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The threat and destructiveness of landslide disasters caused by extreme rainfall are increasing. Rainfall intensity is a key factor in the mechanism of rainfall-induced landslides. However, under natural conditions, rainfall intensity is highly variable. This study focuses on the Fanling landslide and investigates the effects of varying rainfall intensity amplitudes, rainfall durations, and total rainfall amounts on landslide behavior. Three experimental groups were established, and ten rainfall conditions were simulated numerically to analyze the seepage field response of the landslide under fluctuating rainfall conditions. The results indicate that (1) there are positive correlations between the final pore pressure and both the amplitude and duration of rainfall intensity; (2) the pore water pressure response in the upper slope changes significantly, initiating deformation; and (3) the total rainfall amount is the most direct factor affecting the pore pressure response and landslide deformation. Compared to long-term stable rainfall, short-term fluctuating rainstorms are more likely to trigger landslides. These findings enhance our understanding of landslide mechanisms under fluctuating rainfall, providing valuable insights for disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Herein, an environmentally friendly and efficient amidation method of imines by Oxone and CuO has been developed. This facile method shows excellent selectivity without affecting other functional groups such as phenyls, halogens, cyans, esters or heterocycles. This method features a broad substrate scope, mild conditions and high yields (≤90 %), and the yield in the gram scale experiment also reaches up to 81 %. Flonicamid, moclobemide and bupivacaine are also successfully synthesized to demonstrate its potential utilities. [ABSTRACT FROM AUTHOR]

Stretching the bounds of the client advocacy role beyond what is sound, credible, and/or reasonable may threaten compliance with the AICPA Code of Professional Conduct (Code) (ET 1.140.010.03). Students evaluate real-life requests of a CPA to determine whether the client advocacy role was stretched and violated compliance with the Code. More specifically, students apply the Code's principles, select rules of conduct, and threats to analyze and evaluate a CPA's responses to her client's requests that she provide bankers with financial and other information and reclassify income as debt. Student perceptions and knowledge pretests and post-tests indicate completion of the case increased students' knowledge about the Code and required them to apply analytical and critical thinking skills. In addition, students believe the completion of the case was enjoyable and provided a valuable learning experience. Data Availability: Anonymous data are available upon request. JEL Classifications: M410; M420. [ABSTRACT FROM AUTHOR]

This article presents a novel optimization algorithm to control the ultrasonic vibration of piezo-transducer in microelectronics packaging. The control of resonant frequency tracking to piezo-transducer is significant to the bonding quality. A conventional PID controller is applied to track the resonant frequency of piezo-transducer dynamically; however, there are shortcomings, such as tedious parameter tuning and uncertain optimal parameters. This article proposes the particle swarm optimization (PSO) to search the PID parameters intelligently. The MATLAB-Simulink model of PSO-PID is established to analyze the phase and frequency response of the piezo-transducer by a closed loop, where the optimal control parameters are determined by the PSO search. To solve the conventional abrupt ultrasonic power, an editable voltage trajectory with analytical geometry is proposed to provide various driving voltage trajectories. Finally, the control experiments with the proposed optimization are carried out in ultrasonic wire bonder. The results validate that the PSO-PID and editing trajectory optimizations can attain competitive bonding quality, stability, and robustness. [ABSTRACT FROM AUTHOR]

Intelligent exercise recommendation is a research focus in the field of online learning that can help learners quickly find exercises suitable for them from the exercise bank. However, exercise recommendation differs from product or film recommendation because of some special requirements. First, the recommended exercises must cover all knowledge points geared toward the learning objective of the learner. Second, the difficulty of exercises must match the knowledge level of the target learner. In response to the above requirements, this study proposes an exercise recommendation algorithm that integrates learning objective and assignment feedback. This algorithm considers not only the coverage of knowledge points but also the knowledge level of learners to help them find highly suitable exercises. According to this algorithm, the learning objective of the learner must be initially identified to obtain a course knowledge set that suits his/her learning objective. Second, the understanding of the learner about the knowledge set must be judged based on the assignment feedback. Third, suitable exercises are recommended based on the knowledge level of the learner and the course knowledge structure. The proposed algorithm is experimentally verified by using a real-world dataset and by comparing it with other algorithms. The experimental results show that the proposed algorithm significantly outperforms the other algorithms in both precision and recall. Based on these results, the proposed algorithm can achieve an excellent recommendation performance. [ABSTRACT FROM AUTHOR]

• An exponential and logarithmic form builds the SOC-OCV characteristic curve. • Aggregating cubature and particle filters achieves more stable estimation of SOC. • Noise self-adjustment makes estimator more applicable to practical engineering. In this study, a more precise numerical method to discretize the equation of State-of-Charge is proposed. Unscented particle filter and cubature Kalman filter are performed to estimate State-of-Charge. A hybrid cubature particle filter is presented by aggregating the cubature filter and particle filter to achieve a more stable estimation of State-of-Charge under harsh charging & discharging schedules. Furthermore, the noise self-adjustment strategy is applied to make the proposed estimator more applicable to practical engineering environment. Extensive experiments are conducted on the real data from the Federal Urban Driving Schedule and Dynamic Stress Test, and the results verify that the proposed hybrid method is more robust than the existing models. [ABSTRACT FROM AUTHOR]

The global prevalence of obesity is rising year by year, which has become a public health problem worldwide. Many animal and clinical studies have shown that Lactiplantibacillus plantarum is considered an ideal probiotic and potential supplement for the treatment of obesity. In this study, we aimed to complete the genome sequence of L. plantarum HOM2217, which was isolated from human milk, and study its physiological characteristics and anti-obesity effects in 3T3-L1 cells and rats fed a high-fat diet (HFD) to determine its potential as a starter for functional food products. Whole-genome analysis demonstrated that HOM2217 contained a single circular chromosome of 3,267,529 bp with a GC content of 44.5% and one plasmid (62,350 bp) with a GC content of 38.5%. Compared to the reference strains, HOM2217 demonstrated superior tolerance to gastrointestinal conditions, higher adhesion to intestinal epithelial cell lines, potent antimicrobial activity against Enterobacter cloacae ATCC 13047, and effective cholesterol removal ability in vitro . Treatment with heat-killed HOM2217 significantly reduced lipid accumulation and intracellular triglyceride production in 3T3-L1 adipocytes. Daily treatment of HFD-fed rats with HOM2217 for 7 weeks decreased body weight, body weight gain, and body fat without changes in food intake. HOM2217 also significantly increased the serum high-density lipoprotein cholesterol (HDL-C) level, decreased the serum tumor necrosis factor (TNF-α) and increased short-chain fatty acid (SCFA) (formic acid, acetic acid, and butyric acid) levels in the cecum. Thus, HOM2217 could potentially prevent obesity in rats by inhibiting inflammatory responses and regulating lipid metabolism and SCFAs expression. Therefore, HOM2217 has potential as an alternative treatment for obesity., Competing Interests: TW, XZ, LF, YZ, ZZ, and ZC were employed by Beijing Hanmi Pharmaceutical Co., Ltd. YX, SL, CL, and SZ were employed by Coree Beijing Co., Ltd., (Copyright © 2024 Wang, Zhang, Fan, Zhao, Zhang, Cao, Xu, Lee, Lim and Zhang.)