Perceptions of interconnected sustainability : Students’ narratives bridging transition and education

As sustainability becomes a focal point and important aspect of educational development in several disciplines and universities globally, it is important to critically reflect on the different utilisations of sustainability education. Research on educational aims and the potential transformative impact of sustainability courses is quite timely. Among several others, the theory of interconnected learning has been gaining traction as an approach to transformative sustainability education, as it employs a distinct approach to systemic sustainability awareness. This approach aims to further express the plurality of sustainability, with the aim to foster a deeper comprehension beyond the dichotomous thinking often typical in disciplined science. The aim of our research was to study the efficiency of employing the pedagogy of interconnected learning on the types of sustainability transition narratives produced by the students attending an online sustainability course. The sustainability transition narratives, as expressed through fifty-eight students’ course assignments, were studied pre- and post-course, and analysed against a collection of established narratives drawn from transition studies. The comparison from the pre-to post-course answers revealed that while some of the student narratives remained unchanged, the majority of the narratives were expanded during the course experience. Our analysis revealed that while most of the students’ answers referenced a single type of transition narrative, some students produced narratives that hybridised two or more types of narratives. Additionally, some of the students produced elements of a pathway for a transition narrative that are currently unarticulated in the transition narrative framework employed herein. The elements of this newly articulated narrative focused on changes in the societal mindset, achievable through sustainability education.Peer reviewe

Borrelia burgdorferi specific serum and cerebrospinal fluid antibodies in Lyme neuroborreliosis

Publisher Copyright: © 2022 The Author(s)We used definite Lyme neuroborreliosis (LNB) adult patient acute and convalescent phase serum (n = 63 and 61, respectively) and cerebrospinal fluid (CSF; acute n = 63, 3 weeks timepoint n = 41) samples to characterize Borrelia burgdorferi specific antibody responses in patient subgroups categorized by demographics, infection manifestation and phase, infecting B. burgdorferi genospecies, received antibiotic treatments, and treatment outcome. B. burgdorferi antibodies were analyzed using 4 different assays incorporating a large array of antigens. We observed that B. burgdorferi specific serum antibodies show a universal, antigen independent declining trend after antibiotic treatment of LNB at 1 year. Antibodies declined similarly among women and men over time, and the decline was independent of patient age. The antibody responses were independent of the predominant LNB manifestation, treatment received by the patient, infecting B. burgdorferi genospecies, or the subjective improvement experienced by the patients. Finally, the antibody specificities in CSF reflected the specificities observed in serum samples.Peer reviewe

An efficient face recognition system using local binary pattern.

Facial recognition is a critical and prominent aspect of current research into image processing and computer vision, with particular applications including confront location, confront acknowledgement and outward appearance investigation. A basic advancement towards fruitful facial picture examination is to infer a viable facial portrayal from the first face pictures. Local Binary Patterns (LBP) have recently gained increased attention as an approach for facial depiction. Neighborhood double example (LBP) is a nonparametric descriptor, which proficiently abridges the nearby structures of pictures. In this paper, there will be a complete overview of LBP and an explanation of extentions of that concept. LBP-based facial picture examination is broadly evaluated, while its fruitful expansions (which manage different aspects of facial picture investigation) are additionally featured

Moving Object Tracking using Color Feature in a Video

Video processing is one of the most challenging areas in image processing. It deals with identifying an object of interest. Motion detection has been used in many fields either directly or indirectly. In this paper an efficient approach to motion detection in video sequence using color feature extraction operator. Using this approach we improve the background subtraction and detecting the moving object with greater accuracy. In this paper, background modeling is done in order to make the update of background due to light illumination and change in the weather condition. Foreground detection is done before updating the background model. Color feature extraction is done in order to avoid the dynamic background such as moving leaves, rain, snow, rippling water