This agenda-setting series of research monographs, now more than a decade old, provides an interdisciplinary forum aimed at advancing innovative new agendas for approaches to, and understandings of, peace and conflict studies and International Relations. Many of the critical volumes the series has so far hosted have contributed to new avenues of analysis directly or indirectly related to the search for positive, emancipatory, and hybrid forms of peace. New perspectives on peacemaking in practice and in theory, their implications for the international peace architecture, and different conflict-affected regions around the world, remain crucial. This series' contributions offers both theoretical and empirical insights into many of the world's most intractable conflicts and any subsequent attempts to build a new and more sustainable peace, responsive to the needs and norms of those who are its subjects.More information about this series at

Sensory uncertainties and imperfections in motor control play important roles in neural control and Bayesian approaches to neural encoding. However, it is difficult to estimate these uncertainties experimentally. Here, we show that magnitude of the uncertainties during the generation of motor control force can be measured for a virtual stick balancing task by varying the feedback delay, τ. It is shown that the shortest stick length that human subjects are able to balance is proportional to τ 2. The proportionality constant can be related to a combined effect of the sensory uncertainties and the error in the realization of the control force, based on a delayed proportional-derivative (PD) feedback model of the balancing task. The neural reaction delay of the human subjects was measured by standard reaction time tests and by visual blank-out tests. Experimental observations provide an estimate for the upper boundary of the average sensorimotor uncertainty associated either with angular position or with angular velocity. Comparison of balancing trials with 27 human subjects to the delayed PD model suggests that the average uncertainty in the control force associated purely with the angular position is at most 14% while that associated purely with the angular velocity is at most 40%. In the general case when both uncertainties are present, the calculations suggest that the allowed uncertainty in angular velocity will always be greater than that in angular position.

A virtual stick balancing environment is developed using a computer mouse as input device. The development process is presented both on the hardware and software level. Two possible concepts are suggested to obtain the acceleration of the input device: discrete differentiation of the cursor position measured in pixels on the screen and by direct measurements via an Inertial Measurement Unit (IMU). The comparison of the inputs is carried out with test measurements using a crank mechanism. The measured signals are compared to the prescribed motion of the mechanism and it is shown that the IMU-based input signal fits better to the prescribed motion than the pixel-based input signal. The pixel-based input can also be applied after additional filtering, but this presents an extra computational delay in the feedback loop.

Particle size distribution (PSD) is one of the most important fundamental physical properties of soils, as it determines their physical, chemical, mechanical, geotechnical, moreover environmental behaviour. Although the measurement of PSD with different techniques is commonly performed in soil laboratories, their automation and continuous PSD curve generation have not been solved yet.  However, there are some physical principles, various sensors and different data storing methods for measuring the density-time function. In the present paper a possible solution is introduced for the measurement of the soil particle density database as a function of settling time. The equipment used for this purpose is an areometer that is widely used e.g. for determining the sugar content of must, or the alcohol content of distilled spirits, etc. The device is equipped with patent pending capacitive sensors on the neck of the areometer. It measures the changes in the water levels nearby the neck of the areometer in 1 μm units with <10 μm accuracy. The typical water level changes are 3-5 cm, which makes possible a very accurate determination of particle density changes due to settling in particle size analysis. The measured signals are stored in the equipment's memory and can be downloaded to the controller computer via a modified USB port. Data evaluation can be carried out online or later. The large number of measured data points led to the introduction of a new evaluation method, the Method of FInite Tangents or shortly the “FIT Method”. The dispersed soil particle system is considered as the aggregation of many mono-disperse systems. From this it follows that the measured density-time function can be divided into grain size fractions with tangent lines drawn to finite, but optional points. These tangent lines are suitable for calculating the settling speed of a given fraction, as the changing speed of density is equal to the multiplication of settling speed and mass of the given grain size fraction. The settling speed of all fractions is calculable by using the Stokes law, so the mass of all of the floating fraction can be calculated. Because the soil suspension is a poly-disperse system, the measured density decrease can be considered as an integration of finite mono-disperse systems. From this, it follows that it can be interpreted as the sum of linear density vs. time functions. If the mass of each grain size fraction is known, the particle size distribution is calculable. The method is relatively easily programmed and the intervals of grain size fractions are freely adjustable, so with this program almost all types of particle size distribution are calculable, not only those being uniform. Using the appropriate controller and evaluation program, soil particle size distribution can be calculated immediately after downloading the measured data. This technique does not need more sample preparation than past methods. The automated reading lessens the manpower required for performing the measurement - which also reduces human error sources - and provides very detailed PSD data that has advantages, among others, like revealing multi-modality in the particle-size distribution.

The critical length that limits stabilizability for delayed proportionalderivative-acceleration (PDA) feedback and for predictor feedback (PF) is analyzed for the inverted pendulum paradigm. The aim of this work is to improve the understanding of human balancing tasks such as stick balancing on the fingertip, which can be modeled as a pendulum cart system. The relation between the critical length of the balanced stick and the reaction time delay in the presence of sensory uncertainties, which are modeled as static parameter perturbations in the control gains, is investigated rigorously. Robust stabilizability analysis is performed using the real structured stability radius. Performance is assessed by the length of the shortest pendulum (critical length) that can still be balanced for a fixed reaction delay. For both PDA feedback and PF control with delay mismatch, it is observed that the relation between the critical length and the reaction delay remains quadratic in the presence of perturbations on the control gains (of fixed size). Numerical comparison shows that predictor feedback is superior over PDA feedback in terms of critical length: shorter pendulum can be balanced by PF than by PDA feedback for the same reaction delay and for the same static parameter perturbation. Furthermore, it is found that both control concepts are more sensitive to the change in the feedback delay than on the same relative change in the parameter uncertainties. Interpretation to human balancing suggests that it is more challenging for the nervous system to cope with reaction delay than with sensory uncertainties.