Regurgitated bodies: presenting and representing trauma in 'The Act of Killing'

Focusing on The Act of Killing, this chapter examines how an “ethics of realism” operates on three key cinematic arenas: genre, authorship and spectatorship. As far as genre is concerned, the film’s realist commitment emerges from where it is least expected, namely from Hollywood genres, such as the musical, the film noir and the western, which are used as documentary, that is to say, as a fantasy realm where perpetrators can confess to their crimes without restraints or fear of punishment, but which nonetheless retains the evidentiary weight of the audiovisual medium. Authorship, in turn, translates as Oppenheimer’s unmistakable auteur signature through his role of self-confessed “infiltrator” who disguises as a sympathiser of the criminals in order to gain first-hand access to the full picture of their acts. One of them, the protagonist Anwar Congo, is clearly affected by post-traumatic stress disorder, and his repetitive reliving of his killings is made to flare up in front of the camera so as to bring back the dead to the present time in their material reality, through his own body, including a harrowing scene of the actor’s unpredictable and uncontrollable retching as he re-enacts the killing of his victims through strangulation. Finally, in the realm of spectatorship, the usual process of illusionistic identification on the part of the spectator is turned onto its head by means of disguising these criminals as amateur filmmakers, led to shoot, act within, and then watch their own film within the film so as to force them to experience beyond any illusion the suffering they had caused.

Postnatal fluoxetine treatment affects the development of serotonergic neurons in rats

The goal of the present study was to investigate morphological changes in the serotonergic neurons/terminals in the dorsal (DR) and median (MnR) raphe nuclei and on the hippocampal dentate gyrus (DG) in neonatal rats treated from the 1st to the 21st postnatal day with fluoxetine (10 mg/kg sc, daily) or drug vehicle (0 9% saline 1 ml/kg). The results show that postnatal chronic treatment with fluoxetine promoted. (1) a smaller body weight increase during the pre-weaning period; (2) smaller number of 5-HT neurons in the DR, (3) smaller 5-HT neuronal cell bodies (area, perimeter and diameter) in the DR and the MnR and (4) diminished serotonergic terminals in the DG. These data suggest that the development of the serotonergic system was impaired and that early exposure to fluoxetine damaged the morphology of 5-HT neurons in young adult rats While these findings are consistent with other work, more studies are needed to better clarify the effects of postnatal chronic treatment with fluoxetine on the serotonergic system and, consequently, on the functions modulated by serotonin (C) 2010 Elsevier Ireland Ltd All rights reserved

Identification of non-zein proteins in BR473 maize protein bodies by LC-nanoESI-MS/MS

The nutritional value of maize seed is limited due to its high content of storage proteins (zeins), which are deficient in essential amino acids such as lysine and tryptophan. In a previous paper, we showed that protein bodies obtained from BR473 maize variety, developed by Embrapa (Brazilian Agricultural Research Corporation), were mainly constituted by Z27 and a smaller quantity of Z50 gamma-zeins. Besides zein proteins, other not identified protein band in the SDS/PAGE was also observed, which could indicate the presence of non-zein proteins additionally to gamma-zeins. In the present paper, we have demonstrated the presence of non-zein proteins in BR473 maize protein bodies by LC-nanoESI-MS/MS and database searching. This fact could be related to the excellent energetic value and higher protein quality of BR473 maize grains, since high lysine concentration in some maize varieties has been related to the presence of cytoskeleton proteins that are non-zeins. We have identified the following proteins: Brittle-1 protein (chloroplast precursor), Legumin-1, glyceroldehyde-3-phosphate dehydrogenase, and elongation factor 1-alpha.

Solving the Vehicle Routing Problem with Genetic ALgorithm and Simulated Annealing

This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.

The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Materialising bodies : there is nothing more material than a socially constructed body.

Over the last one of two decades, researchers within the physical education (PE) and sport pedagogy research frequently use the concept ‘the material body’. An initial purpose of this article is to explore what a concept of a ‘material body’ might mean. What other bodies are there? Who would dispute the materiality of bodies? I suggest that the use of a concept as ‘the material body’ suggests a hesitation before the radicalism of the linguistic turn in the sense that the concept ‘discourse’ does not include a material dimension. In this way ‘the material body’ relates to an interpretation of ‘the socially (or discursively) constructed body’ as void of matter. A further purpose with the article is to re-inscribe matter in the concept of ‘discourse’. This is done by way of discussing what theorists like Michel Foucault and, in particular, Judith Butler, has to say about the materiality of the body. In their writings, discourse should not be limited to spoken and/or written language. Rather, discourse is understood in terms of actions and events that create meanings—that matters. One conclusion of the article is that it is important to problematise the mundane view of discourse as ‘verbal interchange’ because it reinforces the promise of an objective knowledge that will eventually shed light on the ‘real’ body and the mysteries of sexual difference, what its origins are, what causes it. Another conclusion is that the PE and sport pedagogy research should pay less attention to the body as an object (what it ‘is’), and pay more attention to how the body matters, and e.g. how movements make bodies matter.

Speed prediction for triggering vehicle activated signs

Accurate speed prediction is a crucial step in the development of a dynamic vehcile activated sign (VAS). A previous study showed that the optimal trigger speed of such signs will need to be pre-determined according to the nature of the site and to the traffic conditions. The objective of this paper is to find an accurate predictive model based on historical traffic speed data to derive the optimal trigger speed for such signs. Adaptive neuro fuzzy (ANFIS), classification and regression tree (CART) and random forest (RF) were developed to predict one step ahead speed during all times of the day. The developed models were evaluated and compared to the results obtained from artificial neural network (ANN), multiple linear regression (MLR) and naïve prediction using traffic speed data collected at four sites located in Sweden. The data were aggregated into two periods, a short term period (5-min) and a long term period (1-hour). The results of this study showed that using RF is a promising method for predicting mean speed in the two proposed periods.. It is concluded that in terms of performance and computational complexity, a simplistic input features to the predicitive model gave a marked increase in the response time of the model whilse still delivering a low prediction error.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Review of the effectiveness of vehicle activated signs

This paper reviews the effectiveness of vehicle activated signs. Vehicle activated signs are being reportedly used in recent years to display dynamic information to road users on an individual basis in order to give a warning or inform about a specific event. Vehicle activated signs are triggered individually by vehicles when a certain criteria is met. An example of such criteria is to trigger a speed limit sign when the driver exceeds a pre-set threshold speed. The preset threshold is usually set to a constant value which is often equal, or relative, to the speed limit on a particular road segment. This review examines in detail the basis for the configuration of the existing sign types in previous studies and explores the relation between the configuration of the sign and their impact on driver behavior and sign efficiency. Most of previous studies showed that these signs have significant impact on driver behavior, traffic safety and traffic efficiency. In most cases the signs deployed have yielded reductions in mean speeds, in speed variation and in longer headways. However most experiments reported within the area were performed with the signs set to a certain static configuration within applicable conditions. Since some of the aforementioned factors are dynamic in nature, it is felt that the configurations of these signs were thus not carefully considered by previous researchers and there is no clear statement in the previous studies describing the relationship between the trigger value and its consequences under different conditions. Bearing in mind that different designs of vehicle activated signs can give a different impact under certain conditions of road, traffic and weather conditions the current work suggests that variable speed thresholds should be considered instead.

Data based Calibration System for Radar used by Vehicle Activated Signs

The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Fire Incidences, Water Bodies, and Population in Maine

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Moose-vehicle collisions (MVC) in the State of Maine from 1992-2004

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