The genetic potentials of rice cultivars will need to be expressed to their fullest if global rice production is to be expanded enough by 2050 to meet the increased demand of expanding population while the availability of land and water per capita dwindles. New and ‘improved’ rice varieties have contributed greatly to increased production over the past 50 years, but the rate of rice yield increase based on genetic changes has declined in recent decades compared with the early years of the Green Revolution. In fact, many rice consumers continue to prefer to consume ‘traditional’ rice varieties (referred to also as local, native, unimproved, or indigenous) because of their taste, aroma, texture, and other qualities. Further, many farmers prefer to cultivate these varieties because of their better adaptation to local climatic and soil conditions and their evolved resistance to endemic stresses. The practices that comprise the System of Rice Intensification (SRI), including transplanting rice seedlings at a young age, wide spacing between plants, keeping the soil well-aerated rather than inundated, and enhancing soil organic matter, provide traditional rice varieties with micro-environments that are more favorable for the expression of their genetic and agronomic potentials. Interactions among rice plants, soil characteristics, water, energy, and other inputs improve the phenotypic and physiological performance of rice plants. This paper considers how the cultivation of traditional rice varieties with SRI methods can raise yields, reduce farmers’ costs of production, and generate higher incomes, while contributing to the conservation of rice biodiversity.

In this paper, we introduce a compressible formulation for dealing with 2D/3D compressible interfacial flows. The formulation is combined with an original monolithic solver, according to which a strong velocity-pressure coupling is achieved. The results show that the scheme can ensure accuracy and stability for various fluid flow scenarios: from the standard incompressible conditions to compressible flows, spanning both single-phase and two-phase flows.

The role of postmastectomy radiotherapy and regional nodal irradiation after radical mastectomy is defined in high-risk patients with locally advanced tumors, positive margins, and unfavorable biology. The benefit of postmastectomy radiotherapy in intermediate-risk patients (T3N0 tumors) remains a matter of controversy. It has been demonstrated that radiotherapy after breast-conserving surgery lowers the locoregional recurrence rate compared with surgery alone and improves the overall survival rate. In patients with 4 or more positive lymph nodes or extracapsular extension regional lymph node irradiation is indicated regardless of the surgery type (breast-conserving surgery or mastectomy). Despite the consensus that patients with more than 3 positive lymph nodes should be treated with radiotherapy, there is a controversy regarding the recommendations for patients with one to three involved lymph nodes. In patients with N0 disease with negative findings on axillary surgery, there is a trend to administer regional lymph node irradiation in patients with a high risk of recurrence. In patients treated with neoadjuvant systemic therapy and mastectomy, adjuvant radiotherapy should be administered in case of clinical stage III and/or ≥ypN1. In patients treated with neoadjuvant systemic therapy and breast-conserving surgery, postoperative radiotherapy is indicated irrespective of pathological response.

In this review we collect some recent achievements in the accurate and efficient solution of the Nonlinear Schrödinger Equation (NLSE), with the preservation of its Hamiltonian structure. This is achieved by using the energy-conserving Runge-Kutta methods named Hamiltonian Boundary Value Methods (HBVMs) after a proper space semi-discretization. The main facts about HBVMs, along with their application for solving the given problem, are here recalled and explained in detail. In particular, their use as spectral methods in time, which allows efficiently solving the problems with spectral space-time accuracy.