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Disease severity in plant pathology is often measured by the amount of a plant or plant part that exhibits disease symptoms. This is typically assessed using a numerical scale, which allows a standardized, convenient, and quick method of rating. These scales, known as quantitative ordinal scales (QOS), divide the percentage scale into a predetermined number of intervals. There are various ways to analyze these ordinal data, with traditional methods involving the use of midpoint conversion to represent the interval. However, this may not be precise enough, as it is only an estimate of the true value. In this case, the data may be considered interval-censored, meaning that we have some knowledge of the value but not an exact measurement. This type of uncertainty is known as censoring, and techniques that address censoring, such as survival analysis (SA), use all available information and account for this uncertainty. To investigate the pros and cons of using SA with QOS measurements, we conducted a simulation based on three pathosystems. The results showed that SA almost always outperformed midpoint conversion with data analyzed using at test, particularly when data were not normally distributed. Midpoint conversion is currently a standard procedure. In certain cases, the midpoint approach required a 400% increase in sample size to achieve the same power as the SA method. However, as the mean severity increases, fewer additional samples are needed (approximately an additional 100%), regardless of the assessment method used. Based on these findings, we conclude that SA is a valuable method for enhancing the power of hypothesis testing when analyzing QOS severity data. Future research should investigate the wider use of survival analysis techniques in plant pathology and their potential applications in the discipline. [ABSTRACT FROM AUTHOR]

The nonlinear Schrödinger equation possesses doubly periodic solutions expressible in terms of the Jacobi elliptic functions. Such solutions can be realized through doubly periodic patterns observed in experiments in fluid mechanics and optics. Stability and robustness of these doubly periodic wave profiles in the focusing regime are studied computationally by using two approaches. First, linear stability is considered by Floquet theory. Growth will occur if the eigenvalues of the monodromy matrix are of a modulus larger than unity. This is verified by numerical simulations with input patterns of different periods. Initial patterns associated with larger eigenvalues will disintegrate faster due to instability. Second, formation of these doubly periodic patterns from a tranquil background is scrutinized. Doubly periodic profiles are generated by perturbing a continuous wave with one Fourier mode, with or without the additional presence of random noise. Effects of varying phase difference, perturbation amplitude, and randomness are studied. Varying the phase angle has a dramatic influence. Periodic patterns will only emerge if the perturbation amplitude is not too weak. The growth of higher-order harmonics, as well as the formation of breathers and repeating patterns, serve as a manifestation of the classical problem of Fermi–Pasta–Ulam–Tsingou recurrence. [ABSTRACT FROM AUTHOR]

Describes a polarimetric ultrasonic sensor consisting of a polarization-maintaining fiber carrying light from a laser. Application to the characterization of high-frequency ultrasonic fields; Detection of ultrasonically induced birefringence in the fiber; Advantage of using a polarization-maintaining fiber instead of a single-mode fiber.