49 research outputs found
The Library Treasure Hunt: Reach for the Stars. Introducing First Year Students to the Landscape of Scientific Information
One important task for the librarians at Physics and Astronomy Library at Lund University is to teach the students about the library and its resources. The traditional lectures and tours of the library just weren’t working. The library competes with many other introductory activities, such as general orientation, and social events. The aim of the Treasure Hunt is to present the library in a useful and amusing way for new students at the start of their studies. Divided into small groups, the students carry out various tasks at stations in the participating libraries. The hunt takes about two hours and a treasure (a goody bag) waits for them at the end. The evaluations show that the treasure hunt is highly appreciated by the students. They become familiar with the librarians and get to know essential aspects of the library resources. The treasure hunt is important in the students’ later studies as it paves the way for further development of their information retrieval skills. A crucial factor to success of the Treasure Hunt is the cooperation of committed teachers. A challenge for the future is to have the Treasure Hunt integrated in all courses as a compulsory element
Characterization and modeling of acousto-optic signal strengths in highly scattering media
Ultrasound optical tomography (UOT) is an imaging technique based on the acousto-optic effect that can perform optical imaging with ultrasound resolution inside turbid media, and is thus interesting for biomedical applications, e.g. for assessing tissue blood oxygenation. In this paper, we present near background free measurements of UOT signal strengths using slow light filter signal detection. We carefully analyze each part of our experimental setup and match measured signal strengths with calculations based on diffusion theory. This agreement between experiment and theory allows us to assert the deep tissue imaging potential of ∼5 cm for UOT of real human tissues predicted by previous theoretical studies [Biomed. Opt. Express 8, 4523 (2017)] with greater confidence, and indicate that future theoretical analysis of optimized UOT systems can be expected to be reliable
Radiative transition probabilities of ions with emphasis on isoelectronic regularities
[abstract missing
System för kvalitetssäkring av allmän ingenjörskompetens inom civilingenjörsutbildningen i Ekosystemteknik vid Lunds Tekniska Högskola
The jerk and the vertical fall of a shuttlecock
Jerk, the derivative of acceleration with respect to time, is a physical concept of great practical significance. However, this concept is rarely mentioned in textbooks and is often neglected in physics education. This paper describes how the concept of jerk can be easily introduced in the study of the dynamics of falling bodies, which are significantly affected by air resistance. In this regard, the vertical fall of two different feather shuttlecocks, a standard and a miniature one, is studied. In this simple vertical fall experiment, air resistance is significant and measurable, implying that the acceleration changes, and thus, the jerk can be determined. The velocity, acceleration, and jerk measurements with time during the vertical fall are described and compared with those from different standard air resistance models. The proposed setup can help initiate a discussion of well-known basic physics concepts and modeling approaches, such as displacement, velocity, acceleration, and particularly the often-neglected jerk concept
Distinguishing tumor from healthy tissue in human liver ex vivo using machine learning and multivariate analysis of diffuse reflectance spectra
The aim of this work was to evaluate the capability of diffuse reflectance spectroscopy to distinguish malignant liver tissues from surrounding tissues, and to determine whether an extended wavelength range (450–1550 nm) offers any advantages over using the conventional wavelength range. Furthermore, multivariate analysis combined with a machine learning algorithm, either linear discriminant analysis or the more advanced support vector machine, was used to discriminate between and classify freshly excised human liver specimens from 18 patients. Tumors were distinguished from surrounding liver tissues with a sensitivity of 99%, specificity of 100%, classification rate of 100%, and a Matthews correlation coefficient of 100% using the extended wavelength range and a combination of principal component analysis and support vector techniques. The results indicate that this technology may be useful in clinical applications for real-time tissue diagnostics of tumor margins where rapid classification is important