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Background Hypertension is a common chronic non-communicable disease in clinical practice, and its prevalence is on the rise globally due to population aging and changes in human lifestyles. Prolonged high blood pressure can lead to damage to various target organs such as the heart, brain, kidneys, and retina, severely threatening human health and being a major cause of global disease burden. The left ventricle, as the primary target of end-organ damage, its structural changes are also the pathological basis for the development of many cardiovascular diseases. Objective This study aims to explore the relationship between the atherogenic index of plasma (AIP) and serum lipoprotein-associated phospholipase A2 (Lp-PLA2) levels and left ventricular hypertrophy (LVH) in patients with primary hypertension. Methods A total of 167 patients with primary hypertension who visited the Department of Cardiovascular Medicine at the Second Affiliated Hospital of Zhengzhou University from October 2021 to June 2023 were enrolled in this study. Baseline data of the patients were collected, and fasting venous blood biochemical markers were measured. Echocardiograms were conducted within 24 hours of admission to calculate left ventricular mass (LVM) and left ventricular mass index (LVMI). Patients were divided into non-left ventricular hypertrophy (NLVH) group (87 patients) and LVH group (80 patients) based on LVMI. Pearson correlation test and Spearman rank correlation analysis were used to investigate the correlation between serum Lp-PLA2 level, AIP and echocardiographic parameters. Multivariate Logistic regression analysis was used to explore the influencing factors of LVH in hypertensive patients. Receiver operating characteristic (ROC) curve was plotted to explore the diagnostic value of serum Lp-PLA2 level and AIP in hypertensive patients with LVH, and the area under ROC curve (AUC) was calculated. Results Patients in the LVH group had higher age, duration of hypertension, levels of N-terminal pro B-type natriuretic peptide (NT-proBNP), high-sensitivity C-reactive protein (hs-CRP), left ventricular posterior wall thickness (LVWPT), interventricular septal thickness (IVST), left ventricular end-diastolic diameter (LVEDd), left atrial end-systolic diameter (LAESd), Lp-PLA2 levels, AIP, LVM, and LVMI compared to the NLVH group (P

Background: Auditory-perceptual assessment of voice is a subjective procedure. Artificial intelligence with deep learning (DL) may improve the consistency and accessibility of this task. It is unclear how a DL model performs on different acoustic features. Aims: To develop a generalizable DL framework for identifying dysphonia using a multidimensional acoustic feature. Methods & Procedures: Recordings of sustained phonations of /a/ and /i/ were retrospectively collected from a clinical database. Subjects contained 238 dysphonic and 223 vocally healthy speakers of Chinese Mandarin. All audio clips were split into multiple 1.5-s segments and normalized to the same loudness level. Mel frequency cepstral coefficients and mel-spectrogram were extracted from these standardized segments. Each set of features was used in a convolutional neural network (CNN) to perform a binary classification task. The best feature was obtained through a five-fold cross-validation on a random selection of 80% data. The resultant DL framework was tested on the remaining 20% data and a public German voice database. The performance of the DL framework was compared with those of two baseline machine-learning models. Outcomes & Results: The mel-spectrogram yielded the best model performance, with a mean area under the receiver operating characteristic curve of 0.972 and an accuracy of 92% in classifying audio segments. The resultant DL framework significantly outperformed both baseline models in detecting dysphonic subjects on both test sets. The best outcomes were achieved when classifications were made based on all segments of both vowels, with 95% accuracy, 92% recall, 98% precision and 98% specificity on the Chinese test set, and 92%, 95%, 90% and 89%, respectively, on the German set. Conclusions & Implications: This study demonstrates the feasibility of DL for automatic detection of dysphonia. The mel-spectrogram is a preferred acoustic feature for the task. This framework may be used for vocal health screening and facilitate automatic perceptual evaluation of voice in the era of big data.

Internationally, challenges were raised towards engineering education concerning the industry's widespread questioning of the lack of practical skills of engineering graduates. Scholars in engineering educational research have tried to better understand professional engineers' practices so as to inform engineering education. Concerning the lack of empirical research in China, particularly from practicing engineers' perspectives, this work explored the perceptions of 22 early and mid-career working engineers from multiple industries in a Chinese context via qualitative interviews on the ways in which the knowledge, skills, and attributes that were essential to their project completion were learnt or developed. Our analyses suggested that such development existed mostly in the process of work completion. In particular, the experiences of participating in multiple projects and reflective thinking and discussions on the projects made the engineer progress fast. Based on the findings, suggestions are proposed for engineering educational practices and future research.

Background: Over the past two decades, state policies and industrial associations have challenged engineering educators to expand the training of future engineers beyond technical competencies to the broader domain of professional skills development, with one key aspect being engineering leadership. Purpose: This study adopted the four capabilities (4-Cap) model, which views leadership as a set of four capabilities--sensemaking, relating, visioning, and inventing--as a conceptual framework to explore and operationalize the core skills and attributes required for engineers in a Chinese industrial context. Method: A qualitative study was conducted through semistructured interviews with 23 practicing engineers from different industries (e.g., IT, automobile) and various types of companies (e.g., state-owned companies, foreign-invested enterprises) in China. Using a thematic analysis approach, themes relating to engineering leadership within and beyond the 4-Cap model were reported. Results: Qualitatively, more themes emerged for the dimension of inventing than for the other dimensions. The themes and patterns suggested the central role of inventing, which predominantly represented an innovative process of design-oriented problem-solving and project management closely associated with themes in the other dimensions. Therefore, the 4-Cap model was revisited and revised by highlighting the core construct of inventing. Conclusion: This study enriches the current understanding of engineering leadership, especially in a Chinese industrial context. The results emphasize the importance of design, problem-solving, and the social component in the daily work of engineering professionals. Suggestions for educational practices and future research, along with a call for more empirical data on engineering leadership in China and from a global context, are proposed.