A large-scale longitudinal structured dataset of the dark web cryptomarket Evolution (2014-2015)

Dark Web Marketplaces (DWM) facilitate the online trade of illicit goods. Due to the illicit nature of these marketplaces, quality datasets are scarce and difficult to produce. The Dark Net Market archives (2015) presented raw scraped source files crawled from a selection of DWMs, including Evolution. Here, we present, specifically for the Evolution DWM, a structured dataset extracted from Dark Net Market archive data. Uniquely, many of the data quality issues inherent to crawled data are resolved. The dataset covers over 500 thousand forum posts and over 80 thousand listings, providing data on forums, topics, posts, forum users, market vendors, listings, and more. Additionally, we present temporal weighted communication networks extracted from this data. The presented dataset provides easy access to a high quality DWM dataset to facilitate the study of criminal behaviour and communication on such DWMs, which may provide a relevant source of knowledge for researchers across disciplines, from social science to law to network science.Comment: 19 pages, 5 figure

The Potential Role of Marine Fungi in Plastic Degradation – A Review

Plastic debris has been accumulating in the marine realm since the start of plastic mass production in the 1950s. Due to the adverse effects on ocean life, the fate of plastics in the marine environment is an increasingly important environmental issue. Microbial degradation, in addition to weathering, has been identified as a potentially relevant breakdown route for marine plastic debris. Although many studies have focused on microbial colonization and the potential role of microorganisms in breaking down marine plastic debris, little is known about fungi-plastic interactions. Marine fungi are a generally understudied group of microorganisms but the ability of terrestrial and lacustrine fungal taxa to metabolize recalcitrant compounds, pollutants, and some plastic types (e.g., lignin, solvents, pesticides, polyaromatic hydrocarbons, polyurethane, and polyethylene) indicates that marine fungi could be important degraders of complex organic matter in the marine realm, too. Indeed, recent studies demonstrated that some fungal strains from the ocean, such as Zalerion maritimum have the ability to degrade polyethylene. This mini-review summarizes the available information on plastic-fungi interactions in marine environments. We address (i) the currently known diversity of fungi colonizing marine plastic debris and provide (ii) an overview of methods applied to investigate the role of fungi in plastic degradation, highlighting their advantages and drawbacks. We also highlight (iii) the underestimated role of fungi as plastic degraders in marine habitats

Sedimentary geology of the Middle Carboniferous of the Donbas region (Dniepr-Donets basin, Ukraine)

Peer reviewedPublisher PD

Malassezia infections in humans and animals: pathophysiology, detection and treatment

not availabl

Early warning signals for predicting cryptomarket vendor success using dark net forum networks

In this work we focus on identifying key players in dark net cryptomarkets. Law enforcement aims to disrupt criminal activity conducted through these markets by targeting key players vital to the market's existence and success. We particularly focus on detecting successful vendors responsible for the majority of illegal trade. Our methodology aims to uncover whether the task of key player identification should center around plainly measuring user and forum activity, or that it requires leveraging specific patterns of user communication. We focus on a large-scale dataset from the Evolution cryptomarket, which we model as an evolving communication network. While user and forum activity measures are useful for identifying the most successful vendors, we find that betweenness centrality additionally identifies those with lesser activity. But more importantly, analyzing the forum data over time, we find evidence that attaining a high betweenness score comes before vendor success. This suggests that the proposed network-driven approach of modelling user communication might prove useful as an early warning signal for key player identification

Soil Moisture Data for the Validation of Permafrost Models Using Direct and Indirect Measurement Approaches at Three Alpine Sites

To date, there has been no comprehensive review of the epidemiology, risk factors, species distribution, and outcomes of candidemia in Iran. This study aimed to perform a systematic review and meta-analysis of all reported candidemia cases in Iran until December 2015. The review process occurred in three steps, namely a literature search, data extraction and statistical analyses. After a comprehensive literature search, we identified 55 cases. The mean age of patients was 46.80±24.30 years (range 1–81 years). The main risk factors for candidemia were surgery and burns (23.6%), followed by malignancies (20%), use of broad-spectrum antibiotics (18.2%), and diabetes (7.3%). Candida parapsilosis (n=17, 30.8%) was the leading agent, followed by Candida albicans (n=15, 27.3%), Candida glabrata (n=10, 18.2%), and Candida tropicalis (n=8, 14.5%). The frequencies of candidemia cases due to C. glabrata, C. parapsilosis, and C. albicans were significantly higher among patients aged>60, 21–40, and 41–60 years, respectively. Comparison of risk factors for candidemia by multiple logistic regression showed that one of the most important risk factors was surgery (OR: 4.245; 95% CI: 1.141–15.789; P=0.031). The outcome was recorded in only 19 cases and 13 of those patients (68.4%) expired. This study confirms that knowledge of the local epidemiology is important when conducting surveillance studies to prevent and control candidemia and will be of interest for antifungal stewardship

Use of amplified fragment length polymorphism analysis to identify medically important Candida spp., including C. dubliniensis.

Non-Candida albicans Candida species are increasingly being isolated. These species show differences in levels of resistance to antimycotic agents and mortality. Therefore, it is important to be able to correctly identify the causative organism to the species level. Identification of C. dubliniensis in particular remains problematic due to the high degree of phenotypic similarity between this species and C. albicans. The use of amplified fragment length polymorphism (AFLP) analysis as an identification method for medically important Candida species was investigated. Our results show very clear differences among medically important Candida species. Furthermore, when screening a large collection of clinical isolates previously identified on CHROMagar as C. albicans, we found a misidentification rate of 6%. AFLP analysis is universally applicable, and the patterns can easily be stored in a general, accessible database. Therefore, AFLP might prove to be a reliable method for the identification of medically important Candida species

Apparat zur Reduction des Barometerstandes auf 760 Millimeter

n/