Introduction: looking beyond the walls

In its consideration of the remarkable extent and variety of non-university researchers, this book takes a broader view of ‘knowledge’ and ‘research’ than in the many hot debates about today’s knowledge society, ‘learning age’, or organisation of research. It goes beyond the commonly held image of ‘knowledge’ as something produced and owned by the full-time experts to take a look at those engaged in active knowledge building outside the university walls

Synthesizing Coupled 3D Face Modalities by Trunk-Branch Generative Adversarial Networks

Generating realistic 3D faces is of high importance for computer graphics and computer vision applications. Generally, research on 3D face generation revolves around linear statistical models of the facial surface. Nevertheless, these models cannot represent faithfully either the facial texture or the normals of the face, which are very crucial for photo-realistic face synthesis. Recently, it was demonstrated that Generative Adversarial Networks (GANs) can be used for generating high-quality textures of faces. Nevertheless, the generation process either omits the geometry and normals, or independent processes are used to produce 3D shape information. In this paper, we present the first methodology that generates high-quality texture, shape, and normals jointly, which can be used for photo-realistic synthesis. To do so, we propose a novel GAN that can generate data from different modalities while exploiting their correlations. Furthermore, we demonstrate how we can condition the generation on the expression and create faces with various facial expressions. The qualitative results shown in this paper are compressed due to size limitations, full-resolution results and the accompanying video can be found in the supplementary documents. The code and models are available at the project page: https://github.com/barisgecer/TBGAN.Comment: Check project page: https://github.com/barisgecer/TBGAN for the full resolution results and the accompanying vide

Predicting Geographic Ranges of Marine Animal Populations Using Stable Isotopes: A Case Study of Great Hammerhead Sharks in Eastern Australia

© Copyright © 2020 Raoult, Trueman, Kingsbury, Gillanders, Broadhurst, Williamson, Nagelkerken, Booth, Peddemors, Couturier and Gaston. Determining the geographic range of widely dispersed or migratory marine organisms is notoriously difficult, often requiring considerable costs and typically extensive tagging or exploration programs. While these approaches are accurate and can reveal important information on the species, they are usually conducted on only a small number of individuals and can take years to produce relevant results, so alternative approaches may be preferable. The presence of latitudinal gradients in stable carbon isotope compositions of marine phytoplankton offers a means to quickly determine likely geographic population ranges of species that rely on productivity from these resources. Across sufficiently large spatial and temporal scales, the stable carbon isotopes of large coastal or pelagic marine species should reflect broad geographic patterns of resource use, and could be used to infer geographic ranges of marine populations. Using two methods, one based on a global mechanistic model and the other on targeted low-cost latitudinal sampling of fishes, we demonstrate and compare these stable isotope approaches to determine the core population geography of an apex predator, the great hammerhead (Sphyrna mokarran). Both methods indicated similar geographic ranges and suggested that S. mokarran recorded in south-eastern Australia are likely to be from more northern Australian waters. These approaches could be replicated in other areas where coastlines span predictable geographic gradients in isotope values and be used to determine the core population geography of highly mobile species to inform management decisions

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification

Surveillance of Airborne Adenovirus and Mycoplasma pneumoniae in a Hospital Pediatric Department

This investigation evaluated the distributions of airborne adenovirus and Mycoplasma pneumoniae in public areas in the pediatric department of Children's Hospital in northern Taiwan. The airborne viral and bacterial concentrations were evaluated twice a week for a year using filter sampling with an airflow rate of 12 liters per minute for eight hours in the pediatric outpatient department and 24 hours in the pediatric emergency room. Real-time polymerase chain reaction assays were conducted for analysis. Approximately 18% of the air samples from the pediatric emergency room were found to contain adenovirus. Approximately forty-six percent of the air samples from the pediatric outpatient department contained Mycoplasma pneumoniae DNA products. High detection rates of airborne adenovirus DNA were obtained in July and August in the pediatric public areas. Airborne Mycoplasma pneumoniae was detected only in July in the pediatric emergency room and the peak levels were found from August to January in the pediatric outpatient department. Airborne particles that contained adenovirus and Mycoplasma pneumoniae were the most prevalent in the pediatric public areas. The potential relationship between these airborne viral/bacterial particles and human infection should be examined further

Factors associated with nosocomial SARS-CoV transmission among healthcare workers in Hanoi, Vietnam, 2003

BACKGROUND: In March of 2003, an outbreak of Severe Acute Respiratory Syndrome (SARS) occurred in Northern Vietnam. This outbreak began when a traveler arriving from Hong Kong sought medical care at a small hospital (Hospital A) in Hanoi, initiating a serious and substantial transmission event within the hospital, and subsequent limited spread within the community. METHODS: We surveyed Hospital A personnel for exposure to the index patient and for symptoms of disease during the outbreak. Additionally, serum specimens were collected and assayed for antibody to SARS-associated coronavirus (SARS-CoV) antibody and job-specific attack rates were calculated. A nested case-control analysis was performed to assess risk factors for acquiring SARS-CoV infection. RESULTS: One hundred and fifty-three of 193 (79.3%) clinical and non-clinical staff consented to participate. Excluding job categories with <3 workers, the highest SARS attack rates occurred among nurses who worked in the outpatient and inpatient general wards (57.1, 47.4%, respectively). Nurses assigned to the operating room/intensive care unit, experienced the lowest attack rates (7.1%) among all clinical staff. Serologic evidence of SARS-CoV infection was detected in 4 individuals, including 2 non-clinical workers, who had not previously been identified as SARS cases; none reported having had fever or cough. Entering the index patient's room and having seen (viewed) the patient were the behaviors associated with highest risk for infection by univariate analysis (odds ratios 20.0, 14.0; 95% confidence intervals 4.1–97.1, 3.6–55.3, respectively). CONCLUSION: This study highlights job categories and activities associated with increased risk for SARS-CoV infection and demonstrates that a broad diversity of hospital workers may be vulnerable during an outbreak. These findings may help guide recommendations for the protection of vulnerable occupational groups and may have implications for other respiratory infections such as influenza

In vitro assembly of Ebola virus nucleocapsid-like complex expressed in E. coli

Ebola virus (EBOV) harbors an RNA genome encapsidated by nucleoprotein (NP) along with other viral proteins to form a nucleocapsid complex. Previous Cryo-eletron tomography and biochemical studies have shown the helical structure of EBOV nucleocapsid at nanometer resolution and the first 450 amino-acid of NP (NPΔ451–739) alone is capable of forming a helical nucleocapsid-like complex (NLC). However, the structural basis for NP-NP interaction and the dynamic procedure of the nucleocapsid assembly is yet poorly understood. In this work, we, by using an E. coli expression system, captured a series of images of NPΔ451–739 conformers at different stages of NLC assembly by negative-stain electron microscopy, which allowed us to picture the dynamic procedure of EBOV nucleocapsid assembly. Along with further biochemical studies, we showed the assembly of NLC is salt-sensitive, and also established an indispensible role of RNA in this process. We propose the diverse modes of NLC elongation might be the key determinants shaping the plasticity of EBOV virions. Our findings provide a new model for characterizing the self-oligomerization of viral nucleoproteins and studying the dynamic assembly process of viral nucleocapsid in vitro

Testing statistical significance scores of sequence comparison methods with structure similarity

BACKGROUND: In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. RESULTS: All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. CONCLUSION: The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons

Does Respondent Driven Sampling Alter the Social Network Composition and Health-Seeking Behaviors of Illicit Drug Users Followed Prospectively?

Respondent driven sampling (RDS) was originally developed to sample and provide peer education to injection drug users at risk for HIV. Based on the premise that drug users' social networks were maintained through sharing rituals, this peer-driven approach to disseminate educational information and reduce risk behaviors capitalizes and expands upon the norms that sustain these relationships. Compared with traditional outreach interventions, peer-driven interventions produce greater reductions in HIV risk behaviors and adoption of safer behaviors over time, however, control and intervention groups are not similarly recruited. As peer-recruitment may alter risk networks and individual risk behaviors over time, such comparison studies are unable to isolate the effect of a peer-delivered intervention. This analysis examines whether RDS recruitment (without an intervention) is associated with changes in health-seeking behaviors and network composition over 6 months. New York City drug users (N = 618) were recruited using targeted street outreach (TSO) and RDS (2006–2009). 329 non-injectors (RDS = 237; TSO = 92) completed baseline and 6-month surveys ascertaining demographic, drug use, and network characteristics. Chi-square and t-tests compared RDS- and TSO-recruited participants on changes in HIV testing and drug treatment utilization and in the proportion of drug using, sex, incarcerated and social support networks over the follow-up period. The sample was 66% male, 24% Hispanic, 69% black, 62% homeless, and the median age was 35. At baseline, the median network size was 3, 86% used crack, 70% used cocaine, 40% used heroin, and in the past 6 months 72% were tested for HIV and 46% were enrolled in drug treatment. There were no significant differences by recruitment strategy with respect to changes in health-seeking behaviors or network composition over 6 months. These findings suggest no association between RDS recruitment and changes in network composition or HIV risk, which supports prior findings from prospective HIV behavioral surveillance and intervention studies

Conformational Reorganization of the SARS Coronavirus Spike Following Receptor Binding: Implications for Membrane Fusion

The SARS coronavirus (SARS-CoV) spike is the largest known viral spike molecule, and shares a similar function with all class 1 viral fusion proteins. Previous structural studies of membrane fusion proteins have largely used crystallography of static molecular fragments, in isolation of their transmembrane domains. In this study we have produced purified, irradiated SARS-CoV virions that retain their morphology, and are fusogenic in cell culture. We used cryo-electron microscopy and image processing to investigate conformational changes that occur in the entire spike of intact virions when they bind to the viral receptor, angiotensin-converting enzyme 2 (ACE2). We have shown that ACE2 binding results in structural changes that appear to be the initial step in viral membrane fusion, and precisely localized the receptor-binding and fusion core domains within the entire spike. Furthermore, our results show that receptor binding and subsequent membrane fusion are distinct steps, and that each spike can bind up to three ACE2 molecules. The SARS-CoV spike provides an ideal model system to study receptor binding and membrane fusion in the native state, employing cryo-electron microscopy and single-particle image analysis