An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the existing methods were designed to detect drifts in individual items, which may not be adequate for test characteristic curve–based linking or equating. One example is the item response theory–based true score equating, whose goal is to generate a conversion table to relate number‐correct scores on two forms based on their test characteristic curves. This article introduces a stepwise test characteristic curve method to detect item parameter drift iteratively based on test characteristic curves without needing to set any predetermined critical values. Comparisons are made between the proposed method and two existing methods under the three‐parameter logistic item response model through simulation and real data analysis. Results show that the proposed method produces a small difference in test characteristic curves between administrations, an accurate conversion table, and a good classification of drifted and nondrifted items and at the same time keeps a large amount of linking items.

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Acoustic emission is a nondestructive testing technology based on the propagation of transient elastic waves captured by acoustic emission sensors. The acoustic emission signal depends not only on the distance and quality of the propagation path of the transient elastic wave but also on the sensitivity and frequency bandwidth of the receiving sensor that converts the transient elastic wave into a voltage signal. The frequency range of damage signals in concrete materials is generally in the low-frequency band. If high-frequency sensors are used, the low sensitivity to low-frequency signals will cause measurement errors, while the bandwidth of general commercial acoustic emission sensors is relatively narrow. Therefore, a high-sensitivity, low-frequency acoustic emission sensor is proposed, whose bandwidth is almost four times that of commercial sensors. Based on the customized sensor, we quantitatively analyzed the influence of propagation distance on the characteristic parameters of acoustic waves propagating in concrete. The results show that the different propagation modes of acoustic waves in concrete have different attenuation with the propagation distance, related to the position relationship between the acoustic source and the sensor and the propagation path and path quality. This result gives us a better understanding of the propagation mechanism of acoustic emission signals in concrete materials.

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Hearing is one of the most important senses needed for survival, and its loss is an independent risk factor for dementia. Hearing loss (HL) can lead to communication difficulties, social isolation, and cognitive dysfunction. The hippocampus is a critical brain region being greatly involved in the formation of learning and memory and is critical not only for declarative memory but also for social memory. However, until today, whether HL can affect learning and memory is poorly understood. This study aimed to identify the relationship between HL and hippocampal-associated cognitive function. Mice with complete auditory input elimination before the onset of hearing were used as the animal model. They were first examined via auditory brainstem response (ABR) to confirm hearing elimination, and behavior estimations were applied to detect social memory capacity. We found significant impairment of social memory in mice with HL compared with the controls (p < 0.05); however, no significant differences were seen in the tests of novel object recognition, Morris water maze (MWM), and locomotion in the open field (p > 0.05). Therefore, our study firstly demonstrates that hearing input is required for the formation of social memory, and hearing stimuli play an important role in the development of normal cognitive ability.