This thesis addresses the meaning and scope of application of the right not to be subjected to degrading treatment, a distinct form of harm within the absolute prohibition of torture, inhuman or degrading treatment or punishment under Article 3 of the European Convention on Human Rights. Through an interpretive case-law analysis, the thesis presents a deeper conceptual understanding of the meaning of degrading treatment than is found in existing human rights literature. It is a central argument of this thesis that the concept of human dignity occupies a key position in the interpretation of degrading treatment adopted by the European Court of Human Rights. Consequently, it is argued that the meaning of human dignity in this context ‘frames’ the potential boundaries of the right. The thesis aims to facilitate identification of situations that may convincingly be argued to amount to potential instances of degrading treatment through generating a richer appreciation of the right’s proper scope of concern. A comprehensive account of the meaning of degrading treatment and corresponding state obligations is offered. This account provides a framework for future application of the right that is both practical and plausible.

Cyanide is a well known toxicant that arises in the environment from both biological and industrial sources. Bacteria have evolved novel coping mechanisms for cyanide and function as principal agents in the biosphere for cyanide recycling. Some bacteria exhibit the unusual ability of growing on cyanide as the sole nitrogen source. One such organism is Pseudomonas fluorescens NCIMB 11764 (Pf11764) which employs a novel oxidative mechanism for detoxifying and assimilating cyanide. A unique complex of enzymes referred to as cyanide oxygenase (CNO) is responsible for this ability converting cyanide to ammonia which is then assimilated. Because one component of the four member CNO complex was previously shown to act on cyanide independent of the other members, its characterization was sought as a means of gaining a better understanding of the overall catalytic mechanism of the complex. Preliminary studies suggested that the enzyme belonged to a subset of nitrilase enzymes known as cyanide dihydratases (CynD), however, a cynD-like gene in Pf11764 could not be detected by PCR. Instead, a separate nitrilase (Nit) linked to cyanide metabolism was detected. The corresponding nit gene was shown to be one of a conserved set of nit genes traced to a unique cluster in bacteria known as Nit1C. To determine whether the previously described CynD enzyme was instead Nit, efforts were undertaken to isolate the enzyme. This was pursued by cloning and expressing the recombinant enzyme and by attempting to isolate the native enzyme. This thesis is concerned with the latter activity and describes the purification of a Nit-like cyanide-degrading nitrilase (NitCC) from Pf11764 to ~95% homogeneity. Purification was greatly facilitated by the discovery that fumaronitrile, as opposed to cyanide, was the preferred substrate for the enzyme (20 versus 1 U/mg protein, respectively). While cyanide was less effective as a substrate, the specificity for cyanide far outweighed that (10,000 fold) of the recombinant enzyme (NitPG) implying that the native NitCC protein purified in this work is different from that of the cloned recombinant. Further evidence of this was provided by molecular studies indicating that the two proteins differ in mass (34.5 and 38 kDa, respectively) and amino acid sequence. In summary, two different Nit enzymes are encoded by Pf11764. While the two share greater than 50% amino acid sequence identity, the results suggest that the native NitCC enzyme purified in this work functions better as a cyanide-degrading nitrilase and is one of four enzyme components comprising CNO required for Pf11764 cyanide assimilation.

No description available.

The soil-borne filamentous fungus Trichoderma virens is a biocontrol agent with a well known ability to produce antibiotics, parasitize pathogenic fungi and induce systemic resistance in plants. Here we report the identification, purification and characterization of an elicitor secreted by T. virens; a small protein designated Sm1 (small protein 1). Confrontation and disk assays demonstrated that Sm1 lacks toxic activity against plants and microbes. Native, purified Sm1 triggers production of reactive oxygen species in rice (Oryza sativa) and cotton (Gossypium hirsutum), and induces the expression of defense related genes both locally and systemically in cotton. Gene expression analysis revealed that SM1 is expressed throughout fungal development and is transcriptionally regulated by nutrient conditions and the presence of a host plant. When T. virens was co-cultured with cotton in an axenic hydroponic system, SM1 expression and secretion of the protein was significantly higher than when the fungus was grown alone. These results indicate that Sm1 is involved in plant-Trichoderma recognition and the induction of resistance by activation of plant defense mechanisms. Following the cloning of SM1, strains disrupted in or over-expressing SM1 were generated. Targeted gene disruption revealed that SM1 was not involved in fungal development. Expression of defense related genes in cotton and maize (Zea mays) was induced locally and systemically following colonization by T. virens in the hydroponic system. Low levels of expression of cotton or maize defense genes were found when seedlings were grown with a T. virens strain disrupted in SM1, ssupporting the Sm1-elicitor hypothesis. Additionally, unique proteins in T.virens-cotton/maize interaction were identified. Thus, the induction of defense responses in two agriculturally important crops appears to be microbially mediated. Functional analysis of a cell wall degrading enzyme, beta-1,6-glucananse (Tv-bgn3) from T. virens, demonstrated involvement of this enzyme indirectly in mycoparasitic activity of T. virens. Protein extracts from the strain disrupted in TV-BGN3 displayed reduced capability to inhibit growth of Pythium ultimum as compared to the wild-type. Additionally, protein extracts from the strains co-expressed with TV-BGN2 (beta-1,3-glucananse) from T. virens showed a significantly increased capability to inhibit growth of P. ultimum and Rhizoctonia solani hyphae.

Studiens syfte var att undersöka och analysera pedagogers erfarenheter av en skriftlig utformad plan för att motverka diskriminering och kränkande behandling i förskolan. Det är en kvalitativ studie som bygger på intervjuer med pedagoger på förskolor. Frågeställningarna som låg till grund för studien var: Hur upplever pedagogerna processen kring utformandet av den skriftligt utformade planen för att motverka diskriminering och kränkande handling? Hur beskriver pedagogerna den skriftligt utformade planens användning i arbetet att motverka diskriminering och kränkande handling? Vilka utvecklingsmöjligheter ser pedagogerna kring den skriftligt utformade planen som verktyg i arbetet att motverka diskriminering och kränkande handling? Resultatet i studien visar bland annat att pedagogerna upplever processen kring utformandet av planen som svår då det till exempel var svårt att få tag i information. Användningen av planen beskriver pedagogerna som en punkt på dagordningen, de tycker att den används samtidigt som den upplevs mer som en pappersprodukt än som ett innehållsförankrat dokument. När det gäller utvecklingsmöjligheter kring planen ger pedagogerna uttryck för att de själva behöver mer kunskap i ämnet och planen behöver på olika sätt implementeras mer i verksamheten. / The purpose of this study was to investigate and analyze teachers´ experiences of a written plan designed to counter discrimination and offensive behavior in preschool. It is a qualitative study based on interviews with educators at preschools. The questions that formed the basis for the study was: How do preschool teachers experience the process of designing the written plan designed to counter discrimination and offensive action? How do teachers describe the use of the written plan designed to combat discrimination and offensive action? What development opportunities do the teachers see around the written plan designed as a tool in efforts to combat discrimination and offensive action? The results of the study show that teachers experience the process of designing the plan as difficult as it was difficult to obtain information. The teachers describe the use of the plan as an agenda item, they think that it is used while it is perceived more as a paper product than as a content embedded documents. When it comes to development opportunities of the plan the teachers express that they need more knowledge on the subject and the plan needs to be more implemented in the preschool’s activity.

The probabilistic design of dynamic systems with degrading components is difficult. Design of dynamic systems typically involves the optimization of a time-invariant performance measure, such as Energy, that is estimated using a dynamic response, such as angular speed. The mechanistic models developed to approximate this performance measure are too complicated to be used with simple design calculations and lead to lengthy simulations. When degradation of the components is assumed, in order to determine suitable service times, estimation of the failure probability over the product lifetime is required. Again, complex mechanistic models lead to lengthy lifetime simulations when the Monte Carlo method is used to evaluate probability. Based on these problems, an efficient methodology is presented for probabilistic design of dynamic systems and to estimate the cumulative distribution function of the time to failure of a performance measure when degradation of the components is assumed. The four main steps include; 1) transforming the dynamic response into a set of static responses at discrete cycle-time steps and using Singular Value Decomposition to efficiently estimate a time-invariant performance measure that is based upon a dynamic response, 2) replacing the mechanistic model with an approximating function, known as a “metamodel” 3) searching for the best design parameters using fast integration methods such as the First Order Reliability Method and 4) building the cumulative distribution function using the summation of the incremental failure probabilities, that are estimated using the set-theory method, over the planned lifetime. The first step of the methodology uses design of experiments or sampling techniques to select a sample of training sets of the design variables. These training sets are then input to the computer-based simulation of the mechanistic model to produce a matrix of corresponding responses at discrete cycle-times. Although metamodels can be built at each time-specific column of this matrix, this method is slow especially if the number of time steps is large. An efficient alternative uses Singular Value Decomposition to split the response matrix into two matrices containing only design-variable-specific and time-specific information. The second step of the methodology fits metamodels only for the significant columns of the matrix containing the design variable-specific information. Using the time-specific matrix, a metamodel is quickly developed at any cycle-time step or for any time-invariant performance measure such as energy consumed over the cycle-lifetime. In the third step, design variables are treated as random variables and the First Order Reliability Method is used to search for the best design parameters. Finally, the components most likely to degrade are modelled using either a degradation path or a marginal distribution model and, using the First Order Reliability Method or a Monte Carlo Simulation to estimate probability, the cumulative failure probability is plotted. The speed and accuracy of the methodology using three metamodels, the Regression model, Kriging and the Radial Basis Function, is investigated. This thesis shows that the metamodel offers a significantly faster and accurate alternative to using mechanistic models for both probabilistic design optimization and for estimating the cumulative distribution function. For design using the First-Order Reliability Method to estimate probability, the Regression Model is the fastest and the Radial Basis Function is the slowest. Kriging is shown to be accurate and faster than the Radial Basis Function but its computation time is still slower than the Regression Model. When estimating the cumulative distribution function, metamodels are more than 100 times faster than the mechanistic model and the error is less than ten percent when compared with the mechanistic model. Kriging and the Radial Basis Function are more accurate than the Regression Model and computation time is faster using the Monte Carlo Simulation to estimate probability than using the First-Order Reliability Method.

The soil-borne filamentous fungus Trichoderma virens is a biocontrol agent with a well known ability to produce antibiotics, parasitize pathogenic fungi and induce systemic resistance in plants. Here we report the identification, purification and characterization of an elicitor secreted by T. virens; a small protein designated Sm1 (small protein 1). Confrontation and disk assays demonstrated that Sm1 lacks toxic activity against plants and microbes. Native, purified Sm1 triggers production of reactive oxygen species in rice (Oryza sativa) and cotton (Gossypium hirsutum), and induces the expression of defense related genes both locally and systemically in cotton. Gene expression analysis revealed that SM1 is expressed throughout fungal development and is transcriptionally regulated by nutrient conditions and the presence of a host plant. When T. virens was co-cultured with cotton in an axenic hydroponic system, SM1 expression and secretion of the protein was significantly higher than when the fungus was grown alone. These results indicate that Sm1 is involved in plant-Trichoderma recognition and the induction of resistance by activation of plant defense mechanisms. Following the cloning of SM1, strains disrupted in or over-expressing SM1 were generated. Targeted gene disruption revealed that SM1 was not involved in fungal development. Expression of defense related genes in cotton and maize (Zea mays) was induced locally and systemically following colonization by T. virens in the hydroponic system. Low levels of expression of cotton or maize defense genes were found when seedlings were grown with a T. virens strain disrupted in SM1, ssupporting the Sm1-elicitor hypothesis. Additionally, unique proteins in T.virens-cotton/maize interaction were identified. Thus, the induction of defense responses in two agriculturally important crops appears to be microbially mediated. Functional analysis of a cell wall degrading enzyme, beta-1,6-glucananse (Tv-bgn3) from T. virens, demonstrated involvement of this enzyme indirectly in mycoparasitic activity of T. virens. Protein extracts from the strain disrupted in TV-BGN3 displayed reduced capability to inhibit growth of Pythium ultimum as compared to the wild-type. Additionally, protein extracts from the strains co-expressed with TV-BGN2 (beta-1,3-glucananse) from T. virens showed a significantly increased capability to inhibit growth of P. ultimum and Rhizoctonia solani hyphae.

The following paper is about degrading treatment in preschools and the essay discuss degrading treatment according to the Swedish school law, in preschools and the chosen focus for this study is three to four year old children. The aim is to see whether or not preschool children proceed with degrading treatment towards other children and if preschool teachers believe that children this young have the ability to do so. The questions for this study are: Can children proceed with degrading treatment towards each other? Which conflicts evolve through children’s interactions? Can children in pre-schools have a degrading behavior? To answer these questions participant observation at two preschools and interviews with four preschool teachers were chosen as method. The perspective of this paper is based on the view on children as actors, which is used to acknowledge and enhance the possibilities of letting the children’s own voices be heard. Theories used for this paper is Van Ausdale and Feagin’s (2001) theory about three to four years olds awareness, one about children’s relation to adults presented by Thorne (1993) and Wyness (2012) and lastly Gripsruds explanation of the influence of media combined with statistics from Statens medieråd (Swedish media council). The result of this study show that children between the ages of three to four, use different strategies to include or exclude other children and used things such as age and limitations of participants in a play as excuses. However, these reoccurring excuses cannot be seen as degrading treatment or behavior, according to definition made by the school law. An interesting finding is that the children sometimes used their parents to excuse their actions or used them to threat others. Overall the observational study shows how difficult it can be to see and acknowledge degrading treatment within preschools. The interviews with the preschool teachers indicates that they do not spend much time on acknowledging or trying to prevent degrading treatment amongst children. The preschool teachers discussed children’s quarrels but they tended to see it as something natural within children’s interactions. The conclusion of this essay is that degrading treatment could not be seen at the two preschools, which is contradicting to some of the literature used in this paper.

Studiens syfte var att undersöka hur utvalda organisationer arbetar mot kränkande behandling på nätet bland barn och unga. Metoden som användes var kvalitativ och det empiriska materialet inhämtades genom intervjuer. I studien deltog sex respondenter, fyra av respondenterna var från de olika organisationerna Friends, Bris, Tjejjouren samt Barn- och elevombudet som kommer i kontakt med kränkande behandling på nätet. Två av respondenterna arbetade som skolkuratorer inom skilda elevhälsoteam på två skolor. Resultatet analyserades med hjälp av innehållsanalys och ett teoretiskt ramverk som bestod av institutionell teori och isomorfism. Resultatet visade att arbetsgrunden hos de olika organisationerna skiljde sig åt då de arbetade efter olika lagar och teorier. Organisationerna arbetade med olika insatser, exempelvis genom stödverksamhet, föreläsningar och utbildningar till olika målgrupper. Gemensamt för organisationerna var att de arbetade med liknande metoder mot kränkande behandling på nätet som de använde sig av mot traditionella kränkningar. Resultatet visade att det finns olika sätt för samverkan att bildas mellan organisationer, detta kan vara genom formell samverkan eller informell samverkan. Flera av organisationerna i vår studie riktade sitt arbete mot skolan och resultatet visade att det finns brister i hur den samverkan genomfördes. / The purpose of this study was to explore selected organizations work against degrading treatment on the internet among children and youths. We used a qualitative method and the empirical material was collected by interviews of six participants. Four of them were from the different organizations Friends, Bris, Tjejjouren and Child and School Student Representative which somehow were connected to the issue degrading treatment on the internet. Two of the participants worked as school counselors in various student health teams at two high schools. The material has been analyzed using content analysis and the theoretical framework of institutional theory and isomorfism. The result showed that the working basis of the organizations differed according to laws and theories. The organizations worked with different actions, for example supporting activities, lectures and educations to different target groups such as e.g., school. The organizations had in common that they worked with similar methods against degrading treatment on the internet as against traditional degrading treatment. The results showed that there were different ways to form cooperation between organizations, for example through formal or informal agreements. Several of the organizations in our study directed their work toward the school and the result showed that there are shortcomings in how the cooperation was performed.

The probabilistic design of dynamic systems with degrading components is difficult. Design of dynamic systems typically involves the optimization of a time-invariant performance measure, such as Energy, that is estimated using a dynamic response, such as angular speed. The mechanistic models developed to approximate this performance measure are too complicated to be used with simple design calculations and lead to lengthy simulations. When degradation of the components is assumed, in order to determine suitable service times, estimation of the failure probability over the product lifetime is required. Again, complex mechanistic models lead to lengthy lifetime simulations when the Monte Carlo method is used to evaluate probability. Based on these problems, an efficient methodology is presented for probabilistic design of dynamic systems and to estimate the cumulative distribution function of the time to failure of a performance measure when degradation of the components is assumed. The four main steps include; 1) transforming the dynamic response into a set of static responses at discrete cycle-time steps and using Singular Value Decomposition to efficiently estimate a time-invariant performance measure that is based upon a dynamic response, 2) replacing the mechanistic model with an approximating function, known as a “metamodel” 3) searching for the best design parameters using fast integration methods such as the First Order Reliability Method and 4) building the cumulative distribution function using the summation of the incremental failure probabilities, that are estimated using the set-theory method, over the planned lifetime. The first step of the methodology uses design of experiments or sampling techniques to select a sample of training sets of the design variables. These training sets are then input to the computer-based simulation of the mechanistic model to produce a matrix of corresponding responses at discrete cycle-times. Although metamodels can be built at each time-specific column of this matrix, this method is slow especially if the number of time steps is large. An efficient alternative uses Singular Value Decomposition to split the response matrix into two matrices containing only design-variable-specific and time-specific information. The second step of the methodology fits metamodels only for the significant columns of the matrix containing the design variable-specific information. Using the time-specific matrix, a metamodel is quickly developed at any cycle-time step or for any time-invariant performance measure such as energy consumed over the cycle-lifetime. In the third step, design variables are treated as random variables and the First Order Reliability Method is used to search for the best design parameters. Finally, the components most likely to degrade are modelled using either a degradation path or a marginal distribution model and, using the First Order Reliability Method or a Monte Carlo Simulation to estimate probability, the cumulative failure probability is plotted. The speed and accuracy of the methodology using three metamodels, the Regression model, Kriging and the Radial Basis Function, is investigated. This thesis shows that the metamodel offers a significantly faster and accurate alternative to using mechanistic models for both probabilistic design optimization and for estimating the cumulative distribution function. For design using the First-Order Reliability Method to estimate probability, the Regression Model is the fastest and the Radial Basis Function is the slowest. Kriging is shown to be accurate and faster than the Radial Basis Function but its computation time is still slower than the Regression Model. When estimating the cumulative distribution function, metamodels are more than 100 times faster than the mechanistic model and the error is less than ten percent when compared with the mechanistic model. Kriging and the Radial Basis Function are more accurate than the Regression Model and computation time is faster using the Monte Carlo Simulation to estimate probability than using the First-Order Reliability Method.