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Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization with procedures among personnel is difficult to measure. The US military introduced a chatbot as part of its digital training material to enhance training effectiveness and avoid equipment damage. In this study, the contribution of an artificial intelligence (AI) chatbot in training is explored. To evaluate the necessity of an AI chatbot, research samples were divided into two groups, namely an experimental and a control group, with 20 people in each group. A paired t test was employed for differentiation analysis of pretest and posttest average scores, revealing that the two groups exhibited a statistically significant improvement in their learning performance. In addition, the blend of analysis of variance results indicated significant differences between the two groups. The chatbot training was more effective than traditional instructor teaching in terms of trainee performance improvement.

The current study explores students' collaboration and problem solving (CPS) abilities using a human-to-agent (H-A) computer-based collaborative problem solving assessment. Five CPS assessment units with 76 conversation-based items were constructed using the PISA 2015 CPS framework. In the experiment, 53,855 ninth and tenth graders in Taiwan were recruited, and a multidimensional item response analysis was used to develop CPS scales and represent the students' collaboration and problem solving performance. The results show that the developed H-A approach is feasible for measuring students' CPS skills, and the CPS scales are also shown to be reliable. In addition, the students' CPS performance scores are further explored and discussed under the PISA CPS framework.

A glycan-stimulated and poly(3,4-ethylene-dioxythiophene)s (PEDOT)-based nanomaterial platform is fabricated to purify circulating tumor cells (CTCs) from blood samples of prostate cancer (PCa) patients. This new platform, phenylboronic acid (PBA)-grafted PEDOT NanoVelcro, combines the 3D PEDOT nanosubstrate, which greatly enhances CTC capturing efficiency, with a poly(EDOT-PBA-co-EDOT-EG3) interfacial layer, which not only provides high specificity for CTC capture upon antibody conjugation but also enables competitive binding of sorbitol to gently release the captured cells. CTCs purified by this PEDOT NanoVelcro chip provide well-preserved RNA transcripts for the analysis of the expression level of several PCa-specific RNA biomarkers, which may provide clinical insights into the disease.

The purpose of this study is to explore the validity of the assessment tool. The purposive sampling method is applied in this research on a total of 551 preschool children between 4 and 6 years old. Their ages range from 46 to 81 months, with an average age of 63.9 months (SD = 7.58). The assessment tool used in this research is the "Computerized Visual Motor Integration Assessment Tool Using Chinese Basic Strokes". The multivariate logistic regression analysis was used to automatically determine children's writing classification. The findings suggest that the assessment tool developed has good validity in terms of sensitivity, specificity and the accuracy. This tool is recommended for use in the diagnosis of Chinese visual motor integration issues for preschoolers, so that their potential writing difficulties may be detected early, and the goal of early intervention may be achieved.

In recent years, many studies show that kernel methods are computationally efficient, robust, and stable for pattern analysis. Many kernel-based classifiers were designed and applied to classify remote-sensed data, and some results show that kernel-based classifiers have satisfying performances. Many studies about hyperspectral image classification also show that nonparametric weighted feature extraction (NWFE) is a powerful tool for extracting hyperspectral image features. However, NWFE is still based on linear transformation. In this paper, the kernel method is applied to extend NWFE to kernel-based NWFE (KNWFE). The new KNWFE possesses the advantages of both linear and nonlinear transformation, and the experimental results show that KNWFE outperforms NWFE, decision-boundary feature extraction, independent component analysis, kernel-based principal component analysis, and generalized discriminant analysis. Index Terms--Feature extraction, image classification.

Background and Objective: Tau-specific positron emission topography (PET) imaging enables in vivo assessment of Alzheimer's disease (AD). We aimed to investigate its performance in combination with plasma tau levels in patients with non-AD tauopathy. Methods: A total of 47 participants were enrolled, including 10 healthy controls, 16 with tauopathy parkinsonism syndromes (9 with corticobasal syndrome [CBS], 7 with progressive supranuclear palsy [PSP]), 9 with frontotemporal dementia (FTD), 4 with AD, and 8 with Parkinson's disease (PD). All participants underwent clinical assessments, 18F-T807 tau PET, brain MRI, and plasma tau assay. Results: The global cortical standard uptake value ratio (SUVR) of 18F-T807 PET was comparable between PD and control (p = 0.088). The cortical SUVR was significantly higher in AD group (p = 0.002) but was modestly increased in PSP group compared to the PD group (p = 0.044), especially in parietal and pallidal regions. Asymmetric 18F-T807 uptake at the pallidum was noted in patients with CBS and FTD. Cortical tau tracer uptake was associated with increased plasma total tau level (p = 0.016), especially in frontal and parietal regions. Regional tracer uptake was correlated with cortical thinning in patients with CBS and PSP (CBS: r = −0.092, p = 0.025; PSP: r = −0.114, p = 0.015). Conclusions: The 18F-T807 tau tracer uptake was only modestly increased in patients with PSP. Although the cortical tau tracer uptake correlated with regional cortical atrophy and plasma tau levels, a four-repeated tau-specific tracer is needed for future classifying tauopathy parkinsonism syndromes. [ABSTRACT FROM AUTHOR]