A Hierarchical Attractor Network Model of perceptual versus intentional decision updates

Changes of Mind are a striking example of our ability to flexibly reverse decisions and change our own actions. Previous studies largely focused on Changes of Mind in decisions about perceptual information. Here we report reversals of decisions that require integrating multiple classes of information: 1) Perceptual evidence, 2) higher-order, voluntary intentions, and 3) motor costs. In an adapted version of the random-dot motion task, participants moved to a target that matched both the external (exogenous) evidence about dot-motion direction and a preceding internally-generated (endogenous) intention about which colour to paint the dots. Movement trajectories revealed whether and when participants changed their mind about the dot-motion direction, or additionally changed their mind about which colour to choose. Our results show that decision reversals about colour intentions are less frequent in participants with stronger intentions (Exp. 1) and when motor costs of intention pursuit are lower (Exp. 2). We further show that these findings can be explained by a hierarchical, multimodal Attractor Network Model that continuously integrates higher-order voluntary intentions with perceptual evidence and motor costs. Our model thus provides a unifying framework in which voluntary actions emerge from a dynamic combination of internal action tendencies and external environmental factors, each of which can be subject to Change of Mind

Inspection system for in use pesticide application equiupment in Greece. First three years of application

According to Directive 2009/128/EC, all member states should have inspected all in-use Pesticide Application Equipment (PAE) by November 2016. In Greece, Law 4036/2012 embodied the provisions of this Directive into Greek legislation, but unfortunately due to various reasons, the inspections were significantly delayed. Aim of the current study is to briefly present the inspection system of in-use PAE that was developed due to the aforementioned law and then provide the statistical results of the inspections until February 2018. The progress of the last two years was significant, but a lot of work remains to make the inspection system functional and unproblematic.According to Directive 2009/128/EC, all member states should have inspected all in-use Pesticide Application Equipment (PAE) by November 2016. In Greece, Law 4036/2012 embodied the provisions of this Directive into Greek legislation, but unfortunately due to various reasons, the inspections were significantly delayed. Aim of the current study is to briefly present the inspection system of in-use PAE that was developed due to the aforementioned law and then provide the statistical results of the inspections until February 2018. The progress of the last two years was significant, but a lot of work remains to make the inspection system functional and unproblematic

A virus-evolutionary, multi-objective intelligent tool path optimisation methodology for sculptured surface CNC machining

Today’s production environment faces multiple challenges involving fast adaptation to modern technologies, flexibility in accommodating them to current industrial practices and cost reduction through automating repetitive tasks. At the same time the requirements for manufacturing functional, aesthetic and versatile products, turn these challenges to clear and present industrial problems that need to be solved by delivering at least semi-optimal results. Even though sculptured surfaces can meet such requirements when it comes to product design, a critical problem exists in terms of their machining operations owing to their arbitrary nature and complex geometrical features as opposed to prismatic surfaces. Current approaches for generating tool paths in computer-aided manufacturing (CAM) systems are still based on human intervention as well as trial-and-error experiments. These approaches neither can provide optimal tool paths nor can they establish a generic approach for an advantageous and profitable sculptured surface machining (SSM). Major goal of this PhD thesis is the development of an intelligent, automated and generic methodology for generating optimal 5-axis CNC tool paths to machine complex sculptured surfaces. The methodology considers the tool path parameters “cutting tool”, “stepover”, “lead angle”, “tilt angle” and “maximum discretisation step” as the independent variables for optimisation whilst the mean machining error, its mean distribution on the sculptured surface and the minimum number of tool positions are the crucial optimisation criteria formulating the generalized multi-objective sculptured surface CNC machining optimisation problem. The methodology is a two-fold programming framework comprising a virus-evolutionary genetic algorithm as the methodology’s intelligent part for performing the multi-objective optimisation and an automation function for driving the algorithm through its argument-passing elements directly related to CAM software, i.e., tool path computation utilities, objects for programmatically retrieving tool path parameters’ inputs, etc. These two modules (the intelligent algorithm and the automation function) interact and exchange information as needed towards the achievement of creating globally optimal tool paths for any sculptured surface. The methodology has been validated through simulation experiments and actual machining operations conducted to benchmark sculptured surfaces and corresponding results have been compared to those available from already existing tool path generation/optimisation approaches in the literature. The results have proven the methodology’s practical merits as well as its effectiveness for maintaining quality and productivity in sculptured surface 5-axis CNC machining

Precision sculptured surface CNC machining using cutter location data

Industrial parts with sculptured surfaces are typically, manufactured with the use of CNC machining technology and CAM software to generate surface tool paths. To assess tool paths computed for 3-and 5-axis machining, the machining error is evaluated in advance referring to the parameter controlling the linearization of high-order curves, as well as the scallop yielded as a function of radial cutting engagement parameter. The two parameters responsible for the machining error are modeled and corresponding cutter location data for tool paths are utilized to compare actual trajectories with theoretical curves on a sculptured surface assessing thus the deviation when virtual tools are employed to maintain low cost; whilst ensuring high precision cutting. This operation is supported by applying a flexible automation code capable of computing the tool path; extracting its CL data; importing them to the CAD part and finally projecting them onto the part’s surface. For a given tolerance, heights from projected instances are computed for tool paths created by changing the parameters under a cutting strategy, towards the identification of the optimum tool path. To represent a global solution rough machining is also discussed prior to finish machining where the new proposals are mainly applied.</jats:p

Regional cerebral blood flow and cellular environment in subarachnoid hemorrhage: A thermal doppler flowmetry and microdialysis study

Background Cerebral microdialysis enables assessment of regional metabolic physiology and provides biomarkers for clinical correlation in critical conditions, such as subarachnoid hemorrhage (SAH). The aim of our current study was to investigate the correlation between regional cerebral blood flow and microdialysis parameters (glucose, lactate, glycerol, pyruvate concentrations, and lactate/pyruvate metabolic ratio) in patients with SAH. Materials and methods Twenty-one patients with SAH were enrolled in our retrospective study. Cerebral blood flow (CBF) based on thermal diffusion methodology, the thermal coefficient K, and microdialysis biochemical markers were recorded. The duration of the brain monitoring was 10 days. Results Microdialysis glucose concentration was inversely related to the cerebral temperature and to the L/P ratio. Furthermore, it was positively correlated to all other microdialysis parameters but glycerol. The K coefficient was strongly and positively correlated with the temperature and marginally with the CBF. The L/P ratio was positively correlated with glycerol, while it was inversely correlated with the CBF. Patients who died had elevated L/P ratio and K coefficient compared to the survivors in our series. Conclusions Thermal conductivity coefficient may change over time as cerebral injury progresses and tissue properties alter. These alterations were found to be associated with the microdialysis metabolite concentrations and the CBF itself. The microdialysis biochemical indices of cell stress and death (glycerol, L/P ratio) were positively related to each other, while the measured L/P metabolic ratio was higher among patients who died

Nitrogen replenishment using variable rate application technique in a small hand-harvested pear orchard

Precision agriculture is a management approach for sustainable agriculture. It can be applied even in small fields. It aims to optimize inputs, improve profits, and reduce adverse environmental impacts. In this study, a series of measurements were conducted over three growing seasons to assess variability in a 0.55 ha pear orchard located in central Greece. Soil ECa was measured using EM38 sensor, while soil samples were taken from a grid 17 × 8 m and analysed for texture, pH, P, K, Mg, CaCO3, and organic matter content. Data analysis indicated that most of the nutrients were at sufficient levels. Soil and yield maps showed considerable variability while fruit quality presented small variations across the orchard. Yield fluctuations were observed, possibly due to climatic conditions. Prescription maps were developed for nitrogen variable rate application (VRA) for two years based on the replacement of the nutrients removed by the crop. VRA application resulted in 56% and 50% reduction of N fertiliser compared to uniform application

Intelligent dual curve-driven tool path optimization and virtual CMM inspection for sculptured surface CNC machining

This paper investigates the profitability of a dual‐curve driven surface finish tool path under the concept of optimizing crucial machining parameters such as toroidal end‐mill diameter, lead angle and tilt angle. Surface machining error as well as tool path time are treated as optimization objectives under a multi‐criteria sense, whilst a central composite design is conducted to obtain experimental outputs for examination and, finally, fit a full quadratic model considered as the fitness function for process optimization by means of a genetic algorithm. A benchmark sculptured surface given as a second‐order parametric equation was tested and simulated using a cutting‐edge manufacturing modeling software and best parameters recommended by the genetic algorithm were implemented for validation. Further assessment involves the virtual inspection to selected profile sections on the part. It was shown that the approach can produce dual‐curve driven tool trajectories capable of eliminating sharp scallop heights, maximizing machining strip widths as well as maintaining smoothness quality and machining efficiency

Fossil Fuel Deficit-Conservation Tillage and on Farm Biofuel Production to Cope With the Problem

Abstract The limited resources of fossil fuels along with the highly fluctuating prices, call for investigation to find diesel alternatives. Biofuels from vegetable oils, seems the easiest accessible substitutes as they can be used in conventional diesel engines without lot of modifications. There are though two mainstream attitudes on this approach. The one points that it is immoral to divert environmental resources from food production to energy production when the global population increases and the other claims that without mechanization and fuel to power it, food production will finally be decreased. Conservation tillage adoption may contribute in significant fuel savings by eliminating tillage operations. If they would be combined with on farm biofuel production, they would certainly require less land to be devoted for this purpose. In the present work, based on data of a long term tillage experiment, it was calculated the percentage of land that would be required to cultivate with a biofuel crop (sunflower for instance) in order to cover the fuel requirements of an arable farm, for three alternative tillage methods: conventional (CT), reduced (RT) and no-tillage (NT). The results indicated that in CT, the 11% of the land would be enough to provide the biofuel for all the field operations (except irrigation). In RT, due to lower fuel consumption, the 7.5% of the land would be sufficient. That means that a 3.6% yield reduction is justified. In NT, only the 3.5% of the land is required to produce the biofuels justifying a 7.7% yield reduction. This sets the limits of yield reduction that can be acceptable. However we have to add in this balance the environmental effects of using conservation tillage like erosion reduction, increasing soil organic matter and biodiversity maintenance