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Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide, this does not guarantee successful implementation in practice. It is necessary to develop practical approaches that would allow for the translation of the existing guidelines into practice. In this study, we examine an initial set of privacy-preserving mechanisms on a large-scale education dataset. The data utility is evaluated before and after privacy-preserving mechanisms are applied by fitting into commonly used LA models, providing an evaluation of the utility loss. We further explore the balance between preserving data privacy and maintaining data utility in LA. The results prove the compatibility between preserving learners' privacy and LA, providing a benchmark of utility loss to practitioners and researchers in the education sector. Our study reminds an imminent concern of data privacy and advocates that privacy preserving can and should be an integral part of the design of any LA technique.

Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently, algorithmic fairness has gained significant attention. Nevertheless, algorithmic fairness research has paid little attention to dataset drift. Majority of the existing fairness algorithms are "statically" designed. Put another way, LA models tuned to be "fair" on past data are expected to still be "fair" when dealing with current/future data. However, it is counter-intuitive to deploy a statically fair algorithm to a nonstationary world. There is, therefore, a need to assess the impact of dataset drift on the unfairness of LA models. For this reason, we investigate the relationship between dataset drift and unfairness of LA models. Specifically, we first measure the degree of drift in the features (i.e., covariates) and target label of our dataset. After that, we train predictive models on the dataset and evaluate the relationship between the dataset drift and the unfairness of the predictive models. Our findings suggest a directly proportional relationship between dataset drift and unfairness. Further, we find covariate drift to have the most impact on unfairness of models as compared to target drift, and there are no guarantees that a once fair model would consistently remain fair. Our findings imply that "robustness" of fair LA models to dataset drift is necessary before deployment.

Sum frequency generation vibrational spectroscopy (SFG) was applied to characterize the interfacial adhesion chemistry at several buried polymer interfaces in both model systems and blown multilayer films. Anhydride/acid modified polyolefins are used as tie layers to bond dissimilar polymers in multilayer barrier structures. In these films, the interfacial reactions between the barrier polymers, such as ethylene vinyl alcohol (EVOH) or nylon, and the grafted anhydrides/acids provide covalent linkages that enhance adhesion. However, the bonding strengths vary for different polymer–tie layer combinations. Here, using SFG, we aim to provide a systematic study on four common polymer–tie interfaces, including EVOH/polypropylene–tie, EVOH/polyethylene–tie, nylon/polypropylene–tie, and nylon/polyethylene–tie, to understand how the adhesion chemistry varies and its impact on the measured adhesion. Our SFG studies suggest that adhesion enhancement is driven by a combination of reaction kinetics and the interfacial enrichment of the anhydride/acid, resulting in stronger adhesion in the case of nylon. This observation matches well with the higher adhesion observed in the nylon/tie systems in both lap shear and peel test measurements. In addition, in the polypropylene–tie systems, grafted oligomers due to chain scission may migrate to the interface, affecting the adhesion. These by-products can react or interfere with the barrier–tie chemistry, resulting in reduced adhesion strength in the polypropylene–tie system. [ABSTRACT FROM AUTHOR]

Abstracts: Rationale: Diesel engine exhaust (DEE) is associated with the development and exacerbation of asthma. Studies have shown that DEE can aggravate allergen-induced eosinophilic inflammation in lung. However, it remains not clear that whether DEE alone could initiate non-allergic eosinophilic inflammation and airway hyperresponsiveness (AHR) through innate lymphoid cells (ILCs) pathway. Objective: This study aims to investigate the airway inflammation and hyperresponsiveness and its relationship with ILC after DEE exposure. Method: Non-sensitized BALB/c mice were exposed in the chamber of diesel exhaust or filtered air for 2, 4, and 6 weeks (4 h/day, 6 days/week). Anti-CD4 mAb or anti-Thy1.2 mAb was administered by intraperitoneal injection to inhibit CD4+T or ILCs respectively. AHR、airway inflammation and ILCs were assessed. Result: DEE exposure induced significantly elevated level of neutrophils, eosinophils, collagen content at 4, 6 weeks. Importantly, the airway AHR was only significant in the 4weeks-DEE exposure group. No difference of the functional proportions of Th2 cells was found between exposure group and control group. The proportions of IL-5+ILC2, IL-17+ILC significantly increased in 2, 4weeks-DEE exposure group. After depletion of CD4+T cells, both the proportion of IL-5+ILC2 and IL-17A ILCs was higher in the 4weeks-DEE exposure group which induced AHR, neutrophilic and eosinophilic inflammation accompanied by the IL-5, IL-17A levels. Conclusion: Diesel engine exhaust alone can imitate asthmatic characteristics in mice model. Lung-resident ILCs are one of the major effectors cells responsible for a mixed Th2/Th17 response and AHR.

In order to grasp the dynamic characteristics of the gear transmission system of high-speed trains under the torque excitation of the driving end and the load end, the pure torsional vibration model of the gear transmission system of high-speed trains is established. The analytical solution of the system under the torque excitation of the driving end and the load end is obtained by using the incremental harmonic balance method (IHBM). The rationality of IHBM is verified by comparing with the numerical solution of the system. By drawing the frequency response curve of the system, the influence of the change of the main parameters in the torque excitation of the driving end and the load end on the dynamic characteristics of the system is analyzed. The results show that there are several high-order super harmonic resonance regions, amplitude jumps, one or more multi-valued solution regions and other nonlinear characteristics in the system under the parameter changes of the driving end and the load end torque excitation. The research results have a unique reference value for in-depth analysis of the dynamic characteristics of the gear transmission system of high-speed trains under the torque excitation of the driving end and the load end.

Background: Cough hypersensitivity is an important part of the neurophysiology of cough, which presents with increased cough response to a lower level of stimuli or triggers. Classification of stimuli might bring about additional insight into the underlying mechanisms and management. Objectives: This study investigated the profile of cough triggers in chronic cough patients and their relationship with capsaicin cough sensitivity. Design: This was a cross-sectional observational study. Methods: We enrolled patients with different causes of chronic cough from 2006 to 2021. Cough triggers were defined as cough response to chemical triggers, mechanical triggers, meal triggers, or thermal trigger. Cough sensitivity to capsaicin was evaluated by the capsaicin challenge test, which was expressed as the lowest concentration of capsaicin inducing 5 or more coughing (C5). Results: Among 1211 patients with chronic cough, 1107 (91.4%) patients reported at least one cough trigger. Chemical triggers (66.9%) were the most common cough triggers, followed by thermal exposure (50.6%), mechanical triggers (48.2%), and meal triggers (21.2%). There was no difference in the proportion of chemical triggers among different etiologies. Patients with refractory chronic cough reported the highest prevalence of cough triggers (97.1%). A higher number of meal triggers (34.9%) was associated with gastroesophageal reflux-related cough, and meal triggers and mechanical triggers were more common in refractory chronic cough. Among 254 patients who completed capsaicin challenge test, both the number of total triggers and the number of chemical triggers had a significant but mild correlation with capsaicin cough sensitivity. Conclusion: Cough hypersensitivity as reflected by a variety of cough triggers is a common feature in chronic cough patients, but different etiologies present specific profiles of cough triggers, which could not be evaluated comprehensively by capsaicin cough sensitivity.