Nurturing Plasmonic Properties of Nanocomposite Thin Films: The Importance of Optimum Oblate Shape

Metal nanoparticles (MNPs) embedded dielectric thin films are very crucial for many optoelectronic applications. This report investigates various ways of tuning the plasmonic properties of such nanocomposite thin films. For this, the well-known plasmon resonance condition was first generalized to include the shape and volume fraction of MNPs. This was followed by deriving an empirical formula for the resonance position (λR) which was worked out to be the positive root of a quadratic equation. The coefficients of the deduced quadratic relation involve the parameters obtained from the empirical fit to some of the experimental dielectric functions of MNPs available in literature. The derived working formula enables research community to tune the LSPR of nanocomposites in the whole range of visible wavelengths. The derived formula also concluded that with known lower volume fractions, shape of MNPs affects λR the most, compared to the other parameters. The derived formula was validated by calculating the full extinction spectra. It was shown for the first time that there exists an optimum value of oblate shape to give maximum resonance for a given nanocomposite.

An integrated strategy for managing Grapevine leafroll-associated virus 3 in red berry cultivars in New Zealand vineyards

<p>To sustain growth and revenue projections, the New Zealand wine sector aims to produce premium quality wine to supply lucrative export markets. In grapevines, however, the presence of virus and virus-like diseases can negatively influence qualitative parameters of wine production. Where such risks are identified, sustainable remediation protocols should be developed. One risk factor is Grapevine leafroll-associated virus 3 (GLRaV-3), an economically important virus of Vitis. In this thesis, I develop components of an integrated management plan with the aim of reducing and sustaining GLRaV-3 incidence at <1%. In Hawke’s Bay vineyard study blocks, three aspects related to GLRaV-3 management were explored between 2008 and 2013: Firstly, herbicide-treated vines and/or land left fallow after removing infected vines may mitigate the effects of GLRaV-3. Historically though, vine root removal was not well implemented, meaning persistent roots may be long term reservoirs for GLRaV-3. I tested the virus reservoir hypothesis in vineyard blocks where virus incidence of ≥95% necessitated removing all vines. Enzyme-linked immunosorbent assay (ELISA) and/or real-time polymerase chain reaction (real-time PCR) detected GLRaV-3 in most remnant root samples tested, independent of the herbicide active ingredient applied (glyphosate, triclopyr, or metsulfuron) or the fallow duration (6 months to 4 years). On some virus-positive root samples, the GLRaV-3 mealybug vector, Pseudococcus calceolariae, was found, and after real-time PCR testing, virus was detected in some mealybugs. Thus, without effective vine removal, unmanaged sources of virus inoculum and viruliferous vectors could pose a risk to the health of replacement vines. Secondly, in most red berry cultivars, GLRaV-3 is characterised by dark red downward curling leaves with green veins. With visual diagnostics predicted to be a reliable identifier of GLRaV-3-symptomatic red berry vines, early identification could support a cost-effective and sustainable virus management plan. In blocks planted in Merlot, Cabernet Sauvignon, Syrah, and Malbec vines, the reliability of visual symptom identification was compared with ELISA. In terms of sensitivity (binomial generalised linear model, 0.966) and specificity (0.998), late-season visual diagnostics reliably predicted virus infection. Moreover, accuracy appeared unaffected by the genetically divergent GLRaV-3 populations detected in Hawke’s Bay. Thirdly, by acting to visually identify and remove (rogue) symptomatic vines when GLRaV-3 incidence is low (<20%), an epidemic may be averted. In this ongoing study, an integrated approach to virus management was adopted in 13 well established Hawke’s Bay vineyard study blocks. All were planted in vines from one of five red berry cultivars. When monitoring commenced in 2009, all symptomatic vines visually identified (n=2,544 or 12%) were rogued. Thereafter, integrating visual diagnostics with roguing reduced virus incidence so that by 2013, just 434 (2.0%) vines were identified with virus symptoms. Annual monitoring revealed within-row vines immediately either side of an infected vine were most at risk of vector mediated virus transmission, although by 2013, just 4% of these vines had virus symptoms. Hence, roguing symptomatic vines only was recommended. In individual study blocks in 2013, virus management was tracking positively in four blocks; while in another four, results were inconclusive. In the remaining five blocks, contrasting but definitive results were evident. In three of those blocks, mean virus incidence of 10% in 2009 was sustained at ≤0.3% within 2-3 years of roguing commencing; in the other two blocks, mean incidence was 12% but cumulative vine losses of 37% (2011) and 46% (2013) culminated in roguing being replaced with whole block removal. In all five blocks, roguing protocols were standardised but in those with effective virus control, mealybug numbers were significantly lower in all years (mean: <0.2 per vine leaf; p≤0.036) relative to those where all vines were removed (mean: 0.4-2.3 per vine leaf). Overall, the results of this research suggest that rather than adopting a single management tactic in isolation, effective GLRaV-3 control instead requires an integrated plan to be implemented annually.</p>

An integrated strategy for managing Grapevine leafroll-associated virus 3 in red berry cultivars in New Zealand vineyards

<p>To sustain growth and revenue projections, the New Zealand wine sector aims to produce premium quality wine to supply lucrative export markets. In grapevines, however, the presence of virus and virus-like diseases can negatively influence qualitative parameters of wine production. Where such risks are identified, sustainable remediation protocols should be developed. One risk factor is Grapevine leafroll-associated virus 3 (GLRaV-3), an economically important virus of Vitis. In this thesis, I develop components of an integrated management plan with the aim of reducing and sustaining GLRaV-3 incidence at <1%. In Hawke’s Bay vineyard study blocks, three aspects related to GLRaV-3 management were explored between 2008 and 2013: Firstly, herbicide-treated vines and/or land left fallow after removing infected vines may mitigate the effects of GLRaV-3. Historically though, vine root removal was not well implemented, meaning persistent roots may be long term reservoirs for GLRaV-3. I tested the virus reservoir hypothesis in vineyard blocks where virus incidence of ≥95% necessitated removing all vines. Enzyme-linked immunosorbent assay (ELISA) and/or real-time polymerase chain reaction (real-time PCR) detected GLRaV-3 in most remnant root samples tested, independent of the herbicide active ingredient applied (glyphosate, triclopyr, or metsulfuron) or the fallow duration (6 months to 4 years). On some virus-positive root samples, the GLRaV-3 mealybug vector, Pseudococcus calceolariae, was found, and after real-time PCR testing, virus was detected in some mealybugs. Thus, without effective vine removal, unmanaged sources of virus inoculum and viruliferous vectors could pose a risk to the health of replacement vines. Secondly, in most red berry cultivars, GLRaV-3 is characterised by dark red downward curling leaves with green veins. With visual diagnostics predicted to be a reliable identifier of GLRaV-3-symptomatic red berry vines, early identification could support a cost-effective and sustainable virus management plan. In blocks planted in Merlot, Cabernet Sauvignon, Syrah, and Malbec vines, the reliability of visual symptom identification was compared with ELISA. In terms of sensitivity (binomial generalised linear model, 0.966) and specificity (0.998), late-season visual diagnostics reliably predicted virus infection. Moreover, accuracy appeared unaffected by the genetically divergent GLRaV-3 populations detected in Hawke’s Bay. Thirdly, by acting to visually identify and remove (rogue) symptomatic vines when GLRaV-3 incidence is low (<20%), an epidemic may be averted. In this ongoing study, an integrated approach to virus management was adopted in 13 well established Hawke’s Bay vineyard study blocks. All were planted in vines from one of five red berry cultivars. When monitoring commenced in 2009, all symptomatic vines visually identified (n=2,544 or 12%) were rogued. Thereafter, integrating visual diagnostics with roguing reduced virus incidence so that by 2013, just 434 (2.0%) vines were identified with virus symptoms. Annual monitoring revealed within-row vines immediately either side of an infected vine were most at risk of vector mediated virus transmission, although by 2013, just 4% of these vines had virus symptoms. Hence, roguing symptomatic vines only was recommended. In individual study blocks in 2013, virus management was tracking positively in four blocks; while in another four, results were inconclusive. In the remaining five blocks, contrasting but definitive results were evident. In three of those blocks, mean virus incidence of 10% in 2009 was sustained at ≤0.3% within 2-3 years of roguing commencing; in the other two blocks, mean incidence was 12% but cumulative vine losses of 37% (2011) and 46% (2013) culminated in roguing being replaced with whole block removal. In all five blocks, roguing protocols were standardised but in those with effective virus control, mealybug numbers were significantly lower in all years (mean: <0.2 per vine leaf; p≤0.036) relative to those where all vines were removed (mean: 0.4-2.3 per vine leaf). Overall, the results of this research suggest that rather than adopting a single management tactic in isolation, effective GLRaV-3 control instead requires an integrated plan to be implemented annually.</p>

SolveSAPHE-r2 (v2.0.1): revisiting and extending the Solver Suite for Alkalinity-PH Equations for usage with CO₂, HCO₃⁻ or CO₃²⁻ input data

The successful and efficient approach at the basis of the Solver Suite for Alkalinity-PH Equations (SolveSAPHE) (Munhoven, 2013), which determines the carbonate system speciation by calculating pH from total alkalinity (AlkT) and dissolved inorganic carbon (CT), and which converges for any physically sensible pair of such data, has been adapted and further developed to work with AlkT–CO2, AlkT–HCO3-, and AlkT–CO32-. The mathematical properties of the three modified alkalinity–pH equations are explored. It is shown that the AlkT–CO2, and AlkT–HCO3- problems have one and only one positive root for any physically sensible pair of data (i.e. such that [CO2]>0 and [HCO3-]>0). The space of AlkT–CO32- pairs is partitioned into regions where there is either no solution, one solution or where there are two. The numerical solution of the modified alkalinity–pH equations is far more demanding than that for the original AlkT–CT pair as they exhibit strong gradients and are not always monotonous. The two main algorithms used in SolveSAPHE v1 have been revised in depth to reliably process the three additional data input pairs. The AlkT–CO2 pair is numerically the most challenging. With the Newton–Raphson-based solver, it takes about 5 times as long to solve as the companion AlkT–CT pair; the AlkT–CO32- pair requires on average about 4 times as much time as the AlkT–CT pair. All in all, the secant-based solver offers the best performance. It outperforms the Newton–Raphson-based one by up to a factor of 4 in terms of average numbers of iterations and execution time and yet reaches equation residuals that are up to 7 orders of magnitude lower. Just like the pH solvers from the v1 series, SolveSAPHE-r2 includes automatic root bracketing and efficient initialisation schemes for the iterative solvers. For AlkT–CO32- data pairs, it also determines the number of roots and calculates non-overlapping bracketing intervals. An open-source reference implementation of the new algorithms in Fortran 90 is made publicly available for usage under the GNU Lesser General Public Licence version 3 (LGPLv3) or later.

On the Roots of the Modified Orbit Polynomial of a Graph

The definition of orbit polynomial is based on the size of orbits of a graph which is OG(x)=∑ix|Oi|, where O1,…,Ok are all orbits of graph G. It is a well-known fact that according to Descartes’ rule of signs, the new polynomial 1−OG(x) has a positive root in (0,1), which is unique and it is a relevant measure of the symmetry of a graph. In the current work, several bounds for the unique and positive zero of modified orbit polynomial 1−OG(x) are investigated. Besides, the relation between the unique positive root of OG in terms of the structure of G is presented.

SolveSAPHE-r2: a new versatile 4x4 engine for carbonate system pH calculations

&lt;p&gt;SolveSAPHE, the Solver Suite for Alkalinity-PH Equations (Munhoven, 2013, DOI:10.5194/gmd-6-1367-2013), hereafter SolveSAPHE v.1, was the first carbonate chemistry speciation package that was able to securely and reliably calculate pH for any physically meaningful pair of total alkalinity (Alk&lt;sub&gt;T&lt;/sub&gt;) and dissolved inorganic carbon (&lt;em&gt;C&lt;/em&gt;&lt;sub&gt;T&lt;/sub&gt;) values. We have now revised and extended the solution approach developed for SolveSAPHE v.1 so that Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;2&lt;/sub&gt;, Alk&lt;sub&gt;T&lt;/sub&gt; &amp; HCO&lt;sub&gt;3&lt;/sub&gt; and Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;3&lt;/sub&gt; problems can be processed as well.&lt;/p&gt;&lt;p&gt;The mathematical analysis of the modified alkalinity-pH equations reveals that the Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;2&lt;/sub&gt; and Alk&lt;sub&gt;T&lt;/sub&gt; &amp; HCO&lt;sub&gt;3&lt;/sub&gt; problems have one and only one positive root for any physically sensible pair of data (i.e., such that, resp., [CO&lt;sub&gt;2&lt;/sub&gt;] &gt; 0 and [HCO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8211;&lt;/sup&gt;] &gt; 0). For Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;3&lt;/sub&gt; the situation is completely different: there are pairs of data values for which there is no solution, others for which there is one and still others for which there are two. Similarly to its predecessor, the new SolveSAPHE-r2 offers automatic root bracketing and efficient initialisation schemes for the iterative solvers. The Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;3&lt;/sub&gt; problem is furthermore autonomously and completely characterised: for any given pair of data values, the number of solutions is determined and non-overlapping bracketing intervals are calculated.&lt;/p&gt;&lt;p&gt;The numerical solution of the alkalinity-pH equations for the three new pairs is far more difficult than for the Alk&lt;sub&gt;T&lt;/sub&gt; &amp; &lt;em&gt;C&lt;/em&gt;&lt;sub&gt;T&lt;/sub&gt; pair. The Newton-Raphson and the secant based solvers from SolveSAPHE v.1 had to be reworked in depth to reliably process the three additional data input pairs. The Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;2&lt;/sub&gt; pair is computationally the most demanding. With the Newton-Raphson based solver, it takes about five times as long to solve as the companion Alk&lt;sub&gt;T&lt;/sub&gt; &amp; &lt;em&gt;C&lt;/em&gt;&lt;sub&gt;T&lt;/sub&gt; pair, while Alk&lt;sub&gt;T&lt;/sub&gt; &amp; CO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;2&amp;#8211;&lt;/sup&gt; requires about four times as much time. All in all, the secant based solver offers the best performances. It outperforms the Newton-Raphson based one by up to a factor of four and leads to equation residuals that are up to seven orders of magnitude lower. For carbonate speciation problems posed by Alk&lt;sub&gt;T&lt;/sub&gt; and either one of [CO&lt;sub&gt;2&lt;/sub&gt;], [HCO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;&amp;#8211;&lt;/sup&gt;] or [CO&lt;sub&gt;3&lt;/sub&gt;&lt;sup&gt;2&amp;#8211;&lt;/sup&gt;] the secant based routine from SolveSAPHE-r2 is clearly the method of choice; for calculations with Alk&lt;sub&gt;T&lt;/sub&gt; &amp; &lt;em&gt;C&lt;/em&gt;&lt;sub&gt;T&lt;/sub&gt;, the SolveSAPHE v.1 solvers will perform better, due to the mathematically favourable characteristics of the alkalinity-pH equation for that pair.&lt;/p&gt;

SolveSAPHE-r2: revisiting and extending the Solver Suite for Alkalinity-PH Equations for usage with CO₂, HCO₃⁻ or CO₃²⁻ input data

The successful and efficient approach at the basis of SolveSAPHE (Munhoven, 2013), which determines the carbonate system speciation by calculating pH from total alkalinity (AlkT) and dissolved inorganic carbon (CT), and which converges from any physically sensible pair of such data, has been adapted and further developed for work with AlkT &amp; CO2, AlkT &amp; HCO3− and AlkT &amp; CO32−. The mathematical properties of the three modified alkalinity-pH equations are explored. It is shown that the AlkT &amp; CO2 and AlkT &amp; HCO3− problems have one and only one positive root for any physically sensible pair of data (i.e., such that, resp., [CO2] > 0 and [HCO3−] > 0). The space of AlkT &amp; CO32− pairs is partitioned into regions where there is either no solution, one solution or where there are two. The numerical solution of the modified alkalinity-pH equations is far more demanding than that for the original AlkT-CT pair as they exhibit strong gradients and are not always monotonous. The two main algorithms used from SolveSAPHE v.1 had to be revised in depth to reliably process the three additional data input pairs. The AlkT &amp; CO2 pair is numerically the most challenging. With the Newton-Raphson based solver, it takes about five times as long to solve as the companion AlkT &amp; CT pair, while AlkT &amp; CO2 requires about four times as much time. All in all, it is nevertheless the secant based solver that offers the best performances. It outperforms the Newton-Raphson based one by up to a factor of four, to reach equation residuals that are up to seven orders of magnitude lower. Just like the pH solvers from routines from the v.1 series, SolveSAPHE v.2 includes automatic root bracketing and efficient initialisation schemes for the iterative solvers. For AlkT &amp; CO32− pairs of data, it also determines the number of roots and calculates non-overlapping bracketing intervals. An open source reference implementation in Fortran 90 of the new algorithms is made publicly available for usage under the GNU Lesser General Public Licence v.3 or later.

Effects of root–cortex relationship, root shape, and impaction side on treatment duration and root resorption of impacted canines

Summary Objectives This retrospective longitudinal study aimed to evaluate the factors that affect the orthodontic treatment duration (OTD) and external apical root resorption (EARR) of maxillary impacted canines (MIC) as root–cortex relationship, root shape, impaction side, and gender. Material and method Thirty-eight patients (mean age 15.28 ± 1.48 years) who had unilateral MIC and undergone orthodontic treatment were included in this study. Root–cortex relationship, root–cortex intersection amount, root shape, impaction side, height, alpha angle, impaction zone, and length of the MIC were evaluated on cone-beam computed tomography images at the beginning of the treatment. Final assessments were performed on ortopantograms at the end of the treatment as canine angulation and tooth length. The sample was characterized by descriptive statistics; t-tests, Mann–Whitney U-test, ANOVA, and Kruskal–Wallis tests were used for the comparison of EARR and OTD values between the categorical groups. Results Root shape affected OTD, and the longest value was detected in MIC with bent root (P &lt; 0.000). The presence of root–cortex relationship also prolonged OTD for approximately 3 months (P = 0.006). MIC with risk factors like positive root–cortex relationship and bent roots had higher EARR values than those with negative root–cortex relationship and normal roots (P = 0.042, P = 0.021, respectively). EARR of the palatal MIC was also higher than the buccal MIC (P = 0.009). OTD was significantly influenced by root–cortex intersection amount (P = 0.004). Conclusion The presence of root–cortex relationship and abnormal root shape were risk factors for greater EARR of MIC along OTD, which was also significantly influenced by root shape and root–cortex relationship.

Matching Cut in Graphs with Large Minimum Degree

In a graph, a matching cut is an edge cut that is a matching. Matching Cut is the problem of deciding whether or not a given graph has a matching cut, which is known to be $${\mathsf {NP}}$$ NP -complete. While Matching Cut is trivial for graphs with minimum degree at most one, it is $${\mathsf {NP}}$$ NP -complete on graphs with minimum degree two. In this paper, we show that, for any given constant $$c>1$$ c > 1 , Matching Cut is $${\mathsf {NP}}$$ NP -complete in the class of graphs with minimum degree c and this restriction of Matching Cut has no subexponential-time algorithm in the number of vertices unless the Exponential-Time Hypothesis fails. We also show that, for any given constant $$\epsilon >0$$ ϵ > 0 , Matching Cut remains $${\mathsf {NP}}$$ NP -complete in the class of n-vertex (bipartite) graphs with unbounded minimum degree $$\delta >n^{1-\epsilon }$$ δ > n 1 - ϵ . We give an exact branching algorithm to solve Matching Cut for graphs with minimum degree $$\delta \ge 3$$ δ ≥ 3 in $$O^*(\lambda ^n)$$ O ∗ ( λ n ) time, where $$\lambda$$ λ is the positive root of the polynomial $$x^{\delta +1}-x^{\delta }-1$$ x δ + 1 - x δ - 1 . Despite the hardness results, this is a very fast exact exponential-time algorithm for Matching Cut on graphs with large minimum degree; for instance, the running time is $$O^*(1.0099^n)$$ O ∗ ( 1 . 0099 n ) on graphs with minimum degree $$\delta \ge 469$$ δ ≥ 469 . Complementing our hardness results, we show that, for any two fixed constants $$1< c <4$$ 1 < c < 4 and $$c^{\prime }\ge 0$$ c ′ ≥ 0 , Matching Cut is solvable in polynomial time for graphs with large minimum degree $$\delta \ge \frac{1}{c}n-c^{\prime }$$ δ ≥ 1 c n - c ′ .