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Background With the aging and life expectancy increasing in China, sleep disorders in the elderly (≥80 years old) have received widespread attention. As one of the common problems, sleep disorders seriously affect the quality of life and physical and mental health among the elderly, and can also aggravate or induce multiple diseases. Objective To conduct a scoping review of studies on sleep disorders in community dwelling older adults over 80 years and provide guidance for the early diagnosis and treatment of sleep disorders in community dwelling older adults in China. Methods PubMed, Embase, CINAHL, Web of Science, Cochrane Library, OpenGrey, SinoMed, CNKI, Wanfang Data, and VIP databases were searched for literature on sleep disorders in community dwelling older adults from inception to March 15, 2023. Literature was independently screened by 2 investigators and basic characteristics of the literature were extracted (authors, time of publication, country, type of study, sample size, assessment tool or modality, prevalence, findings) . Results A total of 10 486 papers were searched, and 21 papers were finally included, of which 14 were in English and 7 were in Chinese, 16 were cross-sectional studies, 2 were quasi-experiment studies and 3 were longitudinal studies. The results of the analysis indicated that sleep disorders were more prevalent with serious adverse effects in the community dwelling older adults aged over 80 years (the prevalence rate ranged from 10.0% to 60.3%), which were assessed by nine tools or modalities, including three structured scales with the more commonly used scale being Pittsburgh Sleep Quality Index (PSQI). The influencing factors of sleep disorders were divided into three categories of social demographic factors, physical health and disease-related factors, psychological and behavioral characteristic factors. Interventions such as music therapy, therapy combined with interaction mode groups were found to be effective in improving sleep disorders. However, few prevention and intervention studies were conducted. Conclusion The high prevalence of sleep disorders among older people in the community is high with serious effects, there is insufficient knowledge about sleep disorders among community dwelling older adults and fewer types of assessment tools lacking specificity in China. The influencing factors of sleep disorders among older people are complex and diverse, with a lack of research on prevention and intervention.

There is an academic acceptance that doctoral studies are a complex, multifaceted endeavour bound with the differing, emerging and contrasting identities of the students who undertake them. This article explores such journeys in the context of one of the most disruptive events to hit the higher educational sector worldwide: COVID-19. The study utilises data collected via an online forum established to collectively explore the challenges, the opportunities and the tensions in the lives of 12 students enrolled in a doctoral degree in an Australian higher education institution. Results indicate that the journey of such students pre-COVID-19 was characterised by a sense of liminality, agency and journey. COVID-19 exacerbated such feelings. The conclusion points to a need to enhance spaces of agency in the graduate research experience to reflect the multidimensionality of students' lives.

The security protection of power system is still the focus of power enterprises. In order to solve the problem of untimely and inaccurate secret-related detection of the existing power monitoring system, cloud computing access control technology was used to improve the detection accuracy and efficiency. Firstly, a hierarchical architecture of the power monitoring system was built; with the focus on the control center of the system application layer, the data module and service module in the business layer were regularly scanned, and the system access control and database detection sub modules were connected. Finally, the security model of cloud computing access control was constructed in the sub module, and the self-test process of database secret-related sensitive data was designed to realize the system user access control and confidential and sensitive data self-test. The results show that the average accuracy of the designed secret-related self inspection model is more than 90%, and its response time is less than 7 s, which is better than the comparison model. With the support of the designed model, the power monitoring system can quickly complete the system secret-related detection and response, prevent users from accessing and ensure the security of the system.

Computer-based testing (CBT), which refers to delivering assessments with computers, has been widely used in large English proficiency tests worldwide. Despite an increasing CBT in China, limited research is available concerning whether CBT can be used for the Test for English Majors-Band 4 (TEM 4). The current study investigated whether testing mode impacted TEM 4 score and factors (i.e., computer familiarity level and attitude towards CBT) that might correlate with performance on CBT of TEM 4. Overall 92 Chinese undergraduate students were randomly assigned to one of the groups, i.e., CBT or paper-based testing (PBT), and took the test. A mixed method was employed, including (1) quantitative and qualitative analysis of test performance in two modes, as well as CBT group participants' computer familiarity and attitudes towards the mode; and (2) thematic analysis of semi-structured interviews. The results revealed that (1) test scores in CBT and PBT were comparable; (2) two items in the computer familiarity questionnaire, i.e., comfort level of reading articles on the computer and forgetting time when using computers, positively correlated with CBT scores; and (3) participants' attitude towards CBT did not impact test performance.

Background/Objectives: Degenerative joint disease (DJD) of the TMJ can impact patients' quality of life and complicate orthodontic treatment. Stabilizing splints are a common conservative treatment in managing TMDs symptoms, although their long-term effects on condylar morphology are poorly studied. This study aimed to assess the impact of stabilizing splints on condyle morphology using cone-beam computed tomography (CBCT) in patients with various stages of DJD. Forty-two condyles with pre- (T1) and post- (T2) splint therapy scans were analyzed. Methods: CBCT scans were sectioned into sagittal and coronal slices for condyle classification and measurement. T1 and T2 CBCTs were superimposed before linear and area measurements at different poles. Results: Our results indicate that condyles in the normal group remain unchanged after splint therapy. The majority of subjects in the degenerative groups remained in the same classification group: six out of fourteen degenerative-active patients became degenerative-repair, while three out of twenty-two degenerative-repair patients progressed to degenerative-active. There is no significant remodeling of condylar width pre- and post-splint therapy. On average, there is more bone deposition than reduction in condylar height after splint therapy, although individual variation exists. Conclusions: Stabilizing splints offer a low-risk intervention for managing DJD and may contribute to favorable adaptive changes in the condyles. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the potential of whole-body dynamic (WBD) 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) multiparametric imaging in the differential diagnosis between benign and malignant lung lesions. Procedures: We retrospectively analyzed WBD PET/CT scans from patients with lung lesions performed between April 2020 and March 2023. Multiparametric images including standardized uptake value (SUV), metabolic rate (MRFDG) and distribution volume (DVFDG) were visually interpreted and compared. We adopted SUVmax, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) for semi-quantitative analysis, MRmax and DVmax values for quantitative analysis. We also collected the patients' clinical characteristics. The variables above with P-value < 0.05 in the univariate analysis were entered into a multivariate logistic regression. The statistically significant metrics were plotted on receiver-operating characteristic (ROC) curves. Results: A total of 60 patients were included for data evaluation. We found that most malignant lesions showed high uptake on MRFDG and SUV images, and low or absent uptake on DVFDG images, while benign lesions showed low uptake on MRFDG images and high uptake on DVFDG images. Most malignant lesions showed a characteristic pattern of gradually increasing FDG uptake, whereas benign lesions presented an initial rise with rapid fall, then kept stable at a low level. The AUC values of MRmax and SUVmax are 0.874 (95% CI: 0.763–0.946) and 0.792 (95% CI: 0.667–0.886), respectively. DeLong's test showed the difference between the areas is statistically significant (P < 0.001). Conclusions: Our study demonstrated that dynamic [18F]FDG PET/CT imaging based on the Patlak analysis was a more accurate method of distinguishing malignancies from benign lesions than conventional static PET/CT scans. [ABSTRACT FROM AUTHOR]

In order to achieve impact load localization of complex structures such as ships, this paper proposes a multi-scale feature fusion convolutional neural network (MSFF-CNN) method for impact load localization. An end-to-end machine learning model is used, where the raw vibration signals of impact loads are directly fed into the network model to avoid the process of feature extraction. Automatic feature learning and feature concatenation of the signal are achieved through four independent convolutional layers, each using a different size of convolutional kernel. Data normalization and L2 regularization techniques are introduced to enhance the data and prevent overfitting. Classification and localization of impact loads are accomplished using a softmax classification layer. Validation experiments are carried out using a ship's stern compartment model. Our results show that the classification and localization accuracy of the impact load sample group of MSFF-CNN reaches 94.29% compared with a traditional CNN. The method further improves the ability of the network to extract state features, takes local perception and global vision into account, effectively improves the classification ability of the model, and has good prospects for engineering applications. [ABSTRACT FROM AUTHOR]