From ‘Harry Potter’ to ‘Bachelor Boy’ and beyond: Bridging the gap between expectations and reality for first year students

The focus of this paper is two-fold: to present data from a research project which explores the expectations/reality mismatches of first year students who were first in the family to attend university and to outline two different approaches that address the needs of beginning students. Undoubtedly, most new students arriving at university experience varying degrees of ‘culture shock’ when their expectations fail to match the reality they encounter. However, for students from equity backgrounds and those who are the first in family, this mismatch can be immense. Many of the expectations presumed both prior to arrival at university and during the initial stages of study may remain hidden or unexplained. There is now widespread recognition of the need to provide improved preparation and support for students entering the tertiary sector. A key implication for each university must be to establish a ‘community of practice’ that serves to initiate new students into its institutional culture

Estimating the change in asymptotic direction due to secular changes in the geomagnetic field

The concept of geomagnetic optics, as described by the asymptotic directions of approach, is extremely useful in the analysis of cosmic radiation data. However, when changes in cutoff occur as a result of evolution in the geomagnetic field, there are corresponding changes in the asymptotic cones of acceptance. A method is introduced of estimating the change in the asymptotic direction of approach for vertically incident cosmic ray particles from a reference set of directions at a specific epoch by considering the change in the geomagnetic cutoff

Probable detection of solar neutrons by ground-level neutron monitors during STIP interval 16

The third solar neutron event detected by Earth-orbiting spacecraft was observed during STIP Interval XVI. The solar flare beginning at 2356 UT on 24 April l984 produced a variety of emissions including gamma rays and solar neutrons. The neutrons were observed by the SMM satellite and the neutron-decay protons were observed on the ISEE-3 spacecraft. Between 0000 and 0010 UT on 25 April an increase of 0.7 and 1.7 percent was recorded by neutron monitors at Tokyo (Itabashi) and Morioka, Japan. These stations were located about 42 degrees from the sub-solar point, and consequently, these is approximately 1400 grams of atmosphere between the incident neutrons at the top of the atmosphere and their detection on the Earth's surface. Nevertheless, the time coincidence of a small increase in the total counting rate of two independent neutron monitors indicates the presence of solar neutrons with energies greater than 400 MeV at the top of the Earth's atmosphere. The small increases in the counting rate emphasize the difficulty in identifying similar events using historical neutron monitor data

Timescales of spike-train correlation for neural oscillators with common drive

We examine the effect of the phase-resetting curve (PRC) on the transfer of correlated input signals into correlated output spikes in a class of neural models receiving noisy, super-threshold stimulation. We use linear response theory to approximate the spike correlation coefficient in terms of moments of the associated exit time problem, and contrast the results for Type I vs. Type II models and across the different timescales over which spike correlations can be assessed. We find that, on long timescales, Type I oscillators transfer correlations much more efficiently than Type II oscillators. On short timescales this trend reverses, with the relative efficiency switching at a timescale that depends on the mean and standard deviation of input currents. This switch occurs over timescales that could be exploited by downstream circuits

Towards the improvement of methane production in CO2 photoreduction using Bi2WO6/TiO2 heterostructures

Russelite bismuth tungstate (Bi2WO6) has been widely reported for the photocatalytic degradation and mineralization of a myriad of pollutants as well as organic compounds. These materials present perovskite-like structure with hierarchical morphologies, which confers excellent optoelectronic properties as potentials candidates for photocatalytic solar fuels production. Here, we propose the development of Bi2WO6/TiO2 heterojunctions for CO2 photoreduction, as a promising solution to produce fuels, alleviate global warming and tackle fossil fuel shortage. Our results show an improvement of the photocatalytic activity of the heterojunctions compared to the pristine semiconductors. Near Ambient Pressure X-ray Photoelectron Spectroscopy (NAP-XPS) experiments reveals a preferential CO2 adsorption over TiO2. On the other hand, transient absorption spectroscopy measurements show that the charge transfer pathway in Bi2WO6/TiO2 hybrids leads to longer-lived photogenerated carriers in spatially separated redox active sites, which favor the reduction of CO2 into highly electron demanding fuels and chemicals, such as CH4 and C2H6Financial support has been received from the European Research Council (ERC), through HYMAP project (grant agreement No. 648319), under the European Union's Horizon 2020 research and innovation program, as well as from the Marie Sklodowska-Curie grant agreement No. 754382. L.C. acknowledges funding from the project ARMONIA (PID2020–119125RJ-I00) funded by MCIN/AEI/10.13039/ 501100011033. Financial support has also been received from AEIMINECO/FEDER (Nympha Project, PID2019–106315RB-I00), "Comunidad de Madrid" regional government, and the European Structural Funds (FotoArt-CM project, S2018/NMT-4367). Authors also acknowledge financial support from the grant PLEC2021–007906 funded by MCIN/AEI/10.13039/501100011033 and the "European Union NextGenerationEU/PRTR"

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6-91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice

Energy Landscape and Global Optimization for a Frustrated Model Protein

The three-color (BLN) 69-residue model protein was designed to exhibit frustrated folding. We investigate the energy landscape of this protein using disconnectivity graphs and compare it to a Go model, which is designed to reduce the frustration by removing all non-native attractive interactions. Finding the global minimum on a frustrated energy landscape is a good test of global optimization techniques, and we present calculations evaluating the performance of basin-hopping and genetic algorithms for this system.Comparisons are made with the widely studied 46-residue BLN protein.We show that the energy landscape of the 69-residue BLN protein contains several deep funnels, each of which corresponds to a different β-barrel structure

Methodological quality of systematic reviews of animal studies: a survey of reviews of basic research

BACKGROUND: Systematic reviews can serve as a tool in translation of basic life sciences research from laboratory to human research and healthcare. The extent to which reviews of animal research are systematic and unbiased is not known. METHODS: We searched, without language restrictions, Medline, Embase, bibliographies of known reviews (1996–2004) and contacted experts to identify citations of reviews of basic science literature which, as a minimum, performed search of a publicly available resource. From these we identified reviews of animal studies where laboratory variables were measured or where treatments were administered to live animals to examine their effects, and compared them with reviews of bench studies in which human or animal tissues, cell systems or organ preparations were examined in laboratories to better understand mechanisms of diseases. RESULTS: Systematic reviews of animal studies often lacked methodological features such as specification of a testable hypothesis (9/30, 30%); literature search without language restriction (8/30, 26.6%); assessment of publication bias (5/30, 16.6%), study validity (15/30, 50%) and heterogeneity (10/30, 33.3%); and meta-analysis for quantitative synthesis (12/30, 40%). Compared to reviews of bench studies, they were less prone to bias as they specified the question (96.6% vs. 80%, p = 0.04), searched multiple databases (60% vs. 26.6%, p = 0.01), assessed study quality (50% vs. 20%, p = 0.01), and explored heterogeneity (33.3% vs. 2.2%, p = 0.001) more often. CONCLUSION: There seems to be a gradient of frequency of methodological weaknesses among reviews: Attempted systematic reviews of whole animal research tend to be better than those of bench studies, though compared to systematic reviews of human clinical trials they are apparently poorer. There is a need for rigour when reviewing animal research