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While various studies have focused on the significance of computational thinking (CT) for the future career paths of individuals in science, technology, engineering, and mathematics (STEM), few studies have focused on computational thinking for non-STEM college students. This study explores the relationship between computational thinking and learning satisfaction for non-STEM-major college students. A conceptual model is proposed to examine the structural relationships among computational thinking, self-efficacy, self-exploration, enjoyment and learning satisfaction in an AppInventor-based liberal education course. Collecting data from 190 undergraduate students from Taiwan and analyzing the data by using partial least squares (PLS) methods, the research framework confirms the six proposed hypotheses. These results show that both computational thinking and enjoyment play significant roles in both self-exploration and digital self-efficacy. Moreover, digital self-efficacy and self-exploration also have a significant positive influence on learning satisfaction. These findings have implications for influencing the learning outcomes of non-STEM-major college students, computational thinking course instructors, and computational thinking relevant policies.

The utilization of a reverberant shear-wave field in shear-wave elastography has emerged as a promising technique for achieving robust shear-wave speed (SWS) estimation. However, many types of estimators cannot accurately measure SWS within such a complicated 3D wave field. This study introduces an advanced autocorrelation estimator based on angular integration known as the angular integral autocorrelation (AIA) approach to address this issue. The AIA approach incorporates all the autocorrelation data from various angles during measurements, resulting in enhanced robustness to both noise and imperfect distributions in SWS estimation. The effectiveness of the AIA estimator for SWS estimation is first validated using a k-Wave simulation of a stiff branching tube in a uniform background. Furthermore, the AIA estimator is applied to ultrasound elastography experiments, magnetic resonance imaging (MRI) experiments, and optical coherence tomography (OCT) studies across a range of different excitation frequencies on tissues and phantoms, including in vivo scans. The results verify the capacity of the AIA approach to enhance the accuracy of SWS estimation and the signal-to-noise ratio (SNR), even within an imperfect reverberant shear-wave field. Compared to simple autocorrelation approaches, the AIA approach can also successfully visualize and define lesions while significantly improving the estimated SWS and SNR in homogeneous background materials and providing improved elastic contrast between structures within the scans. These findings demonstrate the robustness and effectiveness of the AIA approach across a wide range of applications, including ultrasound elastography, magnetic resonance elastography (MRE), and optical coherence elastography (OCE), for accurately identifying the elastic properties of biological tissues in diverse excitation scenarios. [ABSTRACT FROM AUTHOR]

Background: The timing of behavior and habitat use of nocturnal animals can be influenced by the lunar cycle in nature. The prevalence of artificial light at night (ALAN) has been recognized as a source of environmental pollution. The interaction between ALAN and the lunar cycle on bat behavior is important for understanding anthropogenic effects on bats. We utilized a decade (2012–2022) of acoustic monitoring data collected in North Carolina, United States, to investigate the relationship between bat activity, lunar cycle, and light pollution. We examined whether the amount of lunar illumination affected species-specific nightly activity and whether hourly bat activity patterns varied between nights with different moon phases. We further investigated if the relationship between bat activity and the lunar cycle might be altered by light pollution. Results: We found that seven bat species showed activity variation across nights in relation to the amount of moon illumination when ALAN was absent. In general, bats were less active on full moon nights compared to new moon nights. Light pollution interacted with the bat–lunar relationship in five of the seven species, masking the effect of the lunar cycle. We identified delayed bat activity patterns on nights with a full or waxing moon in seven species, and light pollution altered that pattern in four species. Overall, ALAN was associated with decreased bat activity independent of lunar cycle effects. Conclusions: Our study demonstrated that at a broad spatial scale, ALAN negatively affected many North American temperate bat species and altered their lunar chronobiology. As light pollution is spreading to historically dark areas and habitats, ALAN might couple with other threats, such as the white-nose syndrome or climate change, to cause cascading damage in the environment that depends on ecosystem services such as pest control provided by bats. We argue that further research and conservation actions are needed to mitigate the impact of light pollution. [ABSTRACT FROM AUTHOR]

Background: The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR. Purpose: This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging‐based proton density fat fraction (MRI‐PDFF) for hepatic steatosis assessment. Methods: We investigated early‐stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI‐PDFF; histology fat percentages. Seven individual US parameters were extracted using B‐mode measurement, Burr distribution estimation, attenuation estimation, H‐scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease‐specific imaging (DSI). Results: The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p‐value < 0.05) and outperforms the correlation between MRI‐PDFF and histology (R = 0.89, p‐value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI‐PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color‐highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p‐value < 0.05). Conclusions: We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI‐PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans. [ABSTRACT FROM AUTHOR]

Gas‐phase reactions of mass‐selected ions with neutrals covers a very broad area of fundamental and applied mass spectrometry (MS). Oftentimes, ion‐molecule reactions (IMR) can serve as a viable alternative to collision‐induced dissociation and other ion dissociation techniques when using tandem MS. This review focuses on the literature pertaining applications of IMR since 2013. During the past decade considerable efforts have been made in analytical applications of IMR, including advances in one of the major techniques for characterization of unsaturated fatty acids and lipids, ozone‐induced dissociation, and the development of a new technique for sequencing of large ions, hydrogen atom attachment/abstraction dissociation. Many advances have also been made in identifying gas‐phase chemistry specific to a functional group in organic and biological compounds, which are useful in structure elucidation of analytes and differentiation of isomers/isobars. With "soft" ionization techniques like electrospray ionization having become mainstream for quite some time now, the efforts in the area of metal ion catalysis have firmly moved into exploring chemistry of ligated metal complexes in their "natural" oxidation states allowing to model individual steps of mechanisms in homogeneous catalysis, especially in combination with high‐level DFT calculations. Finally, IMR continue to contribute to the body of knowledge in the area of chemistry of interstellar processes. [ABSTRACT FROM AUTHOR]