Occurrence, Diversity and Anti-Fungal Resistance of Fungi in Sand of an Urban Beach in Slovenia—Environmental Monitoring with Possible Health Risk Implications

This article belongs to the Special Issue Fungal Diversity in Europe.Beach safety regulation is based on faecal indicators in water, leaving out sand and fungi, whose presence in both matrices has often been reported. To study the abundance, diversity and possible fluctuations of mycobiota, fungi from sand and seawater were isolated from the Portorož beach (Slovenia) during a 1-year period. Sand analyses yielded 64 species of 43 genera, whereas seawater samples yielded 29 species of 18 genera. Environmental and taxonomical data of fungal communities were analysed using machine learning approaches. Changes in the air and water temperature , sunshine hours, humidity and precipitation, air pressure and wind speed appeared to affect mycobiota. The core genera Aphanoascus, Aspergillus, Fusarium, Bisifusarium, Penicillium, Tala-romyces, and Rhizopus were found to compose a stable community within sand, although their presence and abundance fluctuated along with weather changes. Aspergillus spp. were the most abundant and thus tested against nine antimycotics using Sensititre Yeast One kit. Aspergillus niger and A. welwitschiae isolates were found to be resistant to amphotericin B. Additionally, four possible human pollution indicators were isolated during the bathing season, including Meyerozyma, which can be used in beach microbial regulation. Our findings provide the foundations for additional research on sand and seawater mycobiota and show the potential effect of global warming and extreme weather events on fungi in sand and sea.The work of Monika Novak Babiˇc was supported by Slovenian Research Agency (ARRS) through the postdoctoral research project (grant number Z7-2668) and the research program, grant number P1-0198. The work of Sašo Džeroski was supported by Slovenian Research Agency (ARRS) through the program Knowledge Technologies (grant number P2-0103). The work of João Brandão received financial support from CESAM (UID/AMB/50017-POCI-01-0145-FEDER-007638) and CITAB (UID/AGR/04033/2019), via FCT/MCTES, from national funds (PIDDAC), co-founded by FEDER, (PT2020 Partnership Agreement and Compete 2020)info:eu-repo/semantics/publishedVersio

Synchronization of data sources with Microsoft Sync Framework

More and more companies are opting for informatisation of field operations. Regardless of the outcome of the integration, looking from a business perspective, all mobile applications technically face the problem of safe access to the central database without communication failures. In this thesis, I have explained and implemented synchronization of various data sources, through which the end-users can transfer a subset of centralized data to their mobile devices. Enriched information from the field is later, again by means of synchronization, transferred back to the central database. Synchronization between the consuming devices and server is implemented via WCF service. Mock solution is implemented using Microsoft Sync Framework with MS SQL Server 2008 R2 and MS SQL Server CE 3.5 acting as server and client database back-ends respectively. Stored procedures, which are used during the synchronization process, are explained in detail. Since this work is based on a real-life project, it also includes information on security, debugging and unit testing

Dilemmas of urban planning based on private initiatives

Ne glede na vtis, da se zaradi sedanjih gospodarskih razmer pritisk različnih interesnih skupin na prostor zmanjšuje, ostaja vprašanje vključevanja vseh deležnikov v postopek planiranja eden izmed ključnih izzivov planerske prakse. Glede na to prispevek obravnava vidike sprejemljivosti vključevanja individualnih pobud v odločevalski proces, pri čemer gradi na predpostavki, da na eni strani na pobudah temelječi urbanizem ne vodi v vzdržen prostorski razvoj, na drugi strani pa obstoječi kriterijski pristop usmerjanja prostorskega razvoja ne daje optimalnih rezultatov.Notwithstanding the impression that the pressure on land is decreasing because of the current economic crisis, the challenge of a contemporary urban planning to involve all stakeholders as equally as possible in the planning process remains unchanged. This article focuses on the acceptability of the integration private initiatives into the decision-making process. It asserts that urban planning based on private initiative does not lead to a sustainable spatial developmentfurthermore, the existing criteria-based land development approach does not necessarily give optimal results

CLUSplus: A decision tree-based framework for predicting structured outputs

We present CLUSplus, a machine learning framework based on decision trees specialized for complex predictive modeling tasks. We provide the scientific community with an open source Java framework that unifies several major research directions in the machine learning field. The framework supports multi-target prediction, i.e., the simultaneous prediction of multiple continuous values, multiple discrete values, and hierarchically organized discrete values. Furthermore, CLUSplus enables state-of-the-art predictive performance via ensemble learning, exploitation of unlabeled data via semi-supervised learning, and data understanding via feature importance and building interpretable models. Out of a wide array of machine learning frameworks available today, very few support complex predictive modeling tasks and, to the best of our knowledge, none support all of the aforementioned functionalities

Evaluating the effect of Clostridium difficile conditioned medium on fecal microbiota community structure

Abstract Clostridium difficile infection (CDI) is typically associated with disturbed gut microbiota and changes related to decreased colonization resistance against C. difficile are well described. However, nothing is known about possible effects of C. difficile on gut microbiota restoration during or after CDI. In this study, we have mimicked such a situation by using C. difficile conditioned medium of six different C. difficile strains belonging to PCR ribotypes 027 and 014/020 for cultivation of fecal microbiota. A marked decrease of microbial diversity was observed in conditioned medium of both tested ribotypes. The majority of differences occurred within the phylum Firmicutes, with a general decrease of gut commensals with putative protective functions (i.e. Lactobacillus, Clostridium_XIVa) and an increase in opportunistic pathogens (i.e. Enterococcus). Bacterial populations in conditioned medium differed between the two C. difficile ribotypes, 027 and 014/020 and are likely associated with nutrient availability. Fecal microbiota cultivated in medium conditioned by E. coli, Salmonella Enteritidis or Staphylococcus epidermidis grouped together and was clearly different from microbiota cultivated in C. difficile conditioned medium suggesting that C. difficile effects are specific. Our results show that the changes observed in microbiota of CDI patients are partially directly influenced by C. difficile

Effect of Location, Disinfection, and Building Materials on the Presence and Richness of Culturable Mycobiota through Oligotrophic Drinking Water Systems

Safe drinking water is a constant challenge due to global environmental changes and the rise of emerging pathogens—lately, these also include fungi. The fungal presence in water greatly varies between sampling locations. Little is known about fungi from water in combination with a selection of materials used in water distribution systems. Our research was focused on five water plants located in the Pannonian Plain, Slovenia. Sampled water originated from different natural water sources and was subjected to different cleaning methods before distribution. The average numbers of fungi from natural water, water after disinfection, water at the first sampling point in the water network, and water at the last sampling point were 260, 49, 64, and 97 CFU/L, respectively. Chlorination reduced the number of fungi by a factor of 5, but its effect decreased with the length of the water network. The occurrence of different fungi in water and on materials depended on the choice of material. The presence of the genera Aspergillus, Acremonium, Furcasterigmium, Gliomastix, and Sarocladium was mostly observed on cement, while Cadophora, Cladosporium, Cyphellophora, and Exophiala prevailed on metals. Plastic materials were more susceptible to colonization with basidiomycetous fungi. Opportunistically pathogenic fungi were isolated sporadically from materials and water and do not represent a significant health risk for water consumers. In addition to cultivation data, physico-chemical features of water were measured and later processed with machine learning methods, revealing the sampling location and water cleaning processes as the main factors affecting fungal presence and richness in water and materials in contact with water

Xerophilic fungi contaminating historically valuable easel paintings from Slovenia

Historically valuable canvas paintings are often exposed to conditions enabling microbial deterioration. Painting materials, mainly of organic origin, in combination with high humidity and other environmental conditions, favor microbial metabolism and growth. These preconditions are often present during exhibitions or storage in old buildings, such as churches and castles, and also in museum storage depositories. The accumulated dust serves as an inoculum for both indoor and outdoor fungi. In our study, we present the results on cultivable fungi isolated from 24 canvas paintings, mainly exhibited in Slovenian sacral buildings, dating from the 16th to 21st centuries. Fungi were isolated from the front and back of damaged and undamaged surfaces of the paintings using culture media with high- and low-water activity. A total of 465 isolates were identified using current taxonomic DNA markers and assigned to 37 genera and 98 species. The most abundant genus was Aspergillus, represented by 32 species, of which 9 xerophilic species are for the first time mentioned in contaminated paintings. In addition to the most abundant xerophilic A. vitricola, A. destruens, A. tardicrescens, and A. magnivesiculatus, xerophilic Wallemia muriae and W. canadensis, xerotolerant Penicillium chrysogenum, P. brevicompactum, P. corylophilum, and xerotolerant Cladosporium species were most frequent. When machine learning methods were used to predict the relationship between fungal contamination, damage to the painting, and the type of material present, proteins were identified as one of the most important factors and cracked paint was identified as a hotspot for fungal growth. Aspergillus species colonize paintings regardless of materials, while Wallemia spp. can be associated with animal fat. Culture media with low-water activity are suggested in such inventories to isolate and obtain an overview of fungi that are actively contaminating paintings stored indoors at low relative humidity

Machine-learning ready data on the thermal power consumption of the Mars Express Spacecraft.

We present six datasets containing telemetry data of the Mars Express Spacecraft (MEX), a spacecraft orbiting Mars operated by the European Space Agency. The data consisting of context data and thermal power consumption measurements, capture the status of the spacecraft over three Martian years, sampled at six different time resolutions that range from 1 min to 60 min. From a data analysis point-of-view, these data are challenging even for the more sophisticated state-of-the-art artificial intelligence methods. In particular, given the heterogeneity, complexity, and magnitude of the data, they can be employed in a variety of scenarios and analyzed through the prism of different machine learning tasks, such as multi-target regression, learning from data streams, anomaly detection, clustering, etc. Analyzing MEX's telemetry data is critical for aiding very important decisions regarding the spacecraft's status and operation, extracting novel knowledge, and monitoring the spacecraft's health, but the data can also be used to benchmark artificial intelligence methods designed for a variety of tasks