Theory of tunneling spectroscopy of normal metal/ferromagnet/spin-triplet superconductor junctions

We study the tunneling conductance of a ballistic normal metal / ferromagnet / spin-triplet superconductor junction using the extended Blonder-Tinkham-Klapwijk formalism as a model for a $c$-axis oriented Au / SrRuO$_{3}$ / Sr$_{2}$RuO$_{4}$ junction. We compare chiral $p$-wave (CPW) and helical $p$-wave (HPW) pair potentials, combined with ferromagnet magnetization directions parallel and perpendicular to the interface. For fixed $\theta_{M}$, where $\theta_{M}$ is a direction of magnetization in the ferromagnet measured from the $c$-axis, the tunneling conductance of CPW and HPW clearly show different voltage dependencies. It is found that the cases where the $d$-vector is perpendicular to the magnetization direction (CPW with $\theta_{M} = \pi/2$ and HPW with $\theta_{M} = 0$) are identical. The obtained results serve as a guide to determine the pairing symmetry of the spin-triplet superconductor Sr$_{2}$RuO$_{4}$.Comment: 12 pages, 7 figures. There is also a supplementary (not uploaded

Surgical Site Infections at Donor and Recipient Sites in Patients with Iliac Crest Harvesting For Autologous Bone Grafting - A Pilot Evaluation

Surgeons harvest the iliac crest for bone grafting. The epidemiology of surgical site infections (SSI) associated with this procedure at the donor, or recipient site, is unknown. We perform a retrospective pilot evaluation of adult patients undergoing first-time orthopedic surgery at the Balgrist University Hospital between 2014-2019. We excluded patients with infection at the index surgery, diabetic foot surgeries, superficial SSIs, and revision surgeries. We included 20,088 episodes of primary orthopedic surgery, of which 467 with iliac crest bone sampling (467/20,088; 2%). Only two iliac sites (2/467; 0.4%) become infected. In contrast, surgeries with iliac crest sampling yielded more SSIs at the recipient site than those without (1.9% vs. 0.8%; χ2-test; p<0.01). These patients equally revealed more co-morbidities such as a longer duration of surgery (median 127 vs. 79 minutes), when compared to the general orthopedic population. In multivariate logistic regression analysis with the outcome “ SSI at the recipient site”, the iliac harvesting was independently associated with deep SSIs requiring surgical revision (odds ratio 2.1; 95% confidence interval 1.1-4.2). In our pilot evaluation with 20,088 primary orthopedic surgeries, the SSI risk of the iliac harvest site was low. In contrast, surgeries with supplementary iliac crest harvesting revealed a higher SSI risk than the general orthopedic population, potentially due to a mix of local independent risks of grafting together with a prolonged surgery time. Keywords : Autologous bone grafting; Deep surgical site infections; Epidemiology; Iliac crest harvesting; Revision surger

Deep Learning-Based Natural Language Processing in Radiology:The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance

In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and monitoring guideline adherence. Class imbalance, variation in dataset size, variation in report complexity, and algorithm type all influence NLP performance but have not yet been systematically and interrelatedly evaluated. In this study, we investigate these factors on the performance of four types [a fully connected neural network (Dense), a long short-term memory recurrent neural network (LSTM), a convolutional neural network (CNN), and a Bidirectional Encoder Representations from Transformers (BERT)] of deep learning-based NLP. Two datasets consisting of radiologist-annotated reports of both trauma radiographs (n = 2469) and chest radiographs and computer tomography (CT) studies (n = 2255) were split into training sets (80%) and testing sets (20%). The training data was used as a source to train all four model types in 84 experiments (Fracture-data) and 45 experiments (Chest-data) with variation in size and prevalence. The performance was evaluated on sensitivity, specificity, positive predictive value, negative predictive value, area under the curve, and F score. After the NLP of radiology reports, all four model-architectures demonstrated high performance with metrics up to > 0.90. CNN, LSTM, and Dense were outperformed by the BERT algorithm because of its stable results despite variation in training size and prevalence. Awareness of variation in prevalence is warranted because it impacts sensitivity and specificity in opposite directions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10916-021-01761-4

Promises of artificial intelligence in neuroradiology:a systematic technographic review

Purpose To conduct a systematic review of the possibilities of artificial intelligence (AI) in neuroradiology by performing an objective, systematic assessment of available applications. To analyse the potential impacts of AI applications on the work of neuroradiologists. Methods We identified AI applications offered on the market during the period 2017–2019. We systematically collected and structured information in a relational database and coded for the characteristics of the applications, their functionalities for the radiology workflow and their potential impacts in terms of ‘supporting’, ‘extending’ and ‘replacing’ radiology tasks. Results We identified 37 AI applications in the domain of neuroradiology from 27 vendors, together offering 111 functionalities. The majority of functionalities ‘support’ radiologists, especially for the detection and interpretation of image findings. The second-largest group of functionalities ‘extends’ the possibilities of radiologists by providing quantitative information about pathological findings. A small but noticeable portion of functionalities seek to ‘replace’ certain radiology tasks. Conclusion Artificial intelligence in neuroradiology is not only in the stage of development and testing but also available for clinical practice. The majority of functionalities support radiologists or extend their tasks. None of the applications can replace the entire radiology profession, but a few applications can do so for a limited set of tasks. Scientific validation of the AI products is more limited than the regulatory approval

Match-derived relative pitch area changes the physical and team tactical performance of elite soccer players in small-sided soccer games

Small-sided games (SSGs) are used in training sessions to prepare for full-sized matches. For the same number of players, smaller pitch sizes result in decreased physical performance and shorter interpersonal distances. A relative pitch area derived from the full-sized match results in larger pitch sizes and this may increase the fit between SSGs and full-sized matches. This study aimed to investigate SSGs with a traditional small pitch and a match-derived relative pitch area in youth elite soccer players. Four age categories (under-13, under-15, under-17 and under-19) played 4 vs. 4 plus goalkeepers on a small (40x30m, 120m(2) relative pitch area) and large pitch (68x47m, 320m(2) relative pitch area). The number of games per age category ranged 15-30. Positional data (LPM-system) were collected to determine physical (total distance covered, high intensity distance and number of sprints) and team tactical (inter-team distance, LPW-ratio, surface area, stretch indices, goalkeeper-defender distance) performance measures and tactical variability. On a large pitch, physical performance significantly increased, inter-team and intra-team distances were significantly larger and tactical variability of intra-team distance measures significantly increased. The match-derived relative pitch area is an important training manipulation and leads to changes in physical and tactical performance 4 vs. 4 plus goalkeepers.</p