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Cosmic rays interact with fields and background radiation as they propagate in space, producing particle cascades of various sizes, shapes and constituents. The potential observation of at least parts of such phenomena, referred to as cosmic-ray ensembles (CRE), from Earth would open a new channel of cosmic-ray investigation, since it might be a manifestation of fundamental symmetries of nature. Research dedicated to CRE is one of the main scientific objectives of the Cosmic-Ray Extremely Distributed Observatory (CREDO) Collaboration, and with this article we address one of the cornerstones of the relevant scientific program: the simulation method dedicated to CRE studies. Here we focus on CRE resulting from synchrotron radiation by high energy electrons as one of the most prevalent energy loss processes. Providing the example of simulation output analysis, we demonstrate the advantages of our approach as well as discuss the possibility of generalization of current research.

One of the main objectives of the CREDO project is to register cosmic-ray cascades in many distributed detectors in the search for so-called Cosmic-Ray Ensembles (CRE). This requires precise knowledge of the probability of detection of individual Extensive Air Showers (EAS) in a very wide range of energies and an analysis of their correlations. The standard approach based on detailed and extensive simulations is not possible for many such systems; thus, a faster method is developed. Knowing the characteristics of EAS from more general simulations, any required probability is calculated. Such probability depends on particle density at a given point, which is a function of the distance from the centre of the cascade, the energy, mass and the zenith angle of the primary cosmic-ray particle. It is necessary to use proper distribution of the number of secondary particles reaching the ground and their fluctuations. Finally, to calculate the total probability of EAS detection, the primary cosmic-ray spectrum and abundance of various particles in it have to be taken into account. The effective probability can be used to estimate the expected number of EAS events measured by a set of small detectors. In this work, results from several versions of calculations, with different complexity levels, are presented and compared with the first measurement performed with a test detector system. These results confirm that the majority of events observed with this small detector array are caused by cosmic-ray particles with very high energies. Such analysis can be also useful for the design of more effective systems in the future. Slightly larger systems of simple detectors may be used to distinguish cascades initiated by photons from those started from other primary cosmic-ray particles.

Restoring endangered plant species to their historical sites is not always possible due to constantly changing habitat conditions. The aim of this study was to test the effects of reintroduction of two relict willow species in eastern Poland. The experiment consisted of planting 48 individuals of Salix lapponum and S. myrtilloides, obtained by micropropagation, at each of the two selected sites and observing their survival after one year. At the same time, selected physicochemical and biocenotic factors of the environment were monitored. About 70% of S. lapponum individuals and 50% of S. myrtilloides plants survived the one-year period. This result can be considered satisfactory and confirms the effectiveness of this means of active protection. The results of measurements of selected abiotic factors of the environment and the observations and ecological analysis of the flora indicated that the habitat conditions of both historical sites have changed, resulting in accelerated succession of vegetation. However, complete habitat degradation did not occur, although the development of a multi-story structure of one of the phytocenoses intensified competition for light and other environmental resources, which narrowed the potential ecological niche of the reintroduced species.

Reliable tools for artefact rejection and signal classification are a must for cosmic ray detection experiments based on CMOS technology. In this paper, we analyse the fitness of several feature-based statistical classifiers for the classification of particle candidate hits in four categories: spots, tracks, worms and artefacts. We use Zernike moments of the image function as feature carriers and propose a preprocessing and denoising scheme to make the feature extraction more efficient. As opposed to convolution neural network classifiers, the feature-based classifiers allow for establishing a connection between features and geometrical properties of candidate hits. Apart from basic classifiers we also consider their ensemble extensions and find these extensions generally better performing than basic versions, with an average recognition accuracy of 88%.

The wealth of smartphone data collected by the Cosmic Ray Extremely Distributed Observatory (CREDO) greatly surpasses the capabilities of manual analysis. So, efficient means of rejecting the non-cosmic-ray noise and identification of signals attributable to extensive air showers are necessary. To address these problems we discuss a Convolutional Neural Network-based method of artefact rejection and complementary method of particle identification based on common statistical classifiers as well as their ensemble extensions. These approaches are based on supervised learning, so we need to provide a representative subset of the CREDO dataset for training and validation. According to this approach over 2300 images were chosen and manually labeled by 5 judges. The images were split into spot, track, worm (collectively named signals) and artefact classes. Then the preprocessing consisting of luminance summation of RGB channels (grayscaling) and background removal by adaptive thresholding was performed. For purposes of artefact rejection the binary CNN-based classifier was proposed which is able to distinguish between artefacts and signals. The classifier was fed with input data in the form of Daubechies wavelet transformed images. In the case of cosmic ray signal classification, the well-known feature-based classifiers were considered. As feature descriptors, we used Zernike moments with additional feature related to total image luminance. For the problem of artefact rejection, we obtained an accuracy of 99\%. For the 4-class signal classification, the best performing classifiers achieved a recognition rate of 88\%.

Marcin Piekarczyk, Olaf Bar, Łukasz Bibrzycki, Michał Niedźwiecki, Krzysztof Rzecki, Sławomir Stuglik, Thomas Andersen, Nikolay M. Budnev, David E. Alvarez-Castillo, Kévin Almeida Cheminant, Dariusz Góra, Alok C. Gupta, Bohdan Hnatyk, Piotr Homola, Robert Kamiński, Marcin Kasztelan, Marek Knap, Péter Kovács, Matías Rosas, Oleksandr Sushchov, Katarzyna Smelcerz, Karel Smolek, Jarosław Stasielak, Tadeusz Wibig, Krzysztof W. Woźniak, Jilberto Zamora-Saa, Gamification is known to enhance users’ participation in education and research projects that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory (CREDO) experiment is designed for the large-scale study of various radiation forms that continuously reach the Earth from space, collectively known as cosmic rays. The CREDO Detector app relies on a network of involved users and is now working worldwide across phones and other CMOS sensor-equipped devices. To broaden the user base and activate current users, CREDO extensively uses the gamification solutions like the periodical Particle Hunters Competition. However, the adverse effect of gamification is that the number of artefacts, i.e., signals unrelated to cosmic ray detection or openly related to cheating, substantially increases. To tag the artefacts appearing in the CREDO database we propose the method based on machine learning. The approach involves training the Convolutional Neural Network (CNN) to recognise the morphological difference between signals and artefacts. As a result we obtain the CNN-based trigger which is able to mimic the signal vs. artefact assignments of human annotators as closely as possible. To enhance the method, the input image signal is adaptively thresholded and then transformed using Daubechies wavelets. In this exploratory study, we use wavelet transforms to amplify distinctive image features. As a result, we obtain a very good recognition ratio of almost 99% for both signal and artefacts. The proposed solution allows eliminating the manual supervision of the competition process.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) was established to detect and study ultra high-energy cosmic ray particles. In addition to making use of traditional methods for finding rare and extended cosmic ray events such as professional-grade Extensive Air Shower (EAS) arrays, as well as educational &lsquo, class-room&rsquo, detectors, CREDO also makes use of cameras in smartphones as particle detectors. Beyond the primary scientific goal of the CREDO project, to detect Cosmic Ray Ensembles, is the equally important educational goal of the project. To use smartphones for EAS detection, it is necessary to demonstrate that they are capable of effectively registering relativistic charged particles. In this article, we show that the events recorded in the CREDO project database are indeed tracing incoherent cosmic ray muons. The specific observed distribution of zenith angle of charged particle direction corresponds to that expected for muons. It is difficult, if not impossible, to imagine different mechanisms leading to such a distribution, and we believe it clearly demonstrates the suitability of smartphone-based detectors in supporting the more traditional cosmic ray detectors.

The authors acknowledge COST Action ES 1105 "CYANOCOST Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management" and COST Action Global Change Biology ES 1201 NETLAKE -Networking Lake Observatories in Europe" for contributing to this study through networking and knowledge sharing with European experts in the field. We acknowledge the members of the Global Lake Ecological Observatory Network (GLEON) for their collaborative spirit and enthusiasm that inspired the grassroots effort of the EMLS. E.M. was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis. We thank Pieter Slot for assisting with the pigment analysis. We thank Dr. Ian Jones for valuable feedback on an earlier version of the manuscript. We thank the Leibniz Institute of Freshwater Ecology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart, and the Leibniz Association for financial support. H.P. was supported by the US National Science Foundation (1840715, 1831096). A.C.'s work was funded by the Spanish Agencia Estatal de Investigacion and EU funds through the project CLIMAWET (CGL2015-69557-R). The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland. We are grateful to Kristiina Vuorio from the Freshwater Centre of the Finnish Environment institute for her help in organizing, collecting and analysing samples by the University of Jyvaskyla and to Gerald Dorflinger from the Water Development Department of Cyprus for his assistance with the sampling in Cyprus and for granting the CUT team permission to use WDD's equipment. Finally, we would like to thank the numerous other assistants that helped realizing each local survey. Open access funding provided by Universite de Geneve., To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L-1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4 degrees C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature., European Cooperation in Science and Technology (COST) ES 1105 ES 1201, Swiss State Secretariat for Education, Research and Innovation, University of Geneva, Leibniz Association, National Science Foundation (NSF) 1840715 1831096, Spanish Agencia Estatal de Investigacion, European Commission CGL2015-69557-R, Department of Agriculture, Environment and Rural Affairs, Northern Ireland

We present the purpose, long-term development vision, basic design, detection algorithm and preliminary results obtained with the Cosmic Ray Extremely Distributed Observatory (CREDO) Detector mobile application. The CREDO Detector app and related infrastructure are unique in terms of their scale, targeting many form-factors and open-access philosophy. This philosophy translates to the open-source code of the app, open-access in terms of both data inflow as well as data consumption and above all, the citizen science philosophy that means that the infrastructure is open to all who wish to participate in the project. The CREDO infrastructure and CREDO Detector app are designed for the large-scale study of various radiation forms that continuously reach the Earth from space, but with the sensitivity to local radioactivity as well. Such study has great significance both scientifically and educationally as cosmic radiation has an impact on diverse research areas from life on Earth to the functioning of modern electronic devices. The CREDO Detector app is now working worldwide across phones, tablets, laptops, PCs and cheap dedicated registration stations. These diverse measurements contribute to the broader search for large-scale cosmic ray correlations, as well as the CREDO-specific proposed extensive air showers and incoherent secondary cosmic rays.

Muons and other ionizing radiation produced by cosmic rays and radiative decays affect CMOS/CCD sensor. When particles colliding with sensors atoms cause specific kind of noise on images recorded by cameras. We present a concept and preliminary implementation of method for recognizing those events and algorithms for image processing and their classification by machine learning. Our method consists of analyzing the shape of traces present in images recorded by a camera sensor and metadata related to an image like camera model, GPS location of camera, vertical and horizontal orientation of a camera sensor, timestamp of image acquisition, and other events recognized near-by sensors. The so created feature vectors are classified as either a muon-like event, an electron-like event or the other event, possibly noise. For muon-like events our method estimates azimuth of a muon track. Source of the data is database of CREDO (Cosmic-Ray Extremely Distributed Observatory) project and ESO (European Southern Observatory) archives. The telescope dark frames from ESO are analysed. CREDO project collected so far over 2 millions images of events from many kinds of cameralike: smartphones camera, laptop webcams and Internet of Things cameras localised around the globe.

The search for Cosmic-Ray Ensembles (CRE), groups of correlated cosmic rays that might be distributed over very large areas, even of the size of the planet, requires a globally spread and dense network of detectors, as proposed by the Cosmic-Ray Extremely Distributed Observatory (CREDO) Collaboration. This proposal motivates an effort towards exploring the potential of using even very much diversified detection technologies within one system, with detection units located even in hard-to-reach places, where, nevertheless, the sensors could work independently - without human intervention. For these reasons we have developed a dedicated communication solution enabling the connection of many different types of detectors, in a range of environments. The proposed data transmission system uses radio waves as an information carrier on the 169MHz frequency band in a contrast to the typical commercially used frequencies in a IoT systems (868MHz). The connectivity within the system is based on the star topology, which ensures the least energy consumption. The solution is now being prepared to being implemented using the prototype detection system based on the CosmicWatch open hardware design: a portable, pocket size, and economy particle detector using the scintillation technique. Our prototype detector is equipped with a dedicated software that integrates it with the already operational CREDO server system., Comment: ICRC2019

We study the feasibility of detecting preshower initiated by ultra-high energy photons using Monte-Carlo simulations of nearly horizontal air showers for the example of the La Palma site of the Cherenkov Telescope Array. We investigate the efficiency of multivariate analysis in correctly identifying preshower events initiated by 40 EeV photons and cosmic-ray dominated background simulated in the energy range 10 TeV -- 10 EeV. The effective areas for such kind of events are also investigated and event rate predictions related to different ultra-high energy photons production models are presented. While the expected number of preshowers from diffuse emission of UHE photon for 30 hours of observation is estimated around $3.3\times10^{-5}$ based on the upper limits put by the Pierre Auger Observatory, this value is at the level of $2.7\times10^{-4}$ ($5.7\times 10^{-5}$) when considering the upper limits of the Pierre Auger Observatory (Telescope Array) on UHE photon point sources. However, UHE photon emission may undergo possible "boosting" due to gamma-ray burst, increasing the expected number of preshower events up to 0.17 and yielding a minimum required flux of $\sim 0.2$ $\mathrm{km^{-2}yr^{-1}}$ to obtain one preshower event, which is about a factor 10 higher than upper limits put by the Pierre Auger Observatory and Telescope Array (0.034 and 0.019 $\mathrm{km^{-2}yr^{-1}}$, respectively)., Comment: 16 pages, 16 figures, 4 tables

Despite its ecological importance, little information is available regarding spatial and seasonal changes in the testate amoebae community in peat bogs. The objectives of this study were to examine the structure of communities and horizontal distribution of testate amoebae fauna, to improve the understanding of factors affecting the distribution of moss testate amoebae communities and to analyze the seasonal changes in testate amoebae communities in a Sphagnum-dominated peat bog (eastern Poland). A total of 45 testate amoebae species were identified in the samples. The highest species richness occurred in hollows dominated by Sphagnum angustifollum, much lower numbers of taxa were observed in hummocks dominated by Sphagnum magellanicum and Polytrichum. The Monte Carlo permutation test showed the significance of Ntot, temperature, pH, and the depth to the water table for the variability of testate amoebae in all microhabitats. Species found in spring samples were associated with the increased Ntot content. Species occurring in summer samples were associated with the increasing pH gradient and species developing in late spring and autumn preferred a greater depth to the water table.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is the project to search and study ultra high-energy cosmic ray particles from deep space producing simultaneous extensive air showers over the entire exposed surface of the Earth. The concept of the CREDO infrastructure assumes absorbing all kinds of cosmic ray data from any apparatus all over the world, including professional instruments, educational detectors and arrays, and popular devices such as smartphones. We discuss here the usefulness and possibilities of using the last one and present the educational CREDO-Maze mini array comprised of four CosmicWatch detectors. This simple and affordable apparatus is shown to be able to register the extensive air showers and can be used to study cosmic rays much more effectively than the simple two-detector CosmicWatch muon telescope station. The further development direction is indicated.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project dedicated to global studies of extremely extended cosmic-ray phenomena, the cosmic-ray ensembles (CRE), beyond the capabilities of existing detectors and observatories. Up to date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-rays, which may overspread a significant fraction of the Earth, is a scientific terra incognita. Instead of developing and commissioning a completely new global detector infrastructure, CREDO proposes approaching the global cosmic-ray analysis objectives with all types of available detectors, from professional to pocket size, merged into a worldwide network. With such a network it is possible to search for evidences of correlated cosmic-ray ensembles. One of the observables that can be investigated in CREDO is a number of spatially isolated events collected in a small time window which could shed light on fundamental physics issues. The CREDO mission and strategy requires active engagement of a large number of participants, also non-experts, who will contribute to the project by using common electronic devices (e.g. smartphones). In this note the status and perspectives of the project is presented., This article belongs to the Special Issue Selected Papers from the 7th International Conference on New Frontiers in Physics (ICNFP 2018)

Laser-induced breakdown spectroscopy (LIBS) is an important analysis technique with applications in many industrial branches and fields of scientific research. Nowadays, the advantages of LIBS are impaired by the main drawback in the interpretation of obtained spectra and identification of observed spectral lines. This procedure is highly time-consuming since it is essentially based on the comparison of lines present in the spectrum with the literature database. This paper proposes the use of various computational intelligence methods to develop a reliable and fast classification of quasi-destructively acquired LIBS spectra into a set of predefined classes. We focus on a specific problem of classification of paper-ink samples into 30 separate, predefined classes. For each of 30 classes (10 pens of each of 5 ink types combined with 10 sheets of 5 paper types plus empty pages), 100 LIBS spectra are collected. Four variants of preprocessing, seven classifiers (decision trees, random forest, k-nearest neighbor, support vector machine, probabilistic neural network, multi-layer perceptron, and generalized regression neural network), 5-fold stratified cross-validation, and a test on an independent set (for methods evaluation) scenarios are employed. Our developed system yielded an accuracy of 99.08%, obtained using the random forest classifier. Our results clearly demonstrates that machine learning methods can be used to identify the paper-ink samples based on LIBS reliably at a faster rate.

Cyanobacterial blooms are an increasing threat worldwide. Invasions of certain cyanobacterial species, mainly towards higher latitudes, add to this concern as they enrich the pool of potential bloom-formers in the invaded region. Among the numerous causes of this escalating process, climate warming is commonly considered the most crucial factor, but empirical studies of this issue are lacking. The aim of our study was to identify physical, chemical and biological factors related to the occurrence of an invasive cyanobacterium at the northern border of its putative current range, and thus enabling its expansion. This study focuses on the relatively little studied species Sphaerospermopsis aphanizomenoides (Nostocales, Cyanobacteria; synonyms: Aphanizomenon aphanizomenoides, Anabaena aphanizomenoides), which is predicted to become one of the main nuisance species of the future. Forty-nine freshwater lakes located between latitudes 51° and 55°N were examined for the presence of S. aphanizomenoides, and environmental factors that could drive its occurrence were studied simultaneously. To identify factors correlated with the presence of the species, principal component analysis (PCA) and Mann-Whitney U test were performed. Water temperature did not differentiate lakes with or without S. aphanizomenoides, however the study was conducted in a particularly hot summer. Total phosphorus concentration was identified as the primary driving factor of the occurrence of S. aphanizomenoides. The species grew in poor light conditions and high phytoplankton biomass, mainly in shallow lakes. As shown by detrended correspondence analysis (DCA), the species accompanied shade tolerant, eutrophic species of native and invasive cyanobacteria as well as eukaryotic algae. Our results indicate that eutrophication may be the primary factor enabling the increasing occurrence of S. aphanizomenoides in temperate environments, and suggest that this process may stimulate expansion of cyanobacterial species towards high latitudes.

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains. © 2018 by the authors. Licensee MDPI, Basel, Switzerland., The authors acknowledge COST Action ES 1105 “CYANOCOST—Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE—Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from the University of Geneva. We thank Clare Ahnlund, Ena Suarez and Irene Gallego for helping out with the Swiss survey. We thank Wendy Beekman and Els J. Faassen for the nutrient and toxin analysis.

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment., The authors acknowledge COST Action ES 1105 “CYANOCOST – Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE – Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis and the University of Wageningen for covering the costs of this analysis from the personal funding of dr. Miquel Lürling. We thank Pieter Slot for assisting with the pigment analysis and the University of Amsterdam for covering the costs of the analysis through funding from the group of Prof. Jef Huisman and dr. Petra Visser (IBED). We would like to thank the Environmental Data Initiative for covering the cost of archiving the EMLS dataset. We would like to thank the Leibniz Institute of Freshwater Ecology and Inland Fisheries, Dept. of Experimental Limnology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart; and the Leibniz Association for financial support. The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland.

Epiphytic algae are an important group of organisms involved in primary productivity, nutrient cycling, and energy transfer in littoral food webs. However, multifactorial studies conducted on epiphyton on the same substrate across a spectrum of environmental parameters are very limited. Here, we present first complex field study on the role of abiotic and biotic factors in shaping the species richness, diversity, abundance, and biomass composition of epiphyton on common reed in four shallow lakes with different trophic status, water and fish management, and the abundance and structure of potential algal grazers: littoral crustaceans and fish. The obtained results revealed that the algal taxa richness was the lowest in the hypertrophic lake and the highest in the meso-eutrophic lake. Epiphyton abundance (predominated by pennate diatoms) and biomass were found to be the highest in eutrophic water bodies. Biomass consisted primarily of diatoms, but we found the seasonal predominance of filamentous Chlorophyta (in the eutrophic lakes) and Chlorophyceae (in the meso-eutrophic lake). Redundancy analysis (RDA) showed that the frequency of water level fluctuations was the most significant variable in the composition of epiphyton. RDA also revealed the importance of grazing pressure of fish. Thus, in hydrologically transformed lakes, man-made factors may be of great relevance in the development of epiphytic algae.

Man-made peat pools are permanent freshwater habitats developed due to non-commercial man-made peat extraction. Yet, they have not been widely surveyed in terms of ecosystem functioning, mainly regarding the complexity of heterotrophic components of the plankton. In this study we analysed distribution and trophic interrelations among heterotrophic plankton in man-made peat pools located in different types of peatbogs. We found that peat pools showed extreme differences in environmental conditions that occurred to be important drivers of distribution of microplankton and metazooplankton. Abundance of bacteria and protozoa showed significant differences, whereas metazooplankton was less differentiated in density among peat pools. In all peat pools stress-tolerant species of protozoa and metazoa were dominant. In each peat pool five trophic functional groups were distinguished. The abundance of lower functional trophic groups (bacteria, heterotrophic nanoflagellates (HNF) and ciliates feeding on bacteria and HNF) was weakly influenced by environmental drivers and was highly stable in all peat pool types. Higher functional trophic groups (naupli, omnivorous and carnivorous ciliates, cladocerans, adult copepods and copepodites) were strongly influenced by environmental variables and exhibited lower stability. Our study contributes to comprehensive knowledge of the functioning of peat bogs, as our results have shown that peat pools are characterized by high stability of the lowest trophic levels, which can be crucial for energy transfer and carbon flux through food webs.

Biometrics is based on the analysis of biometric features and is usually used for person recognition. In this article we analyze biometric features related to touch screen gestures. The proposed approach to person identification has a great application potential due to the popularity of mobile devices, so research in this area will be an important direction of technological development. The aims of this research are to design and build a data acquisition system to collect surveys resulting from the execution of single finger gestures on a mobile device screen and to propose data preprocessing procedure and to indicate the best classification method for person recognition based on these surveys. The experiment with fifty persons, nine gestures and ten repetitions was performed, so 4 500 surveys acquired and analyzed within the developed system. Depending on the classification method the accuracy of the task of gesture-based person recognition was in the range from 96.60% to 99.29%. All the patterns, which achieved the highest performance in terms of the typical performance measures consist of a single connected movement of a finger over the touch screen. The patterns which include multiple disconnected segments and/or taps are less successful in the task of recognizing people.

W niniejszym artykule, na podstawie bazy artykułów naukowych, opisano ilościowy efekt wzrostu współpracy uczonych, która objawia się zmianami cech rozkładu liczby współautorów artykułu w czasie. Rozkład liczby współautorów artykułu dostępnego w bazie danych zmienia się w czasie z maksimum dla jednego autora do maksimum kilku autorów. Do wyjaśnienia dynamiki zmian rozkładu liczby współautorów zaproponowano model dylematu społecznego. Spośród trzech została wybrana jedna strategia współpracy odnosząca największe sukcesy. In the present paper, the case of a database of scientific articles is described. There can be observed the quantitative effects of the increasing strength of cooperation between scholars. It is manifested in time-related features changes of the numbers distribution of a single co-authors’ article. The distribution of the number of co-authors of an article recorded in the database evolves with time from a profile with no more than one author to a profile with several authors. A social dilemma model is proposed to explain the dynamics of changes in the distribution of the number of co-authors. The most successful strategy of the three considered alternative strategies of cooperation is selected.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project created a few years ago in the Institute of Nuclear Physics PAS in Krak\'ow and dedicated is to global studies of extremely extended cosmic-ray phenomena. The main reason for creating such a project was that the cosmic-ray ensembles (CRE) are beyond the capabilities of existing detectors and observatories. Until now, cosmic ray studies, even in major observatories, have been limited to the recording and analysis of individual air showers therefore ensembles of cosmic-rays, which may spread over a significant fraction of the Earth were neither recorded nor analyzed. In this paper the status and perspectives of the CREDO project are presented., Comment: 8 pages, 5 figures

This paper presents a complex negotiations model that has been adapted to the organisation of the process of the conclusion and execution of a contract between customer (buyer) and bidder (seller), each represented by software agents. Most research on agent-based automated negotiation is focused on models that end their action at the time at which the contract is concluded. However, the implementation of the contract can be a long process. In this time, the needs and capabilities of both sides are subject to change. In complex negotiations, the negotiation is spread over the entire lifespan of the contract and includes pre-contract negotiations as well as renegotiations during the execution of the contract. With this approach, participants can adapt dynamically to changing conditions, and can renegotiate contract conditions which have previously been concluded by both parties.

In the past few years, cosmic-rays beyond the GZK cut-off ($E > 5 \times 10^{19}$ eV) have been detected by leading collaborations such as Pierre Auger Observatory. Such observations raise many questions as to how such energies can be reached and what source can possibly produce them. Although at lower energies, mechanisms such as Fermi acceleration in supernovae front shocks seem to be favored, top-down scenarios have been proposed to explain the existence of ultra-high energy cosmic-rays: the decay of super-massive long-lived particles produced in the early Universe may yield to a flux of ultra-high energy photons. Such photons might be presently generating so called super-preshowers, an extended cosmic-ray shower with a spatial distribution that can be as wide as the Earth diameter. The Cosmic Ray Extremely Distributed Observatory (CREDO) mission is to find such events by means of a network of detectors spread around the globe. CREDO's strategy is to connect existing detectors and create a worldwide network of cosmic-ray observatories. Moreover, citizen-science constitutes an important pillar of our approach. By helping our algorithms to recognize detection patterns and by using smartphones as individual cosmic-ray detectors, non-scientists can participate in scientific discoveries and help unravel some of the deepest mysteries in physics., excited QCD Conference, CREDO Collaboration, 7 pages, 3 figures

Interactions between the microbial loop and the classical grazing food chain are essential to ecosystem ecology. The goal of the present study was to examine the impact of chironomid larvae, rotifers and copepods on the major components of the microbial food web (algae, bacteria, heterotrophic flagellates, testate amoebae and ciliates) in peatlands. Two enclosure experiments were carried out in a Sphagnum peatland. In the experiments we manipulated rotifers, copepods and macroinvertebrates, i.e. chironomid larvae (Psectrocladius sordidellus gr). During the experiments variation was observed in the abundance of potential predators. The beginning of the first experiment was distinguished by dominance of rotifers, but five days later copepods were dominant. In the second experiment copepods dominated. The results of this study are the first to suggest a substantial impact of chironomid larvae, rotifers and copepods on microorganism communities in peatland ecosystems. The impact is reflected by both a decrease in the abundance and biomass of testate amoebae and ciliates and a transformation of the size structure of bacteria. Heterotrophic flagellates (HNF) were not controlled by metazoans, but rather by testate amoebae and ciliates, as HNF were more abundant in the control treatment.

One of the major procedures for testing the geometrical accuracy of devices used in radiotherapy treatments is the test of the geometrical position of the radiation isocenter. The importance of the test reflects the fact that geometrical position of the radiation isocenter generally affects the tumor targeting. At present the geometric accuracy is assessed with the Winston-Lutz test which checks the position of an image of a ball marker with the respect to the center of the radiation field as projected on a detector plane. Obviously, determination of coordinates of a single marker is not sufficient to fully account for a complicated geometry of a therapeutic device. The purpose of the study was to design a new image analysis tool to better determine the isocenter. The proposed automated procedure for determining isocenter position uses projection data acquired for a special cube phantom. The projection images of a phantom are acquired for various angles of rotation of the gantry. A procedure is proposed to extract some geometric characteristics of a therapeutic device from the projection images.

The need for cost optimization in a broad sense constitutes the basis of opera- tion of every enterprise. In the case of IT structure (which is present in almost every field of activity these days), one of the most commonly applied technolo- gies leading to good cost-to-profit adjustment is virtualization. This allows the location of several operational systems with IT systems on a single server. In order for such an optimization to be carried out correctly, it has to be stric- tly controlled by means of allocating access to resources (which is known as performance isolation). Modern virtualizers allow us to set up this allocation in quantitative terms (the number of processors, size of RAM, or disc space). It appears, however, that in qualitative terms (processor time, RAM, or hard disc bandwidth), the actual allocation of resources does not always correspond with this configuration. This paper provides an experimental presentation of the achievable quality level of performance isolation of the Hyper-V virtualizer.