Where do people want to become entrepreneurs? Mapping entrepreneurship potential across Great Britain

Promoting entrepreneurial activities is crucial for regions to facilitate innovation and economic development. Yet, becoming an entrepreneur is not aspired by all people, and regions may differ considerably in their entrepreneurship potential. Assessing and providing accurate estimates of the entrepreneurship potential across fine-grained spatial scales is thus crucial to inform regional policymakers, but it still remains a major challenge due to data availability. Here we used the lab data set from the British Broadcasting Corporation (BBC) covering 368,364 individuals and providing high-resolution data about their residences to map the entrepreneurship potential across 9271 postcode sectors in Great Britain. We used a novel mapping approach that relies on a spatial smoothing function based on distance weights to utilize the most fine-grained spatial level available in the data. Our detailed maps show substantial difference in entrepreneurship potential across postcode sectors in Great Britain and within the largest cities: London, Birmingham and Manchester

Trauma and allegory: truthfulness in fact and fiction. Making a private archive productive

Herengracht 401 (H401), until 2019 known as Castrum Peregrini, represents the complex and intriguing history of a hermetic community of artists and scholars in Amsterdam which was formed in the years of the Nazi occupation of The Netherlands, 1940–1945.This article attempts to take stock on what we have learned in these ten years about the history of the place, as an indicator of memory politics. It also reflects on the hermeneutic gap of what we cannot know of H401’s history as we lack experiential knowledge of eyewitnesses. As the author argues below, the site of H401 shows how the ‘hermeneutic gap’ can offer a chance to make an archive, such as in the case of ‘the house on Herengracht 401’, productive and meaningful through the artistic practice of research

Comparison of very affordable immersion pump and heart-lung-machine for post mortem CT angiography in forensic pathology – A case-control study

Full body post mortem CT angiography (PMCTA) in forensic medicine started on a larger scale with relatively expensive roller-pumps for what in essence seems to be a task consisting of pumping mostly homogenous contrast fluids. At considerably lower cost, centrifugal pumps are a technically powerful alternative. We compare a very affordable immersion pump (IP) with a heart lung machine (HLM) for an iodine based vascular contrast agent in a age-sex matched case-control study of 10 each. The IP outperformed the HLM, in part with statistical significance, depending on the aspect or metric that was compared. Concluding, the IP may be preferred as a useful and affordable alternative over a more expensive roller-pump

Detecting missing teeth on PMCT using statistical shape modeling

The identification of teeth in 3D medical images can be a first step for victim identification from scant remains, for comparison of ante- and postmortem images or for other forensic investigations. We evaluate the performance of a tooth detection approach on mandibles with missing parts or pathologies based on statistical shape models. The proposed approach relies on a shape model that has been built from the full lower jaw, including the mandible and teeth. The model is fitted to the target, resulting in a reconstruction, in addition to a label map that indicates the presence or absence of teeth. We evaluate the accuracy of the proposed solution on a dataset consisting of 76 target mandibles, all extracted from CT images and exhibiting various cases of missing teeth or other cases, such as roots, implants, first dentition, and gap closure. We show an accuracy of approximately 90% on the front teeth (including incisors and canines in our study) that decreases for the molars due to high false-positive rates at the wisdom teeth level. Despite the drop in performance, the proposed approach can be used to obtain an estimate of the tooth count without wisdom teeth, tooth identification, reconstruction of the existing teeth to automate measurements taken as part of routine forensic procedures, or prediction of the missing teeth shape. In comparison to other approaches, our solution relies solely on shape information. This means it can be applied to cases obtained from either medical images or 3D scans because it does not depend on the imaging modality intensities. Another novelty is that the proposed solution avoids heuristics for the separation of teeth or for fitting individual tooth models. The solution is therefore not target-specific and can be directly applied to detect missing parts in other target organs using a shape model of the new target

Sperm hunting on optical microscope slides for forensic analysis with deep convolutional networks – a feasibility study

Microscopic sperm detection is an important task in sexual assault cases. In some instances, the samples contain no or only low amounts of semen. Therefore, the biological material is transferred onto a glass slide and needs to be manually scanned using an optical microscope. This work can be very time consuming, especially when no spermatozoa is present. In such a case, the result needs to be validated. In this article we show how convolutional neural networks can perform this task and how they can reduce the scanning time by locating the sperm cells on images taken under the microscope. For this purpose, we trained a VGG19 network and a VGG19 variation with 1942 images, some containing sperm cells and some not

Augmented Reality in Forensics and Forensic Medicine - Current Status and Future Prospects

Forensic investigations require a vast variety of knowledge and expertise of each specialist involved. With the increase in digitization and advanced technical possibilities, the traditional use of a computer with a screen for visualization and a mouse and keyboard for interactions has limitations, especially when visualizing the content in relation to the real world. Augmented reality (AR) can be used in such instances to support investigators in various tasks at the scene as well as later in the investigation process. In this article, we present current applications of AR in forensics and forensic medicine, the technological basics of AR, and the advantages that AR brings for forensic investigations. Furthermore, we will have a brief look at other fields of application and at future developments of AR in forensics

Illustrated argument for CT-scanning a whole car for the forensic investigation of projectile holes, defects, fragments and possible trajectories

Contemporary documentation of a car with bullet defects after a shooting incident can secure the usual tracks and gunshot residue, take photographs, and use trajectory rods and probes. Since the advent of the ”XXL-CT -Scanner” (Fraunhofer Institute, Germany), we have wondered if the advantages of volume scanning CT, already noted for forensic pathology, could be applied to cars. To this end, we damaged a small 3D-printed car model with an electric drill and added CT -dense material with a soldering iron, simulating linearly configured defect morphologies with metal particles. This model was CT -scanned and the resulting data visualized to illustrate how these visualizations can support reconstructive visualization of trajectories. Performing a real XXL-CT scan of a bullet-riddled car requires extensive preparation, transportation, and other logistical measures that are costly and time-consuming. Nonetheless, we suggest that this is a worthwhile research direction to explore

Classification of rib fracture types from postmortem computed tomography images using deep learning

Human or time resources can sometimes fall short in medical image diagnostics, and analyzing images in full detail can be a challenging task. With recent advances in artificial intelligence, an increasing number of systems have been developed to assist clinicians in their work. In this study, the objective was to train a model that can distinguish between various fracture types on different levels of hierarchical taxonomy and detect them on 2D-image representations of volumetric postmortem computed tomography (PMCT) data. We used a deep learning model based on the ResNet50 architecture that was pretrained on ImageNet data, and we used transfer learning to fine-tune it to our specific task. We trained our model to distinguish between “displaced,” “nondisplaced,” “ad latus,” “ad longitudinem cum contractione,” and “ad longitudinem cum distractione” fractures. Radiographs with no fractures were correctly predicted in 95–99% of cases. Nondisplaced fractures were correctly predicted in 80–86% of cases. Displaced fractures of the “ad latus” type were correctly predicted in 17–18% of cases. The other two displaced types of fractures, “ad longitudinem cum contractione” and “ad longitudinem cum distractione,” were correctly predicted in 70–75% and 64–75% of cases, respectively. The model achieved the best performance when the level of hierarchical taxonomy was high, while it had more difficulties when the level of hierarchical taxonomy was lower. Overall, deep learning techniques constitute a reliable solution for forensic pathologists and medical practitioners seeking to reduce workload

3D multimodal teaching of human anatomy and autopsy with real human data

With advances in digitalization, the industrial, education, and research sectors have made use of novel methods to train their staff and students. Simulations and visualizations of real-life situations allow effective and tailored learning strategies. In medicine, the advancement of three-dimensional (3D) surface documentation technologies, particularly close-range photogrammetry, are used to document pathologies or procedural steps in 3D. Subsequently created 3D models enhanced by adding annotations, incision lines, explanations, and animations can be used for educational purposes. In this paper, we describe possible ways to improve or extend actual learning methods in medical teaching and show a concept for possible application. As various teaching tools already exist, we aim to add a teaching approach using 3D visualization. Therefore, a forensic dissection of the neck was documented in 3D, annotated and prepared for teaching using animated videos, 3D PDFs and virtual reality. In the future, the dissection of each body part and organ will be documented using the procedure presented in this paper. The aim of this method is to provide a technique to teach human anatomy and autopsy steps to both medical students and forensic pathologists

Technical note: Semiautomated targeted postmortem computed tomography angiography of the pulmonary arteries using a robotic system

INTRODUCTION To better depict vascular lesions on postmortem computed tomography (PMCT), whole-body postmortem computed tomography angiography (PMCTA) can be used in forensic diagnostics. Targeted angiography, in which only a specific vessel is filled with contrast agent, might help in cases of traumatic changes that render whole-body PMCTA impossible. Moreover, in targeted PMCTA, the contrast agent does not affect the haptics of any other organs. In this article, we describe automated, CT-guided targeted angiography of the pulmonary artery (PA) using the Virtobot system. MATERIAL AND METHODS Our study group consisted of 8 deceased persons (3 males, 5 females). We first performed an unenhanced CT scan and used the data obtained to plan the needle trajectories with the Virtobot planning software. Then, the needle was fully automatically placed by the Virtobot system. Subsequently, 50 ml of contrast agent was injected manually, and the CT scan was repeated (targeted PMCTA). RESULTS AND DISCUSSION We tested a new method for performing semiautomated targeted postmortem angiography of the PAs using a robotic needle placement system (Virtobot). In 6 out of our 8 cases, the injection of contrast agent in the PA was successful. In five of the six successful cases, there was reflux of contrast agent to some extent, but the reflux did not affect the readout. In general, the procedure was easy to plan based on a PMCT data set, and the pulmonary trunk was easy to reach with a robotic needle placement system