高校突发事件的特征及其应对策略

高校突发事件具有区别于其他突发事件的特征,如参与对象的特殊性、诱发因素的多样性、事件的迅速扩散性和后果的严重危害性等。当突发事件发生后,高校应当采取以人为本、预防为主、实事求是、统一领导、团结协作、快速平息危机、总结经验教训等应对策略,以切实维护学校和广大师生的利益。     

Comparison of feature selection and data fusion of Fourier transform infrared and Raman spectroscopy for identifying watercolor ink

The identification of different kinds of watercolor inks is an important work in the field of forensic science. Four different kinds of watercolor ink Spectroscopy data fusion strategies (Fourier Transform Infrared spectroscopy and Raman spectroscopy) combined with a non-linear classification model (Extreme Learning Machine) were used to identify the brand of watercolor inks. The study chose Competitive Adaptive Reweighted Sampling (CARS), Random Frog (RF), Variable Combination Population Analysis-Genetic Algorithm (VCPA-GA), and Variable Combination Population Analysis-Iteratively Retains Informative Variables (VCPA-IRIV) to extract characteristic variables for mid-level data fusion. The Cuckoo Search (CS) algorithm is used to optimize the extreme learning machine classification model. The results showed that the classification capacity of the mid-level fusion spectra model was more satisfactory than that of single Infrared spectroscopy or Raman spectroscopy. The CS-ELM models based on infrared spectroscopy used to recognize the watercolor ink according to brands (ZHENCAI, DELI, CHENGUANG, and STAEDTLER) obtained an accuracy of 66.67% in the test set using all spectral datasets. The accuracy of CS-ELM models based on Raman spectroscopy was 67.39%. The characteristic wavelength selection algorithms effectively improved the accuracy of the CS-ELM models. The classification accuracy of the mid-level spectroscopy fusion model combined with the VCPA-IRIV algorithm was 100%. The data fusion method increased effectively spectral information. The method could satisfactorily identify different brands of watercolor inks and support the preservation of artifacts, paintings, and forensic document examination.     

高校哲学课教学创新的思考

哲学是时代精神的精华,马克思主义哲学是科学的世界观和方法论。但是大学的哲学课堂却普遍是死气沉沉,缺乏应有的生机与活力。文章对高校哲学课存在的问题及原因作了深入分析,提出了哲学课教学改革的一些设想。     

文明自信的中国理念及其世界历史意义——论习近平关于文明交流互鉴的理念

当今世界,人类文明发展面临的风险与希望、挑战与愿景正呈现出前所未有的内在张力与外在表现,深刻揭示人类文明的本质及其互动与发展特征,成为当下必须直面的具有根本性、战略性、紧迫性的重大时代课题。党的十八大以来,立足于中国道路实现史诗般崛起的现实成就与文明品质,习近平深刻把握人类文明演进的基本规律,以文明交流互鉴为主题展开一系列重要论述,系统地阐发了“多彩、平等、包容”的文明本质论、“交流、互鉴、共存”的文明关系论和“共商、共建、共享”的文明发展论,从而为在21世纪推动构建人类命运共同体、实现人类历史进步与和平发展,提供了具有世界历史意义的文明自信理念。     

Caregiving and quality of life

ABSTRACT

The increase in life expectancy for adults with learning disabilities has extended the caring role for their parents. This study examined the experiences of older parents who provide long-term care for their adult children with learning disabilities and how they conceptualise their quality of life. Data were collected using semi-structured interviews with 27 older parent carers from four London boroughs and were analysed using framework technique. Findings indicate that most parents appraised their quality of life positively and reported benefits, despite the challenges they had to negotiate daily. The benefits from caregiving, more so in later life, were: a connected family from shared caregiving; a sense of belonging; purposeful living; a reciprocal relationship with their adult children; and personal transformations from providing care that improved their quality of life. The challenges that participants regularly encountered were: multiple losses (sleep, career, identity and friends); the added stress of the government’s Personalisation Agenda of caring services; struggles for access to services; searching for a diagnosis; worry about future care and fear of abuse when carers are unable to continue in their role; unhelpful attitudes of health and social care professionals; and a lack of empathy from friends as well as the public towards people with learning disabilities. Caregiving and quality of life are inextricably linked and the difficulties that parents experienced were mainly associated with socio-structural barriers, rather than their children’s disabilities. Importantly, the findings inform the practice of social workers and others who support this unique group of carers by providing new insights into how caring impacts on quality of life over time and how best these parents’ needs can be met. This study makes a specific contribution to understanding the lived realities of older carers and extends current conceptualisations of caregiving and quality of life among older people.     

Knowledge production on conflict early warning at the African Union

ABSTRACT

How does the African Union (AU) generate knowledge about on-going violent conflict as well as post-conflict situations? This article offers an analysis of the multiple sites and sources in the construction of conflict-related knowledge. It also reflects on the various institutional ways this knowledge is filtered into the activities of a wide range of AU actors, starting with the AU Commission, the AU Commission Chairperson and the Peace and Security Council. Emphasis is on the development of the Continental Early Warning System and some of its limitations, the latter partly related to the specific organisational culture of the African Union.     

Code-switching as a Strategy for the Decolonisation of Learning: A Case of One University in Swaziland

Although the call for the decolonisation of learning and an African renaissance has been a common trend in research recently, less attention has been paid to code-switching as a strategy for decolonising learning at universities. This article explores code-switching as a strategy for decolonising learning at a private university in Swaziland. The article addresses two questions: 1) What are students’ experiences of code-switching during Englishmedium lectures? 2) What are the students’ perceptions of code-switching during Englishmedium lectures? Data were collected using a mixed methods, single case study among a purposive sample of 30 first-year Bachelor of Education in Mathematics students at a private university in Swaziland. The findings indicated that students code switch to solidify pedagogical content presented in English during lectures. The findings also indicated that students employ code-switching as a strategy for breaking linguistic barriers imposed by the English language. Finally, the findings indicated that students describe code-switching as an invaluable strategy for decolonising learning at university. The study contributed in a unique way to knowledge because it is the first of this kind to explore decolonisation at a Swazi university—hence it does not only add to the growing body of literature—but also pioneers scholarship on the decolonisation of learning at Swazi universities. The article concludes by suggesting a student-centred approach to learning that embraces code-switching as a strategy for decolonising learning at the university.     

Automated detection of regions of interest in cartridge case images using deep learning

This paper explores a deep-learning approach to evaluate the position of circular delimiters in cartridge case images. These delimiters define two regions of interest (ROI), corresponding to the breech face and the firing pin impressions, and are placed manually or by an image-processing algorithm. This positioning bears a significant impact on the performance of the image-matching algorithms for firearm identification, and an automated evaluation method would be beneficial to any computerized system. Our contribution consists in optimizing and training U-Net segmentation models from digital images of cartridge cases, intending to locate ROIs automatically. For the experiments, we used high-resolution 2D images from 1195 samples of cartridge cases fired by different 9MM firearms. Our results show that the segmentation models, trained on augmented data sets, exhibit a performance of 95.6% IoU (Intersection over Union) and 99.3% DC (Dice Coefficient) with a loss of 0.014 for the breech face images; and a performance of 95.9% IoU and 99.5% DC with a loss of 0.011 for the firing pin images. We observed that the natural shapes of predicted circles reduce the performance of segmentation models compared with perfect circles on ground truth masks suggesting that our method provide a more accurate segmentation of the real ROI shape. In practice, we believe that these results could be useful for firearms identification. In future work, the predictions may be used to evaluate the quality of delimiters on specimens in a database, or they could determine the region of interest on a cartridge case image.     

Shoeprint image retrieval and crime scene shoeprint image linking by using convolutional neural network and normalized cross correlation

A shoeprint image retrieval process aims to identify and match images of shoeprints found at crime scenes with shoeprint images from a known reference database. It is a challenging problem in the forensic discipline of footwear analysis because a shoeprint found at the crime scene is often imperfect. Recovered shoeprints may be partial, distorted, left on surfaces that do not mark easily, or perhaps come from shoes that do not transfer marks easily. In this study, we present a shoeprint retrieval method by using a convolutional neural network (CNN) and normalized cross-correlation (NCC). A pre-trained CNN was used to extract features from the pre-processed shoeprint images. We then employed NCC to compute a similarity score based on the extracted image features. We achieved a retrieval accuracy of 82% in our experiments, where a “successful” retrieval means that the ground truth image was returned in the top 1% of returned images. We also extend our shoeprint retrieval method to the problem of linking shoeprints recovered from crime scenes. This new method can provide a linkage between two crime scenes if the two recovered shoeprints originated from the same shoe. This new method achieved a retrieval accuracy of 88.99% in the top 20% of returned images.     

Institutional Change Through Policy Learning: The Case of the European Commission and Research Policy

Research initiatives to enhance knowledge‐based societies demand regionally coordinated policy approaches. By analyzing the case of the European Commission, Directorate‐General Research and Innovation, this study focuses on examining the cognitive mechanisms that form the foundation for institutional transformations and result in leadership positions in regional governance. Drawing on policy learning theories, the study emphasizes specific mechanisms of institutional change that are often less noticeable but can gradually lead to mobilizing diverse groups of stakeholders. Through historical and empirical data, this study shows the importance of policy learning through communication processes, Open Method of Coordination initiatives, and issue framing in creating a stronger foundation for policy coordination in European research policy since the 2000s.