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A 2D imaging instrument has been designed and deployed on C-2W (“Norman”) [H. Gota et al., Nucl. Fusion 61, 106039 (2021)] to study the plasma in the expander divertor by simultaneously measuring three neutral helium spectral lines. Ratios of these images, in conjunction with a collisional-radiative model, yield 2D maps of electron temperature and density. Almost the entire radial plasma cross-section (∼60 cm) can be mapped with a spatial resolution ≲1 cm. These data can, in principle, be acquired at 3 kHz. The neutral helium target is provided by a custom-built supersonic gas injector located inside the divertor vessel, which injects helium toward the magnetic axis and perpendicular to the camera sight-cone. Images of helium emission and reconstructed electron density and temperature profiles of the plasma produced from an end gun are presented. Voltages applied to concentric annular electrodes located in the divertors are used to stabilize beam-driven field reversed configuration plasmas. Magnetic field expansion is also employed to thermally isolate electrons from the end electrodes. Measurements of electron temperature and density in the divertor are important in order to study the effects of both the electrostatic biasing and the divertor magnetic field on electron confinement, neutral gas transport, and the overall machine performance.

In order to measure the fast ion using neutral particle analyzers (NPAs) in the low neutral density core region of a magnetic confinement fusion device, active change exchange measurements are often performed using a neutral beam (NB) as a charge-exchange (CX) target. One of the complications with this approach is that an NB injected as a CX target can also contribute to the total fast ion source. C-2W has a unique solution to this difficulty in that it is equipped with both eight NB injectors, which can inject beams of different particle species, and an electro-magnetic NPA (EM-NPA), which can measure multiple ion species simultaneously. This enables the active and passive fast ion CX components to be clearly distinguished. The decrease in amplitude of the CX spectra when a hydrogen NB is terminated was clearly observed by the EM-NPA in both hydrogen and deuterium channels. This reduction of observed fast ion flux was mainly caused by the diminished fast ion source, not crosstalk or a general reduction in fast ion confinement. As an example application of this technique on C-2W, fast ion behavior during a periodic density drop is explored. The large difference between the active and passive CX components of the EM-NPA signals clearly demonstrates the usefulness of the active fast ion CX measurement.

A necessary reduction in climate impact and raised interest in the self-sufficiency of food in Sweden serve as the major background for the study. The purpose was to examine whether conversion of Swedish agriculture following principles of Ecological Recycling Agriculture (ERA) could be a realistic alternative. Case studies of 22 ERA farms were performed, and results were presented for five production groups in kg production, carbon sequestration, and nutrient balance per hectare. The farms show climate impact substantially lower than Swedish average agriculture, through 85% lower commodity purchases and 2.3 times larger carbon sequestration due to more ley cropping. Target diets with varying amounts of meat and dairy products were defined and matched with the production and presented in scenarios where the farms’ staple food production is upscaled for a Swedish population of 11 million inhabitants. Results are presented in kg of food category produced, hectares of arable land, CO2 equivalents, and kg of N surplus per capita. The scenario results show that it is possible to achieve at least a 90% decrease in climate impact. It is concluded that it is within range for Sweden to be self-sufficient in staple foods based on the available acreage of arable land by adopting Ecological Recycling Agricultural principles in a similar manner as the studied farms.

Many imaging systems can be approximately described by a linear operator that maps an object property to a collection of discrete measurements. However, even in the absence of measurement noise, such operators are generally “blind” to certain components of the object, and hence information is lost in the imaging process. Mathematically, this is explained by the fact that the imaging operator can possess a null space. All objects in the null space, by definition, are mapped to a collection of identically zero measurements and are hence invisible to the imaging system. As such, characterizing the null space of an imaging operator is of fundamental importance when comparing and/or designing imaging systems. A characterization of the null space can also facilitate the design of regularization strategies for image reconstruction methods. Characterizing the null space via an associated projection operator is, in general, a computationally demanding task. In this tutorial, computational procedures for establishing projection operators that map an object to the null space of a discrete-to-discrete imaging operator are surveyed. A new machine-learning-based approach that employs a linear autoencoder is also presented. The procedures are demonstrated by use of biomedical imaging examples, and their computational complexities and memory requirements are compared.

This article explores processes of place-making through the study of the linguistic landscape of a small-size town in Northern Sweden. The analysis of signs is used as a tool for examining the role and visibility of actors in the landscape. For this purpose, we examine who the authors are, what forms of multilingualism can be observed, and who has agency in the place-making of the public space. Our documentation consists of photos and fieldnotes from observations, encounters, and conversations with people during ethnographic fieldwork in 2019. Using a mixed-methods approach, all signs were first analysed quantitatively according to the categories of authors and function. Regression analysis was used to explore correlations between the categories. Secondly, multilingual signs were analysed qualitatively regarding their function and purpose in relation to their contexts. Our results illustrate a city centre with a strong presence of the Swedish language. Multilingual signs target specific groups and are intended for information, advertisement, rules and regulations; moreover, our findings indicate that the opportunities for private actors to influence the linguistic landscape are limited. The form of multilingualism in this context—visible multilingualism present mainly through English—is different from the one we can see in the socio-demographic data.

Virtual reality, VR, has become more popular in the last decade thanks to the rapid development of the technology, and thanks to becoming more accessible. One of the demands that users have is that the VR experience should be immersive, which means that the computer-generated world should be perceived as if it was real. This is achieved by taking all senses into account. In addition to the visual impression, the sound is essential and contributes information to the user. When locating audio sources, a three-dimensional sound image is necessary. A part of the localization includes estimating the distance to the audio source. Our perception of distance is based upon two impressions, the volume and the relationship between direct and diffuse sound. The direct sound is the sound that reaches the listener directly, and the diffuse sound is the sound that arrives at the listener after being reflected against the surroundings [4]. This study aims to explore how the relationship between direct and diffuse sound affects the perception of distance to audio sources in VR. The study consisted of two phases: A design phase for building the test environment and a test phase where physical tests were conducted. The test environment was built in Unity and consisted of four scenes, two of which were for educational purposes and two for test purposes. It was also analyzed whether any previous experience of VR or playing an instrument affected the result. No evident trends could be seen in the results, and therefore no conclusions could be drawn from the study. Noticeable from the data was that the answers became more extreme when the reverberation was increased. And that the answers were more evenly distributed when the reverberation was reduced. It was also noted that the reverberation affected the participants' perception of space more than the perception of distance. The most prominent reasons for the vague result are believed to be that the study group was too small and that the test was too difficult. Another factor that impacted the result was the software used. Although no conclusions could be drawn from this study, it will continue to be interesting to investigate further what can affect the perception of distance in VR. Virtuell verklighet, VR, har blivit mer och mer populärt under det senaste årtiondet tack vare att tekniken utvecklats och tack vare att den har blivit mer tillgänglig. Ett av de största kraven som användarna ställer på VR-upplevelsen är att den ska vara omslutande, vilket innebär att den datorgenererade världen ska uppfattas som om den var verklig. För att det ska uppnås måste alla sinnen tas i beaktning. Förutom synintrycket, är ljudupplevelsen ett viktigt stimuli som bidrar med information till användaren. För att kunna lokalisera ljudkällor är en tredimensionell ljudbild nödvändig. En del av lokaliseringen innefattar att uppskatta avståndet till ljudkällan. Vår avståndsuppfattning bygger på två intryck, ljudstyrkan och förhållandet mellan direkt och diffust ljud. Det direkta ljudet är det ljud som når lyssnaren direkt och det diffusa ljudet är det som når lyssnaren efter att ha reflekterats mot omgivningen [4]. Syftet med denna studie är att undersöka hur förhållandet mellan direkt och diffust ljud påverkar avståndsuppfattningen till ljudkällor i VR. Studien har bestått av två faser: En designfas där testmiljön byggdes, och en testfas där det utfördes fysiska tester på deltagarna. Testmiljön byggdes i Unity och bestod av fyra scener, varav två var i utbildande syfte och de andra två utgjorde testet. Det analyserades även om tidigare erfarenhet av VR eller instrumentspelande hade någon påverkan på resultatet. Det gick inte att se några tydliga trender i resultatet och därav kan inga slutsatser dras av undersökningen. Det mest utmärkande i datan var att svaren blev mer extrema vid ökad efterklang och mer jämt fördelade vid minskad efterklang. Det noterades att efterklangen påverkade deltagarnas rumsuppfattning mer än uppfattningen om avståndet till ljudkällan. De mest framträdande anledningarna till det vaga resultatet tros vara att studiegruppen var för liten och att testet var för svårt. Den använda programvaran har även haft påverkan på utfallet. Trots att inga slutsatser kunde dras så är det fortsatt intressant att undersöka vad som kan påverka avståndsuppfattningen i VR.

Purpose: Deep learning-based image super-resolution (DL-SR) has shown great promise in medical imaging applications. To date, most of the proposed methods for DL-SR have only been assessed using traditional measures of image quality (IQ) that are commonly employed in the field of computer vision. However, the impact of these methods on objective measures of IQ that are relevant to medical imaging tasks remains largely unexplored. We investigate the impact of DL-SR methods on binary signal detection performance. Approach: Two popular DL-SR methods, the super-resolution convolutional neural network and the super-resolution generative adversarial network, were trained using simulated medical image data. Binary signal-known-exactly with background-known-statistically and signal-known-statistically with background-known-statistically detection tasks were formulated. Numerical observers (NOs), which included a neural network-approximated ideal observer and common linear NOs, were employed to assess the impact of DL-SR on task performance. The impact of the complexity of the DL-SR network architectures on task performance was quantified. In addition, the utility of DL-SR for improving the task performance of suboptimal observers was investigated. Results: Our numerical experiments confirmed that, as expected, DL-SR improved traditional measures of IQ. However, for many of the study designs considered, the DL-SR methods provided little or no improvement in task performance and even degraded it. It was observed that DL-SR improved the task performance of suboptimal observers under certain conditions. Conclusions: Our study highlights the urgent need for the objective assessment of DL-SR methods and suggests avenues for improving their efficacy in medical imaging applications.

The C-2W device (“Norman”) [Gota et al., Nucl. Fusion 59, 112009 (2019)] has produced and sustained beam-driven field-reversed configuration (FRC) plasmas embedded in a magnetic mirror geometry using neutral beams and end-bias electrodes located in expander divertors. Several discrete vessels comprise this device, and many imaging instruments are required in order to view the plasma throughout. To meet this need, a suite of spatially and radiometrically calibrated, high-speed camera systems have been deployed. Besides global visualization of the plasma evolution and macro-stability, this imaging suite has been used in a variety of applications. One example application is a tomographic reconstruction of passive impurity emission. Calculation of the magnetic field in the equilibrium vessel is complicated by eddy currents in conducting structures and internal currents in the high-β FRC plasma. In addition, thus far non-perturbative measurements of internal field have not been available. The tomographic reconstruction of O4+ impurity emission enables an independent visualization of the plasma geometry, serving as a check on magnetic modeling and indirect evidence for field reversal within the FRC. A second application uses the cameras to view the Balmer-α emission throughout the plasma in order to estimate the ionization rate in each region. These rates can then be incorporated into particle balance calculations and a circuit model for currents from the end-bias electrodes. Finally, arcing on the electrode surfaces is identified through automated image processing of carefully selected spectral line emission.

The article presents a new language learner corpus for Swedish, SweLL, and the methodology from collection and pesudonymisation to protect personal information of learners to annotation adapted to second language learning. The main aim is to deliver a well-annotated corpus of essays written by second language learners of Swedish and make it available for research through a browsable environment. To that end, a new annotation tool and a new project management tool have been implemented, – both with the main purpose to ensure reliability and quality of the final corpus. In the article we discuss reasoning behind metadata selection, principles of gold corpus compilation and argue for separation of normalization from correction annotation.

Generative adversarial networks (GANs) have proven useful for several medical imaging tasks, including image reconstruction and stochastic object model generation. Thus far, most of the work with GANs has been constrained to twodimensional images. Considering that medical imaging data are often inherently three-dimensional (3D), a 3D GAN would be a more principled way to synthesize realistic volumes. Training a 3D GAN is both computationally and memory intensive. However, prior work has not considered the anisotropic nature of many medical imaging systems. In this paper, the SlabGAN is proposed to reduce the inefficiencies associated with training a 3D GAN. The SlabGAN uses the progressive GAN architecture extended to 3D, but removes the requirement of the three dimensions being equal sizes. This permits the generation of anisotropic 3D volumes with large x and y dimensions. The SlabGAN is trained on MRI brain images from the fastMRI dataset to generate images of dimension 256×256×16. The x and y dimensions of these images are comparable to previously published results while requiring significantly fewer computational resources to generate. The trained SlabGAN is applicable to tasks such as 3D medical image reconstruction and thin-slice MR super resolution.

In medical imaging, it is sometimes desirable to acquire high resolution images that reveal anatomical and physiological information to support clinical practice such as diagnosis and image-guided therapies. However, for certain imaging modalities (i.e., magnetic resonance imaging (MRI)), acquiring high resolution images can be a very time-consuming and resource-intensive process. One popular solution recently developed is to create a high resolution version of the acquired low-resolution image by use of deep image super-resolution (DL-SR) methods. It has been demonstrated in literature that deep super-resolution networks can improve the image quality measured by traditional physical metrics such as mean square error (MSE), structural similarity index metric (SSIM) and peak signal-to-noise ratio (PSNR). However, it is not clear how well these metrics quantify the diagnostic value of the generated SR images. Here, a task-based super-resolution (SR) image quality assessment is conducted to quantitatively evaluate the efficiency and performance of DL-SR methods. A Rayleigh task is designed to investigate the impact of signal length and super-resolution network complexity on s binary detection performance. Numerical observers (NOs) including the regularized Hotelling Observer (RHO), the anthropomorphic Gabor channelized observers (Gabor CHO) and the ResNet-approximated ideal observer (ResNet-IO) are implemented to assess the Rayleigh task performance. For the datasets considered in this study, little to no improvement in task performance of the considered NOs due to the considered DL-SR SR networks, despite substantial improvement in traditional IQ metrics.

Image reconstruction algorithms seek to reconstruct a sought-after object from a collection of measurements. However, complete measurements such that an object can be uniquely reconstructed are seldom available. Analysis of the null components of the imaging system can guide both physical design of the imaging system and algorithmic design of reconstruction algorithms to more closely reconstruct the true object. Characterizing the null space of an imaging operator is a computationally demanding task. While computationally efficient methods have been proposed to iteratively estimate the null space components of a single or a small number of images, full characterization of the null space remains intractable for large images using existing methods. This work proposes a novel learning-based framework for constructing a null space projection operator of linear imaging operators utilizing an artificial neural network autoencoder. To illustrate the approach, a stylized 2D accelerated MRI reconstruction problem (for which an analytical representation of the null space is known) was considered. The proposed method was compared to state-of-the-art randomized linear algebra techniques in terms of accuracy, computational cost, and memory requirements. Numerical results show that the proposed framework achieves comparable or better accuracy than randomized singular value decomposition. It also has lower computational cost and memory requirements in many practical scenarios, such as when the dimension of the null space is small compared to the dimension of the object.

Medical imaging systems are commonly assessed and optimized by use of objective-measures of image quality (IQ) that quantify the performance of an observer at specific tasks. Variation in the objects to-be-imaged is an important source of variability that can significantly limit observer performance. This object variability can be described by stochastic object models (SOMs). In order to establish SOMs that can accurately model realistic object variability, it is desirable to use experimental data. To achieve this, an augmented generative adversarial network (GAN) architecture called AmbientGAN has been developed and investigated. However, AmbientGANs cannot be immediately trained by use of advanced GAN training methods such as the progressive growing of GANs (ProGANs). Therefore, the ability of AmbientGANs to establish realistic object models is limited. To circumvent this, a progressively-growing AmbientGAN (ProAmGAN) has been proposed. However, ProAmGANs are designed for generating two-dimensional (2D) images while medical imaging modalities are commonly employed for imaging three-dimensional (3D) objects. Moreover, ProAmGANs that employ traditional generator architectures lack the ability to control specific image features such as fine-scale textures that are frequently considered when optimizing imaging systems. In this study, we address these limitations by proposing two advanced AmbientGAN architectures: 3D ProAmGANs and Style-AmbientGANs (StyAmGANs). Stylized numerical studies involving magnetic resonance (MR) imaging systems are conducted. The ability of 3D ProAmGANs to learn 3D SOMs from imaging measurements and the ability of StyAmGANs to control fine-scale textures of synthesized objects are demonstrated., SPIE Medical Imaging 2021

I förskolans utbildning ska varje individuellt barn erbjudas en lärorik och trygg vistelse, detta enligt förskolans styrdokument. Förskolan ska lägga grunden för ett livslångt lärande och utgå ifrån en helhetssyn på barnen utifrån omsorg, utveckling och lärande. Varje individuellt barns behov av trygghet och omsorg ska beaktas för att barnet ska uppleva en känsla av trygghet och därmed ta till sig lärandet i förskolan. Syftet med denna studie var att synliggöra hur pedagoger i förskolan resonerar om och skapar förutsättningar för anknytning mellan pedagog och barn samt den problematik som kan uppstå kring anknytning i förskolan. I studiens frågeställningar efterfrågas vilken syn pedagoger har på anknytningens betydelse i förskolan, hur de arbetar med barns anknytning till pedagoger och vilken problematik som kan uppstå kring anknytning mellan pedagoger och barn i förskolan. Studien har sin utgångspunkt i anknytningsteorin av John Bowlby (1907-1990). För att uppnå studiens syfte och frågeställningar genomfördes kvalitativa, semistrukturerade intervjuer med fyra pedagoger inom två olika förskolor i två olika kommuner. Majoriteten av pedagogerna ansåg att de faktorer som är av vikt vid barnsanknytning i förskolan är relationer, trygghet, omsorg, vilken slags anknytning barnen hartill sina föräldrar, personaltäthet, storlek på barngruppen samt vilket förhållningssätt ochvilken kompetens man som pedagog besitter.

Deep learning-based image super-resolution (DL-SR) has shown great promise in medical imaging applications. To date, most of the proposed methods for DL-SR have only been assessed by use of traditional measures of image quality (IQ) that are commonly employed in the field of computer vision. However, the impact of these methods on objective measures of image quality that are relevant to medical imaging tasks remains largely unexplored. In this study, we investigate the impact of DL-SR methods on binary signal detection performance. Two popular DL-SR methods, the super-resolution convolutional neural network (SRCNN) and the super-resolution generative adversarial network (SRGAN), were trained by use of simulated medical image data. Binary signal-known-exactly with background-known-statistically (SKE/BKS) and signal-known-statistically with background-known-statistically (SKS/BKS) detection tasks were formulated. Numerical observers, which included a neural network-approximated ideal observer and common linear numerical observers, were employed to assess the impact of DL-SR on task performance. The impact of the complexity of the DL-SR network architectures on task-performance was quantified. In addition, the utility of DL-SR for improving the task-performance of sub-optimal observers was investigated. Our numerical experiments confirmed that, as expected, DL-SR could improve traditional measures of IQ. However, for many of the study designs considered, the DL-SR methods provided little or no improvement in task performance and could even degrade it. It was observed that DL-SR could improve the task-performance of sub-optimal observers under certain conditions. The presented study highlights the urgent need for the objective assessment of DL-SR methods and suggests avenues for improving their efficacy in medical imaging applications.

Documenting and analyzing how multilingualism materializes around us gives insights in the use, hierarchies and inclusions of languages in society. The visualization of these insights, however, is often challenging as characteris- tics of languages, their flows, movements etc. demand contextualization and clar- ifications that can be difficult to render on a visualization model such as a map. This paper discusses the challenges of visualization and the potentials of digital maps in Linguistic Landscape Studies. We suggest to include and integrate vari- ous layers of qualitative and quantitative data in order to strive for rendering the dynamism of language use.

I dagens samhälle överutnyttjas jordens resurser. Dagens levnadssätt och klimatförändringarna som sker, leder därför till att högre krav ställs på företag att arbeta med hållbarhetsfrågor och sträva efter resurseffektiva arbetsmetoder. För att företag ska bli mer resurseffektiva kan det krävas verktyg eller arbetsmetoder som hjälper till att identifiera områden med förbättringspotential. I den här studien analyserades Leanverktyget värdeflödesanalys och dess tillämpbarhet på processindustrin. Värdeflödesanalys är ett kartläggningsverktyg som används för att identifiera förluster och flödesbegränsade faktorer relaterade till en tillverkningsprocess. Kartläggningen analyserar såväl information- som materialflöde. Författarna vill med den här studien undersöka hur värdeflödesanalys kan tillämpas eller anpassas till en kontinuerligt tillverkande miljö. Studien är gjord som en fallstudie hos Stora Enso Skoghall där datainsamlingen har gjorts genom en kartläggning av flödet, en enkätundersökning och semistrukturerade intervjuer. Studien visar att verktyget kan tillämpas på processindustrin då det ger en bra översikt över processerna och indikerar områden som kan ses som flödesbegränsande. Som verktyg för förlustidentifiering krävs det att kartläggningen kompletteras med ytterligare analysmetoder för att få en tydligare bild över vilka förluster som sker inom pappers- och massaindustrin. Värdeflödesanalysen kan bland annat utvecklas gällande en tydligare kartläggning av informationsflödet. Studiens författare anser också att kartläggningen av materialflödet kan utvecklas med mer information om hur avvikelser sker längs tillverkningen. Materialflödet kan också illustreras med hjälp av ett simulerande verktyg för att ge en mer korrekt bild över avvikelserna som sker. In today's society, the earth's resources are overused. Today's way of living and the climate changes that are taking place therefore lead to higher requirements on companies to work with issues regarding sustainability and strive for resource-efficient working methods. For companies to become more resource efficient, tools may be needed to help and identify areas with potential for improvement. In this study, the Lean tool value stream mapping and its applicability to the process industry were analyzed. Value stream mapping is a mapping tool used to identify losses and flow-limiting factors related to a manufacturing process. The mapping analyzes both information and material flow. With this study, the authors want to investigate how value flow analysis can be applied or adapted to a continuous manufacturing environment. The study was conducted as a case study at Stora Enso Skoghall, where data collection was done through a mapping of the process, a questionnaire and semi-structured interviews. The study shows that the tool can be applied to the process industry as it provides a good overview of the processes and indicates areas that can be seen as flow-limiting. As a tool for loss identification, it is required that the mapping is supplemented with additional analysis methods in order to get a clearer picture of the losses that occur in the paper and pulp industry. The value stream mapping can, among other things, be developed regarding a clearer mapping of the information flow. The authors of the study also believe that the mapping of the material flow can be developed with more information about how deviations occur along the production. The material flow can also be illustrated with the help of a simulating tool to give a more correct picture of the deviations that occur.

Introduction: The history of going concern have been surrounded by uncertainties. The concept becomes relevant in times of economic crisis. The accuracy of existing procedures concerning GCOs have been questioned, where firms file for bankruptcy without any prior indications of going concern issues. Therefore, it has been questioned if the auditors are better than anyone else to predict the future. The standards and regulations leave out large room for professional judgement, thus there is a great risk of fluctuations in the judgement process in practice. Without a complete understanding of going concern, one could question the added value of the concept, and what conclusions can be made from prior literature. Purpose: The purpose of our study is to enhance the understanding of the auditor’s going concern assessment by looking further into their application and treatment of the concept in practice. This will provide a more complete nuanced picture of auditor’s conceptualization and their process of evaluating going concern. Method: Our purpose in this study is achieved by using a qualitative research method. The empirical findings are collected through using a semi-structured interview approach. The interview guide is developed from our model (Figure 2) which is derived from previous literature in the field. Our sample consists of 6 authorized auditors from the Jönköping region. Findings: The findings indicate that the perception shifts based on the process. Going concern is a difficult assessment, which is highly influenced by subjective judgement. Auditor’s application process in practice can be identified as a step-process. Between these steps, the perception changes. The process is characterized by auditors seeking evidence to the contrary of issuing a GCO.

In medical imaging systems, task-based metrics have been advocated as a means of evaluating image quality. Mathematical observers are one method of computing such metrics. Although the Bayesian Ideal Observer (IO) is optimal by definition, it is frequently intractable and non-linear. Linear approximations to the IO are sometimes employed to obtain task-based statistics when computing the IO is infeasible. The optimal linear observer for maximizing the SNR of the test statistic is the Hotelling Observer (HO). However, the computational cost for computing the HO increases with image size and becomes intractable for larger images. Channelized methods of reducing the dimensionality of the data before computing the HO have become popular, with efficient channels capable of approximating the HO’s performance at significantly reduced computational cost. State-of-the-art channels have been learned by using an autoencoder (AE) to encode data by employing a known signal template as the desired reconstruction, but the method is dependant on a high-quality estimate of the signal. An alternative to channels is approximating the test statistic directly using a feed-forward neural network (FFNN). However, this approach can overfit when the amount of training data is limited. In this work, a generalized method for learning channels utilizing an AE with dual losses (AEDL) is proposed. The AEDL framework jointly minimizes both task-specific and reconstruction losses to learn a set of efficient channels, even when the number of training images is relatively small. Preliminary results indicate that the proposed network outperforms state-of-the-art methods on the selected imaging task. Additionally, the AEDL framework suffers from less overfitting than the FFNN.

The objective assessment of image quality (IQ) has been advocated for the analysis and optimization of medical imaging systems. One method of obtaining such IQ metrics is through a mathematical observer. The Bayesian ideal observer is optimal by definition for signal detection tasks, but is frequently both intractable and non-linear. As an alternative, linear observers are sometimes used for task-based image quality assessment. The optimal linear observer is the Hotelling observer (HO). The computational cost of calculating the HO increases with image size, making a reduction in the dimensionality of the data desirable. Channelized methods have become popular for this purpose, and many competing methods are available for computing efficient channels. In this work, a novel method for learning channels using an autoencoder (AE) is presented. AEs are a type of artificial neural network (ANN) that are frequently employed to learn concise representations of data to reduce dimensionality. Modifying the traditional AE loss function to focus on task-relevant information permits the development of efficient AE-channels. These AE-channels were trained and tested on a variety of signal shapes and backgrounds to evaluate their performance. In the experiments, the AE-learned channels were competitive with and frequently outperformed other state-of-the-art methods for approximating the HO. The performance gains were greatest for the datasets with a small number of training images and noisy estimates of the signal image. Overall, AEs are demonstrated to be competitive with state-of-the-art methods for generating efficient channels for the HO and can have superior performance on small datasets., 10 pages, 7 figures, submitted to IEEE-TMI

Die Langzeitversuche in Järna, Schweden, zeigen: Kompostierung und der Einsatz der biologisch-dynamischen Präparate steigern den Humusgehalt. Anhand verschiedener Düngungsvarianten konnte gezeigt werden, dass Mistkompost und Präparate den Humusgehalt im Boden innerhalb von 14 Jahren um 10% steigerte. Dies zeigt, wie wertvoll der hofeigene Dünger, in Form von Festmist, für den Hoforganismus ist.

Task-based measures of image quality (IQ) quantify the ability of an observer to perform a specific task. Such measures are employed for assessing and optimizing medical imaging systems. Although the Bayesian ideal observer is optimal by definition, it is frequently both non-linear and intractable. In such cases, linear observers are commonly employed. However, the optimal linear observer, the Hotelling observer (HO), becomes intractable when considering large images. Channelized methods have become popular for reducing the dimensionality of image data. In this work, we propose a novel method for determining efficient channels by learning them with autoencoders (AEs). Autoencoders are neural networks that can be employed to learn concise representations of data, frequently for the purposes of reducing dimensionality. We trained several AEs to encode task-specific information by modifying the standard loss function and examined the effect of hidden layer size and the use of tied/untied weights on the resulting representation accuracy. Subsequently, HOs were applied to both the original images and the dimensionality-reduced versions of them produced by the AEs. It was demonstrated that, for a suitable specification of the AE, the performance of the HO was relatively unaffected by the encoding of the image. However, the computational cost of inverting the covariance matrix was greatly reduced when the HO was applied with the encoded data due to its reduced dimensionality. Our findings suggest that AEs may represent an attractive alternative to the use of heuristic channels for reducing the dimensionality of image data when seeking to accurately approximate the performance of the HO on signal detection tasks.

The article presents a new language learner corpus for Swedish, SweLL, and the methodology from collection and pesudonymisation to protect personal information of learners to annotation adapted to second language learning. The main aim is to deliver a well-annotated corpus of essays written by second language learners of Swedish and make it available for research through a browsable environment. To that end, a new annotation tool and a new project management tool have been implemented, both with the main purpose to ensure reliability and quality of the final corpus. In the article we discuss reasoning behind metadata selection, principles of gold corpus compilation and argue for separation of normalization from correction annotation. Special Issue of Selected Contributions from the Seventh Swedish Language Technology Conference (SLTC 2018)

In the current experimental device of TAE Technologies, C-2W (also called "Norman"), record breaking advanced beam-driven field-reversed configuration (FRC) plasmas are produced and sustained in steady state utilizing variable energy neutral beams (15-40 keV, total power up to 20 MW), advanced divertors, bias electrodes, and an active plasma control system. This fully operational experiment is coupled with a fully operational suite of advanced diagnostic systems. The suite consists of 60+ individual systems spanning 20 categories, including magnetic sensors, Thomson scattering, interferometry/polarimetry, spectroscopy, fast imaging, bolometry, reflectometry, charged and neutral particle analysis, fusion product detection, and electric probes. Recently, measurements of main ion temperatures via a diagnostic neutral beam, axial profiles of energy flux from an array of bolometers, and divertor and edge plasma parameters via an extensive set of electric probes, interferometers, and spectrometers have all been made available. All the diagnostics work together to provide a complete picture of the FRC, fast-ion inventory, and edge plasma details enabling tomographic reconstruction of plasma parameter profiles and real-time plasma control.

A suite of diagnostics was developed to measure particle and heat fluxes arriving at the divertor electrodes of the C-2W experiment at TAE Technologies. The divertor electrodes consist of 4 concentric rings, each equipped with a bolometer, electrostatic energy analyzer, and thermocouple mounted at two opposing azimuthal locations. These probes provide measurements of the power flux to the divertor electrodes as well as measurements of the ion current density, ion energy distribution, and total energy deposition. The thermocouples also provide calibration points for inferring the heat deposition profile via thermographic imaging of the electrodes with a fast infrared camera. The combined measurements enable the calculation of the energy lost per escaping electron/ion pair, which is an important metric for understanding electron heat transport in the open field lines that surround the field-reversed configuration plasma in C-2W.

Two filtered, fast-imaging instruments, with radial and axial views, respectively, were used on the C-2U device to visualize line emission from impurities and hydrogenic neutrals. Novel calibration techniques needed to be developed for these instruments because the accelerated pace of C-2U operations precluded access to the interior of the vacuum vessel, targets used in typical calibration methods were not available, and in order to account for effects which have not been sufficiently addressed in the literature. Spatial calibration involved optimizing parameters in a generic camera model: ex situ using a checkerboard target and in situ using the vacuum vessel port geometry. Radiometric calibration was performed ex situ in three stages. First, the camera relative response function was mapped using an algorithm developed for high dynamic-range imaging. Second, the non-uniformity of the optical system was measured using a large LCD monitor with a characterized angular emission pattern. Finally, the absolute photon efficiency of each interference filter was determined using a calibrated uniform radiance source while also accounting for reduction in the filter transmission for off-normal rays. Periodically during the run campaign, line emission from neutral beams fired into a gas target was used as an in situ reference to check for degradation of viewport transmission. One application using calibrated camera data was tomographic reconstruction of passive impurity emission, which provided a sanity check to the excluded-flux radius inferred from wall-mounted magnetic sensors.

Active control of field reversed configuration (FRC) devices requires a method to determine the flux surface geometry and dynamic properties of the plasma during both transient and steady-state conditions. The current tomography (CT) method uses Bayesian inference to determine the plasma current density distribution using both the information from magnetic measurements and a physics model in the prior. Here we show that, from the inferred current sources, the FRC topology and its axial stability properties are readily obtained. When Gaussian process priors are used and the forward model is linear, the CT solution involves non-iterative matrix operations and is then ideally suited for deterministic real-time applications. Because no equilibrium assumptions are used in this case, inference of plasma topology and dynamics up to Alfvenic frequencies then becomes possible. Inference results for the C-2U device exhibit self-consistency of motions and forces during Alfvenic transients, as well as good agreement with plasma imaging diagnostics., It is important to understand the fast plasma dynamics in the operation of fusion plasma devices. Here the authors demonstrate the inference on the internal field reversed configuration magnetic topology and their occurrence during fast Alfvenic transient phenomena in C-2U device.

I ett samhälle där eventindustrin är växande är det av stor vikt att få förståelse för vad som motiverar individer till att arbeta volontärt. Många evenemang skulle inte gå att genomföra utan volontär arbetskraft. Syftet med denna studie är att få förståelse för hur de instrumentella (yttre) och intrinsikala (inre) motivationsfaktorerna påverkar individer till att arbeta volontärt. Studien genomfördes med en kvalitativ metod och data samlades in genom sju semistrukturerade intervjuer. Studiens respondenter bestod av individer som tidigare arbetat volontärt. Vidare ska samtliga av respondenterna arbeta volontärt för EuroPride 2018. Resultatet påvisade mer skilda upplevelser gällande de instrumentella motivationsfaktorerna och fler enstämmiga svar gällande de intrinsikala faktorerna. Gemenskap var dock ett återkommande tema som samtliga respondenter belyste. Det framgick tydligt i studien hur de intrinsikala motivationsfaktorerna fanns väl förankrade och djupt rotade hos respondenterna, medan de instrumentella motivationsfaktorerna mer sågs som en bonus som förgyllde tillvaron. In a society where the event industry is growing, it is of importance to understand what motivates individuals to work voluntarily. Many events would not be possible to accomplish without the work of volunteers. The purpose of this study is to gain knowledge of how the instrumental (external) and intrinsic (internal) motivational factors influence individuals to work voluntarily. The study was conducted with a qualitative method and data was collected through seven semi- structured interviews. The study's respondents consisted of individuals who previously have worked as volunteers. Furthermore, all of them will volunteer at EuroPride 2018. The result demonstrated different experiences regarding the instrumental motivation factors and more unanimous answers regarding the intrinsic factors. However, belonging to a community was a recurring theme highlighted by all respondents. It was clear in the study how the intrinsic motivation factors were well-rooted within the respondents, while the instrumental motivational factors were more viewed as a bonus that embellished life. This study will be presented in Swedish.

This paper reports on the status of learner corpus anonymization for the ongoing research infrastructure project SweLL. The main project aim is to deliver and make available for research a well-annotated corpus of essays written by second language (L2) learners of Swedish. As the practice shows, annotation of learner texts is a sensitive process demanding a lot of compromises between ethical and legal demands on the one hand, and research and technical demands, on the other. Below, is a concise description of the current status of pseudonymization of language learner data to ensure anonymity of the learners, with numerous examples of the above-mentioned compromises.

Eutrophication caused by agriculture is an increasing ecological threat to the Baltic Sea. Modern, resource-efficient farming systems based on integrated plant and animal production, effective nutrient recycling and low external inputs can enhance multiple agro-ecosystem services, resulting in reduced pollution. Practical examples of such farming systems are not widespread. Therefore, the Baltic Ecological Recycling Agriculture and Society (BERAS) Implementation project aimed to foster this systemic shift. In this paper, agronomic strategies are described to improve nitrogen (N) efficiency for the conversion to ecological recycling agriculture (ERA). First, N farm gate balances of 22 farms in conversion are presented. They showed a large variation from −9 to 90 kg∙N∙ha−1∙a−1. Then, the use of guidelines and advisory tools to improve the nitrogen efficiency is described. The legume estimation trainer and nitrogen budget calculator help assess and optimize the nitrogen supply from legumes under farming conditions. The application of the crop rotation planning tool “ROTOR” guides advisors and farmers to identify agronomically and environmentally sound rotations. The tools can help overcome key agronomic constraints by implementing ERA. The necessity of accompanying measures from policy and the need to change food consumption patterns are discussed.

C-2 is a unique, large compact-toroid (CT) device at Tri Alpha Energy that produces field-reversed configuration (FRC) plasmas by colliding and merging oppositely directed CTs. Significant progress has recently been made on C-2, achieving ~5 ms stable plasmas with a dramatic improvement in confinement, far beyond the prediction from the conventional FRC scaling. This stable, long-lived FRC plasma state is called the high-performance FRC (HPF) regime. The key approaches to achieve the HPF regime are as follows: (i) dynamic FRC formation by collision/merging of super-Alfvenic CTs, (ii) effective control of stability and transport by end-on plasma guns and neutral-beam (NB) injection, and (iii) active wall conditioning using titanium and lithium gettering systems. Moreover, further improvement in FRC confinement has been obtained with improved open-field-line plasma properties such as a lower fluctuation level, reduced transport rates in radial/axial directions, and lower background neutral density a...

This study evaluated the effects of organic agriculture manuring systems on carrot (Daucus carota) root morphology and sugar and polyacetylene content. Carrots were harvested three times per season 2006–2007 in a long-term field experiment at Skilleby research farm, Sweden. The effects of pelleted chicken manure, fresh farmyard manure and composted farmyard manure (COM) were compared against control plots left unmanured since the field experiment started in 1991. The carrots were analyzed for root size, root shape, amount of soluble sugars and amount of falcarinol-type polyacetylenes. Differences between manuring systems were found to be smaller than the variation between harvest years and harvest occasions, probably due to the grass-clover ley included in the crop rotation system. On an average for the six harvests, manuring with COM increased root length by 6% compared with fertilizing with pelleted chicken manure. Carrots fertilized with pelleted chicken manure also had 6–7% lower total soluble sugar content than carrots manured with 50 t ha−1 of composted or fresh manure. The falcarinol to total falcarinol-type polyacetylenes ratio was 15.4% in carrots manured with 50 t ha−1 of composted or fresh manure and 14.7% in carrots fertilized with pelleted chicken manure. Seasonal fluctuations in falcarinol-type polyacetylenes were more pronounced in carrots manured with fresh or composted manure than in carrots fertilized with pelleted chicken manure. The results suggest that manuring organic carrots with compost may be the most beneficial strategy, at least in systems where fertilizer is applied only once per crop rotation, whether directly to the carrot crop or in the preceding crop.

Paraphrase sparsity is an issue that complicates the training process of question answering systems: syntactically diverse but semantically equivalent sentences can have significant disparities in predicted output probabilities. We propose a method for generating an augmented paraphrase corpus for the visual question answering system to make it more robust to paraphrases. This corpus is generated by concatenating two sequence to sequence models. In order to generate diverse paraphrases, we sample the neural network using diverse beam search. We evaluate the results on the standard VQA validation set. Our approach results in a significantly expanded training dataset and vocabulary size, but has slightly worse performance when tested on the validation split. Although not as fruitful as we had hoped, our work highlights additional avenues for investigation into selecting more optimal model parameters and the development of a more sophisticated paraphrase filtering algorithm. The primary contribution of this work is the demonstration that decent paraphrases can be generated from sequence to sequence models and the development of a pipeline for developing an augmented dataset. Master of Science

TAE Technologies' research is devoted to producing high temperature, stable, long-lived field-reversed configuration (FRC) plasmas by neutral-beam injection (NBI) and edge biasing/control. The newly constructed C-2W experimental device (also called "Norman") is the world's largest compact-toroid (CT) device, which has several key upgrades from the preceding C-2U device such as higher input power and longer pulse duration of the NBI system as well as installation of inner divertors with upgraded electrode biasing systems. Initial C-2W experiments have successfully demonstrated a robust FRC formation and its translation into the confinement vessel through the newly installed inner divertor with adequate guide magnetic field. They also produced dramatically improved initial FRC states with higher plasma temperatures (Te ~250+ eV; total electron and ion temperature g1.5 keV, based on pressure balance) and more trapped flux (up to ~15 mWb, based on rigid-rotor model) inside the FRC immediately after the merger of collided two CTs in the confinement section. As for effective edge control on FRC stabilization, a number of edge biasing schemes have been tried via open field-lines, in which concentric electrodes located in both inner and outer divertors as well as end-on plasma guns are electrically biased independently. As a result of effective outer-divertor electrode biasing alone, FRC plasma diamagnetism duration has reached up to ~9 ms which is equivalent to C-2U plasma duration. Magnetic field flaring/expansion in both inner and outer divertors plays an important role in creating a thermal insulation on open field-lines to reduce a loss rate of electrons, which leads to improvement of the edge and core FRC confinement properties. Experimental campaign with inner-divertor magnetic-field flaring has just commenced and early result indicates that electron temperature of the merged FRC stays relatively high and increases for a short period of time, presumably by NBI and ExB heating.

The Lithium Tokamak eXperiment (LTX) is a spherical tokamak with the unique capability of studying the low-recycling regime by coating nearly 90% of the first wall with lithium in either solid or liquid form. Several grams of lithium are evaporated onto the plasma-facing side of the first wall. Without lithium coatings, the plasma discharge is limited to less than 5 ms and only 10 kA of plasma current, and the first wall acts as a particle source. With cold lithium coatings, plasma discharges last up to 20 ms with plasma currents up to 70 kA. The lithium coating provides a low-recycling first wall condition for the plasma and higher fueling rates are required to realize plasma densities similar to that of pre-lithium walls. Traditional puff fueling, supersonic gas injection, and molecular cluster injection (MCI) are used. Liquid lithium experiments will begin in 2012.

This study assessed the concentrations of three falcarinol-type polyacetylenes (falcarinol, falcarindiol, falcarindiol-3-acetate) in carrots and the correlations between these and different soil traits. A total of 144 carrot samples, from three different harvests taken a single season, were analysed in terms of their polyacetylene concentrations and root development. On one of the harvesting occasions, 48 soil samples were also taken and analysed. The chemical composition of the soil was found to influence the concentrations of falcarinol-type polyacetylenes in carrots. When the total soil potassium level was 200 mg/100 g soil, the concentration of falcarindiol (FaDOH) in the carrot samples was 630 μg/g DW, but when carrots were grown in soil with a total potassium level of 300 mg/100 g soil, the FaDOH concentration in the carrots fell to 445 μg/g DW. Carrots grown in soils generally low in available phosphorus exhibited higher levels of falcarindiol if the soil was also low in available magnesium and calcium. The concentrations of polyacetylenes in carrots were positively correlated with total soil phosphorus level, but negatively correlated with total soil potassium level. Of the three polyacetylenes analysed, FaDOH concentrations were influenced most by changes in soil chemical composition.

This project was designed to assess the viability of transmitting data over cell phone audio channels through the use of vowel-like sounds. Sound data was generated by using LPC to generate signals with bandwidth and resonant frequencies corresponding to known formants. Modifications were made to the pulse train and formant frequencies to improve detection performance. A filter bank was also implemented to balance the magnitudes of the frequencies for the symbol set. These symbols were transmitted over a pair of connected cell phones and processed using the Goertzel algorithm. The experiments were carried out over one set of cell phones and repeated multiple times in the same conditions to ensure accuracy. The final system determined that all 10 of the formants tested were potential symbols. Future work should be dedicated to automating detection and determining a transmission rate for the system.

Inledning: Flertalet studier visar att den finansiella kunskapen bland dagens konsumenter av finansiella tjänster är högst bristfällig vilket leder till ett kunskapsunderläge i mötet med en finansiell rådgivare. Dessutom är konsumenten i ett informationsunderläge då rådgivaren har information om bland annat avgifter och incitamenten bakom valet av en viss placering. Dessa underlägen ger upphov till en asymmetrisk relation och det är denna asymmetri samt dess konsekvenser som studeras i denna uppsats. Syfte: Syftet med denna uppsats är att från rådgivarnas perspektiv beskriva den asymmetri som förekommer i relationen mellan rådgivare och konsument samt vad denna asymmetriska relation får för konsekvenser för konsumenterna. I tillägg till detta belyses även de konsekvenser som införandet av provisionsförbudet kan ge upphov till. Metod: Genom en kvalitativ tvärsnittsstudie med deduktiv ansats har empiri samlats in genom sju stycken semi-strukturerade intervjuer med finansiella rådgivare. Empirin har sedan analyserats med hjälp av kodning för att kunna beskriva och karaktärisera asymmetrin mellan rådgivare och konsument samt de konsekvenser denna leder till för konsumenterna. Slutsats: Informationsasymmetrin är ett problem som måste överbryggas, kunskapsasymmetrin är däremot en förutsättning för tjänstens existerande. Båda asymmetrier medför konsekvenser för konsumenterna, tar dock konsumenterna eget ansvar kan dessa asymmetrier överbryggas och negativa konsekvenser förhindras. Lagar och regleringar som till exempel provisionsförbudet behöver nödvändigtvis inte vara en optimal lösning för branschen då de även medför nya problem. Hårdast drabbas småspararna då de saknar en betydande förmögenhet och därför inte utgör en lönsam kundgrupp. Att småspararna inte får rådgivning kan leda till samhällsekonomiska konsekvenser eftersom de utgör majoriteten av befolkningen och deras privatekonomi har direkt påverkan på landets ekonomiska tillväxt. Background:Studies have shown that the financial knowledge among today's consumers of financial services is highly inadequate. This means that in the relationship between the advisor and the consumer there is a substantial difference in knowledge. The consumer also has less information regarding fees and incentives behind the choice of products, compared to the advisor. These disadvantages create an asymmetrical relationship and it is this asymmetry and its consequences for consumers that are being studied in this paper. Aim: The purpose of this paper is to describe the asymmetry that exists in the relationship between the financial advisor and the consumer from the perspective of the advisers. This paper also studies what impact the asymmetry has on the consumers. In addition, the consequences resulting from the implementation of the prohibition of commission accepted from third parties are studied. Methodology: Through a qualitative cross-sectional study with a deductive approach empirical evidence is gathered through seven semi-structured interviews with financial advisors. The empirical data were then analyzed to describe the asymmetry between advisors and consumers as well as the resulting consequences. Results: The authors have been able to conclude that the information asymmetry is a problem that must be overcome, the knowledge asymmetry on the other hand is what is enabling the service to exist. Both asymmetries have consequences for consumers, but if consumers take on the responsibility they can decrease the asymmetry gap and prevent negative consequences. Laws and regulations are not necessarily an optimal solution for the industry since they also cause new problems. The consequences are biggest for the small savers as they lack a substantial fortune and do not represent a profitable customer base. If small savers do not receive counseling it might lead to economic consequences for the society because they represent the majority of the population and their personal finances have direct impact on the country's economic growth.

In this article, we describe the research and societal needs as well as ongoing efforts to shape Swedish as a Second Language (L2) infrastructure. Our aim is to develop an electronic research infrastructure that would stimulate empiric research into learners' language development by preparing data and developing language technology methods and algorithms that can successfully deal with deviations in the learner language. SWE-CLARIN

Conventional field-reversed configurations (FRC) face notable stability and confinement concerns, which can be ameliorated by introducing and maintaining a significant fast ion population in the system. This is the conjecture first introduced by Norman Rostoker multiple decades ago and adopted as the central design tenet in Tri Alpha Energy’s advanced beam driven FRC concept. In fact, studying the physics of such neutral beam (NB) driven FRCs over the past decade, considerable improvements were made in confinement and stability. Next to NB injection, the addition of axially streaming plasma guns, magnetic end plugs, as well as advanced surface conditioning lead to dramatic reductions in turbulence driven losses and greatly improved stability. In turn, fast ion confinement improved significantly and allowed for the build-up of a dominant fast particle population. This recently led to the breakthrough of sustaining an advanced beam driven FRC, thereby demonstrating successful maintenance of trapped magnetic flux, plasma dimensions and total pressure inventory for times much longer than all characteristic system time scales and only limited by hardware and electric supply constraints.

Recent experiments on the National Spherical Torus eXperiment (NSTX) have shown the benefits of solid lithium coatings on carbon PFC's to diverted plasma performance, in both L- and H-mode confinement regimes. Better particle control, with decreased inductive flux consumption, and increased electron temperature, ion temperature, energy confinement time, and DD neutron rate were observed. Successive increases in lithium coverage resulted in the complete suppression of ELM activity in H-mode discharges. A liquid lithium divertor (LLD), which will employ the porous molybdenum surface developed for the LTX shell, is being installed on NSTX for the 2010 run period, and will provide comparisons between liquid walls in the Lithium Tokamak eXperiment (LTX) and liquid divertor targets in NSTX. LTX, which recently began operations at the Princeton Plasma Physics Laboratory, is the world's first confinement experiment with full liquid metal plasma-facing components (PFCs). All materials and construction techniques in LTX are compatible with liquid lithium. LTX employs an inner, heated, stainless steel-faced liner or shell, which will be lithium-coated. In order to ensure that lithium adheres to the shell, it is designed to operate at up to 500–600 °C to promote wetting of the stainless by the lithium, providing the first hot wall in a tokamak to operate at reactor-relevant temperatures. The engineering of LTX will be discussed.

In modern field-reversed configuration (FRC) experiments (Binderbauer et al 2015 Phys. Plasmas 22 056110) at TAE Technologies, classical FRC instabilities are suppressed by advanced neutral beam injection and edge biasing methods, leading to high plasma confinement and fast ion pressure built-up which is comparable to the bulk plasma pressure. In some of these high performance FRC plasmas, a new macroscopically non-destructive fast ion driven micro-burst instability is observed as periodic small amplitude bursts with frequency down chirping in the diamagnetic drift frequency range, repeating about every 0.1 to 0.5 ms. The occurrence of these micro-bursts and burst-free operation can be controlled by changing the injected neutral beam energy. Major observed characteristics of this new instability are presented. Possible explanation of the phenomenon is suggested.

The new C-2W Thomson scattering (TS) diagnostic consists of two individual subsystems for monitoring electron temperature (Te) and density (ne): one system in the central region is currently operational, and the second system is being commissioned to monitor the open field line region. Validating the performance of the TS's custom designed system components and unique calibration of the detection system and diagnostic as a whole is crucial to obtaining high precision Te and ne profiles of C-2W's plasma. The major components include a diode-pumped Nd:YAG laser which produces 35 pulses at up to 20 kHz, uniquely designed collection lenses with a fast numerical aperture, and uniquely designed polychromators with filters sets to optimize a Te ranging from 10 eV to 2 keV. This paper describes the design principles and techniques used to characterize the main components of the TS diagnostic on C-2W, as well as the results of Rayleigh scattering calibrations performed for the whole system response.

Agricultural production and nutrient loads to the Baltic Sea are likely to increase following Poland's and the Baltic States' entrance into the EU. According to HELCOM these trends will be highly d ...