyl isothiocyanate (AITC) derives from the biodegradation of the glucosinolate sinigrin and has been associated with growth inhibition in several plants, including the model plant Arabidopsis thaliana. However, the underlying cellular mechanisms of this feature remain scarcely investigated in plants. In this study, we present evidence of an AITC-induced inhibition of actin-dependent intracellular transport in A. thaliana. A transgenic line of A. thaliana expressing yellow fluorescent protein (YFP)-tagged actin filaments was used to show attenuation of actin filament movement by AITC. This appeared gradually in a time- and dose-dependent manner and resulted in actin filaments appearing close to static. Further, we employed four transgenic lines with YFP-fusion proteins labeling the Golgi apparatus, endoplasmic reticulum (ER), vacuoles and peroxisomes to demonstrate an AITC-induced inhibition of actin-dependent intracellular transport of or, in these structures, consistent with the decline in actin filament movement. Furthermore, the morphologies of actin filaments, ER and vacuoles appeared aberrant following AITC-exposure. However, AITC-treated seedlings of all transgenic lines tested displayed morphologies and intracellular movements similar to that of the corresponding untreated and control-treated plants, following overnight incubation in an AITC-absent environment, indicating that AITC-induced decline in actin-related movements is a reversible process. These findings provide novel insights into the cellular events in plant cells following exposure to AITC, which may further expose clues to the physiological significance of the glucosinolate-myrosinase system© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/)

A mixture model approach to sample size estimation in two-sample comparative microarray experiments

Background: Choosing the appropriate sample size is an important step in the design of a microarray experiment, and recently methods have been proposed that estimate sample sizes for control of the False Discovery Rate (FDR). Many of these methods require knowledge of the distribution of effect sizes among the differentially expressed genes. If this distribution can be determined then accurate sample size requirements can be calculated. Results: We present a mixture model approach to estimating the distribution of effect sizes in data from two-sample comparative studies. Specifically, we present a novel, closed form, algorithm for estimating the noncentrality parameters in the test statistic distributions of differentially expressed genes. We then show how our model can be used to estimate sample sizes that control the FDR together with other statistical measures like average power or the false nondiscovery rate. Method performance is evaluated through a comparison with existing methods for sample size estimation, and is found to be very good. Conclusion: A novel method for estimating the appropriate sample size for a two-sample comparative microarray study is presented. The method is shown to perform very well when compared to existing methods

Enhancement of deep epileptiform activity in the EEG via 3-D adaptive spatial filtering,

The detection of epileptiform discharges (ED’s) in the electroencephalogram (EEG) is an important component in the diagnosis of epilepsy. However, when the epileptogenic source is located deep in the brain, the ED’s at the scalp are often masked by more superficial, higher-amplitude EEG activity. A noninvasive technique which uses an adaptive “beamformer” spatial filter has been investigated for the enhancement of signals from deep sources in the brain suspected of containing ED’s. A forward three-layer spherical model was used to relate a dipolar source to recorded signals to determine the beamformer’s spatial response constraints. The beamformer adapts, using the least-mean-squares (LMS) algorithm, to reduce signals from sources distant to some arbitrarily defined location in the brain. The beamformer produces three outputs, being the orthogonal components of the signal estimated to have arisen at or near the assumed location. Simulations were performed by using the same forward model to superimpose realistic ED’s on normal EEG recordings. The simulations show the beamformer’s ability to enhance signals emanating from deep foci by way of an enhancement ratio (ER), being the improvement in signal-to-noise ratio (SNR) to that observed at any of the scalp electrodes. The performance of the beamformer has been evaluated for 1) the number of scalp electrodes, 2) the recording montage, 3) dependence on the background EEG, 4) dependence on magnitude, depth, and orientation of epileptogenic focus, and 5) sensitivity to inaccuracies in the estimated location of the focus. Results from the simulations show the beamformer’s performance to be dependent on the number of electrodes and moderately sensitive to variations in the EEG background. Conversely, its performance appears to be largely independent of the amplitude and morphology of the ED. The dependence studies indicated that the beamformer’s performance was moderately dependent on eccentricity with the ER increasing as the dipolar source and the beamformer were moved from the center to the surface of the brain (1.51–2.26 for radial dipoles and 1.17–2.69 for tangential dipoles). The beamformer was also moderately dependent on variations in polar or azimuthal angle for radial and tangential dipoles. Higher ER’s tended to be seen for locations between electrode sites. The beamformer was more sensitive to inaccuracies in both polar and azimuthal location than depth of the dipolar source. For polar locations, an ER > 1.0 was achieved when the beamformer was located within 25 of a radial dipole and 35 of a tangential dipole. Similarly, angular ranges of 37.5 and 45 , respectively, for inaccuracies in azimuthal locations. Preliminary results from real EEG records, comprising 12 definite or questionable epileptiform events, from four patients, demonstrated the beamformer’s ability to enhance these events by a mean 100% (52%–215%) for referential data and a mean 104% (50%–145%) for bipolar data

Allyl-isothiocyanate treatment induces a complex transcriptional reprogramming including heat stress, oxidative stress and plant defence responses in Arabidopsis thaliana

Comparison of the transcriptional response to allyl-ITC with the CPR response. (XLSX 85 kb

A Sensor Fusion Algorithm for Filtering Pyrometer Measurement Noise in the Czochralski Crystallization Process

The Czochralski (CZ) crystallization process is used to produce monocrystalline silicon for solar cell wafers and electronics. Tight temperature control of the molten silicon is most important for achieving high crystal quality. SINTEF Materials and Chemistry operates a CZ process. During one CZ batch, two pyrometers were used for temperature measurement. The silicon pyrometer measures the temperature of the molten silicon. This pyrometer is assumed to be accurate, but has much high-frequency measurement noise. The graphite pyrometer measures the temperature of a graphite material. This pyrometer has little measurement noise. There is quite a good correlation between the two pyrometer measurements. This paper presents a sensor fusion algorithm that merges the two pyrometer signals for producing a temperature estimate with little measurement noise, while having significantly less phase lag than traditional lowpass- filtering of the silicon pyrometer. The algorithm consists of two sub-algorithms: (i) A dynamic model is used to estimate the silicon temperature based on the graphite pyrometer, and (ii) a lowpass filter and a highpass filter designed as complementary filters. The complementary filters are used to lowpass-filter the silicon pyrometer, highpass-filter the dynamic model output, and merge these filtered signals. Hence, the lowpass filter attenuates noise from the silicon pyrometer, while the graphite pyrometer and the dynamic model estimate those frequency components of the silicon temperature that are lost when lowpass-filtering the silicon pyrometer. The algorithm works well within a limited temperature range. To handle a larger temperature range, more research must be done to understand the process' nonlinear dynamics, and build this into the dynamic model

Improving multivariate data streams clustering.

Clustering data streams is an important task in data mining research. Recently, some algorithms have been proposed to cluster data streams as a whole, but just few of them deal with multivariate data streams. Even so, these algorithms merely aggregate the attributes without touching upon the correlation among them. In order to overcome this issue, we propose a new framework to cluster multivariate data streams based on their evolving behavior over time, exploring the correlations among their attributes by computing the fractal dimension. Experimental results with climate data streams show that the clusters' quality and compactness can be improved compared to the competing method, leading to the thoughtfulness that attributes correlations cannot be put aside. In fact, the clusters' compactness are 7 to 25 times better using our method. Our framework also proves to be an useful tool to assist meteorologists in understanding the climate behavior along a period of time.Edição dos Proceedings do 16th International Conference on Computational Science, San Diego, 2016

Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

Background Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking. Results In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p < 0.01) in 10 ecotypes, including 498 transcription factors and 315 transposable elements. The majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about regulatory interactions between transcription factors and their target genes in the model plant A. thaliana, we have adopted a powerful systems genetics approach- Network Component Analysis (NCA) to construct an in-silico transcriptional regulatory network model during response to cold stress. The resulting regulatory network contained 1,275 nodes and 7,720 connections, with 178 transcription factors and 1,331 target genes. Conclusions A. thaliana ecotypes exhibit considerable variation in transcriptome level responses to non-freezing cold stress treatment. Ecotype specific transcripts and related gene ontology (GO) categories were identified to delineate natural variation of cold stress regulated differential gene expression in the model plant A. thaliana. The predicted regulatory network model was able to identify new ecotype specific transcription factors and their regulatory interactions, which might be crucial for their local geographic adaptation to cold temperature. Additionally, since the approach presented here is general, it could be adapted to study networks regulating biological process in any biological systems

A study of the dissociative recombination of CaO + with electrons: Implications for Ca chemistry in the upper atmosphere

The dissociative recombination of CaO+ ions with electrons has been studied in a flowing afterglow reactor. CaO+ was generated by the pulsed laser ablation of a Ca target, followed by entrainment in an Ar+ ion/electron plasma. A kinetic model describing the gas-phase chemistry and diffusion to the reactor walls was fitted to the experimental data, yielding a rate coefficient of (3.0 ± 1.0) × 10¯⁷ cm³ molecule¯¹ s¯¹ at 295 K. This result has two atmospheric implications. First, the surprising observation that the Ca+/Fe+ ratio is ~8 times larger than Ca/Fe between 90 and 100 km in the atmosphere can now be explained quantitatively by the known ion-molecule chemistry of these two metals. Second, the rate of neutralization of Ca+ ions in a descending sporadic E layer is fast enough to explain the often explosive growth of sporadic neutral Ca layers

CRISPR/Cas9-mediated editing of Δ5 and Δ6 desaturases impairs Δ8-desaturation and docosahexaenoic acid synthesis in Atlantic salmon (Salmo salar L.)

The in vivo functions of Atlantic salmon fatty acyl desaturases (fads2), Δ6fads2-a, Δ6fads2-b, Δ6fads2-c and Δ5fads2 in long chain polyunsaturated fatty acid (LC-PUFA) synthesis in salmon and fish in general remains to be elucidated. Here, we investigate in vivo functions and in vivo functional redundancy of salmon fads2 using two CRISPR-mediated partial knockout salmon, Δ6abc/5Mt with mutations in Δ6fads2-a, Δ6fads2-b, Δ6fads2-c and Δ5fads2, and Δ6bcMt with mutations in Δ6fads2-b and Δ6fads2-c. F0 fish displaying high degree of gene editing (50–100%) were fed low LC-PUFA and high LC-PUFA diets, the former containing reduced levels of eicosapentaenoic (20:5n-3) and docosahexaenoic (22:6n-3) acids but higher content of linoleic (18:2n-6) and alpha-linolenic (18:3n-3) acids, and the latter containing high levels of 20:5n-3 and 22:6n-3 but reduced compositions of 18:2n-6 and 18:3n-3. The Δ6abc/5Mt showed reduced 22:6n-3 levels and accumulated Δ6-desaturation substrates (18:2n-6, 18:3n-3) and Δ5-desaturation substrate (20:4n-3), demonstrating impaired 22:6n-3 synthesis compared to wildtypes (WT). Δ6bcMt showed no effect on Δ6-desaturation compared to WT, suggesting Δ6 Fads2-a as having the predominant Δ6-desaturation activity in salmon, at least in the tissues analyzed. Both Δ6abc/5Mt and Δ6bcMt demonstrated significant accumulation of Δ8-desaturation substrates (20:2n-6, 20:3n-3) when fed low LC-PUFA diet. Additionally, Δ6abc/5Mt demonstrated significant upregulation of the lipogenic transcription regulator, sterol regulatory element binding protein-1 (srebp-1) in liver and pyloric caeca under reduced dietary LC-PUFA. Our data suggest a combined effect of endogenous LC-PUFA synthesis and dietary LC-PUFA levels on srebp-1 expression which ultimately affects LC-PUFA synthesis in salmon. Our data also suggest Δ8-desaturation activities for salmon Δ6 Fads2 enzymes.publishedVersio