Profitability Optimization of Dairy Farms: The Effect of Pregnancy Rate and Culling Decision.

One of the most important decisions in dairy cattle production today is the correct choice of culling time for cows. In the culling decision process, the farmer has to take into account a number of factors, the complexity of which makes the decision-making task difficult. A crucial factor is the evolution of reproductive indicators. The aim of the research was to develop a microsimulation method that can be used to easily investigate the impact on profitability of increasing pregnancy rates and when the culling decision is made. In the microsimulation, the stock was examined without changing any other conditions. A microsimulation method has been developed to determine with high accuracy the effect of the pregnancy rate and the increase in culling days on the economic indicators of individual dairy farms. By microsimulation, the effect of changing these two parameters on the expected milk production of cows, the most important economic indicator for cattle farms, was investigated. The other parameters of economic importance were simulated using a cattle farm database. The purpose of microsimulation is to assist in producing certain managerial decisions in order to achieve better profitability and economic efficiency. In summary, the results showed that increasing the pregnancy rate can successfully reduce the length of the calving interval, but the improved pregnancy rate did not show a significant increase in milk production. In order to obtain results that can be used by farms, the authors intend to further develop the model in the future, adapting it to farms and taking into account their specificities.

Superradiant diamond color center arrays coupled to concave plasmonic nanoresonators.

Superradiantly enhanced emission of SiV diamond color centers was achieved via numerically optimized concave plasmonic nanoresonators. Advantages of different numbers of SiV color centers, diamond-silver (bare) and diamond-silver-diamond (coated) core-shell nanoresonator types, spherical and ellipsoidal geometries were compared. Indistinguishable superradiance is reached via four color centers, which is accompanied by line-width narrowing except in a coated ellipsoidal nanoresonator that outperforms its bare counterpart in superradiance. Seeding of both spherical and bare ellipsoidal nano-resonators with six color centers results in larger fluorescence enhancement and better overridden superradiance thresholds simultaneously. Both phenomena are the best optimized in a six color centers seeded ellipsoidal bare nanoresonator according to the pronounced bad-cavity characteristics.

Improved emission of SiV diamond color centers embedded into concave plasmonic core-shell nanoresonators.

Configuration of three different concave silver core-shell nanoresonators was numerically optimized to enhance the excitation and emission of embedded silicon vacancy (SiV) diamond color centers simultaneously. Conditional optimization was performed to ensure ~20-30-40 and 50% apparent quantum efficiency (cQE) of SiV color centers. The enhancement spectra, as well as the near-field and charge distribution were inspected to uncover the underlying nanophotonical phenomena. The conditionally optimized coupled systems were qualified by the product of the radiative rate enhancements at the excitation and emission, which is nominated as P x factor. The optimized spherical core-shell nanoresonator containing a centralized emitter is capable of enhancing the emission considerably via bonding dipolar resonance. The P x factor is 529-fold with 49.7% cQE at the emission. Decentralization of the emitter leads to appearance of higher order nonradiative multipolar modes. Transversal and longitudinal dipolar resonance of the optimized ellipsoidal core-shell resonator was tuned to the excitation and emission, which results in 6.2∙105 P x factor with 50.6% cQE at the emission. Rod-shaped concave core-shell nanoresonators exploit similar transversal and longitudinal dipolar resonance, moreover they enhance the fluorescence more significantly due to their antenna-like geometry. P x factor indicating 8.34∙105 enhancement is achievable while the cQE is 50.3% at the emission.

Black box optimization benchmarking of the GLOBAL method.

GLOBAL is a multi-start type stochastic method for bound constrained global optimization problems. Its goal is to find the best local minima that are potentially global. For this reason it involves a combination of sampling, clustering, and local search. The role of clustering is to reduce the number of local searches by forming groups of points around the local minimizers from a uniformly sampled domain and to start few local searches in each of those groups. We evaluate the performance of the GLOBAL algorithm on the BBOB 2009 noiseless testbed, containing problems which reflect the typical difficulties arising in real-world applications. The obtained results are also compared with those obtained form the simple multi-start procedure in order to analyze the effects of the applied clustering rule. An improved parameterization is introduced in the GLOBAL method and the performance of the new procedure is compared with the performance of the MATLAB GlobalSearch solver by using the BBOB 2010 test environment.