Introduction:navigating secrecy in security research

This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book offers a rich set of analyses of the challenges of secrecy in security research, and sets out practical ways to navigate, encircle and work with secrecy. It aims to offer not just a conceptual reflection on the dynamics of secrecy, but also practical, hands-on methodological guidance for qualitative fieldwork in the security domain. The book describes new ways of conceptualising secrecy in relation to fieldwork, by understanding secrecy as more than a barrier to be overcome. It shows how secrecy itself can be made productive to the analysis: mapping secrecies and sensitivities in the field can itself be revealing; navigating obfuscation is co-productive of research design and data. The book focuses on reconceptualising secrecy as a complex practice and mode of power

Effects of GM potato Modena on soil microbial activity and litter decomposition fall within the range of effects found for two conventional cultivars

Plant roots have a profound effect on soil microbial activity, particularly in the rhizosphere. Hence, it is important to understand the potential effects of genetically modified (GM) crops on soil microbial activity and related processes such as litter decomposition. In this study, we compared the effects of GM potato Modena on soil microbial activity and carbon (C) and nitrogen (N) mineralization to effects induced by Modena’s parental isoline (Karnico) and a conventional potato cultivar (Aventra). A field experiment was conducted at two sites to assess microbial catabolic diversity (using MicroRespTM) in the rhizosphere and in bulk soil, during flowering and senescence of the potato plants. In a laboratory experiment with soil and potato litter from the field experiment, we investigated whether the cultivars had modified the activity of soil microbial communities to such an extent that this affected C and N mineralization. Results of the field experiment showed no GM-induced effects on microbial catabolic diversity, while effects of field site location and sampling date were significant. Multivariate analysis including plant traits and soil characteristics revealed that microbial catabolic activities in rhizosphere soil were strongly correlated with soil organic matter and tuber sucrose content, whereas in bulk soil, they were primarily correlated with soil moisture. In the laboratory experiment, we found that Modena induced a "home-field advantage" in N mineralization, yet this effect was inconsistent across locations and was also observed for other cultivars. Based on our data and results from previous studies, we conclude that the effects of GM cultivar Modena on soil microbial activity and litter decomposition fall within the normal range of effects found for conventional potato cultivars

Формалізація основних принципів взаємодії інвестора (кредитора) та позичальника (господарюючого суб’єкта)

Здійснено аналіз питань пов’язаних з організацією раціонального інвестування як з точки зору позичальника (господарюючого суб’єкта) так і з точки зору інвестора (кредитора). Проблему узгодження інтересів інвестора та позичальника сформульовано як багатокритеріальну задачу математичного програмування. Запропонована формалізація взаємодії господарюючого суб’єкта та інвестора за допомогою дослідження дискретного Марковського процесу, стани якого задаються вектором інтегральних показників діяльності кредитора та позичальника.This work comprises the rational investment organizationrelated issues analysis from the borrower’s (managing entity), as well as from the investor’s (creditor’s) point of view. The borrower and investor’s interests’ coordination issue is formulated as a mathematical programming multicriterion problem. The borrower and investor cooperation formalization with help of discreet Markov’s process study is introduced. The Markov’s process’ states are determined by the investor and borrower’s integral activities’ rates vector

Entropies of the EEG: The effects of general anaesthesia

The aim of this paper was to compare the performance of different entropy estimators when applied to EEG data taken from patients during routine induction of general anesthesia. The question then arose as to how and why different EEG patterns could affect the different estimators. Therefore we also compared how the different entropy estimators responded to artificially generated signals with predetermined, known, characteristics. This was done by applying the entropy algorithms to pseudoEEG data: (1) computer-generated using a second-order autoregressive (AR2) model, (2) computer-generated white noise added to step signals simulating blink and eyemovement artifacts and, (3) seeing the effect of exogenous (computer-generated) sine-wave oscillations added to the actual clinically-derived EEG data set from patients undergoing induction of anesthesia