The Tabby phenotype is caused by mutation in a mouse homologue of the EDA gene that reveals novel mouse and human exons and encodes a protein (ectodysplasin-A) with collagenous domains

Mouse Tabby (Ta) and X chromosome-linked human EDA share the features of hypoplastic hair, teeth, and eccrine sweat glands. We have cloned the Ta gene and find it to be homologous to the EDA gene. The gene is altered in two Ta alleles with a point mutation or a deletion. The gene is expressed in developing teeth and epidermis; no expression is seen in corresponding tissues from Ta mice. Ta and EDA genes both encode alternatively spliced forms; novel exons now extend the 3′ end of the EDA gene. All transcripts recovered have the same 5′ exon. The longest Ta cDNA encodes a 391-residue transmembrane protein, ectodysplasin-A, containing 19 Gly-Xaa-Yaa repeats. The isoforms of ectodysplasin-A may correlate with differential roles during embryonic development.

Open randomised study of use of levonorgestrel releasing intrauterine system as alternative to hysterectomy

Objectives: To assess whether the levonorgestrel intrauterine system could provide a conservative alternative to hysterectomy in the treatment of excessive uterine bleeding.

Inherited susceptibility to uterine leiomyomas and renal cell cancer

Herein we report the clinical, histopathological, and molecular features of a cancer syndrome with predisposition to uterine leiomyomas and papillary renal cell carcinoma. The studied kindred included 11 family members with uterine leiomyomas and two with uterine leiomyosarcoma. Seven individuals had a history of cutaneous nodules, two of which were confirmed to be cutaneous leiomyomatosis. The four kidney cancer cases occurred in young (33- to 48-year-old) females and displayed a unique natural history. All these kidney cancers displayed a distinct papillary histology and presented as unilateral solitary lesions that had metastasized at the time of diagnosis. Genetic-marker analysis mapped the predisposition gene to chromosome 1q. Losses of the normal chromosome 1q were observed in tumors that had occurred in the kindred, including a uterine leiomyoma. Moreover, the observed histological features were used as a tool to diagnose a second kindred displaying the phenotype. We have shown that predisposition to uterine leiomyomas and papillary renal cell cancer can be inherited dominantly through the hereditary leiomyomatosis and renal cell cancer (HLRCC) gene. The HLRCC gene maps to chromosome 1q and is likely to be a tumor suppressor. Clinical, histopathological, and molecular tools are now available for accurate detection and diagnosis of this cancer syndrome.

Farm-level Capital: Capital positions, structures, the dynamics of farm-level investments, capital accumulation and leverage positions. Factor Markets Working Paper No. 7, October 2011

This Factor Markets Working Paper describes and highlights the key issues of farm capital structures, the dynamics of investments and accumulation of farm capital, and the financial leverage and borrowing rates on farms in selected European countries. Data collected from the Farm Account Data Network (FADN) suggest that the European farming sector uses quite different farm business strategies, capabilities to generate capital revenues, and segmented agricultural loan market regimes. Such diverse business strategies have substantial, and perhaps more substantial than expected, implications for the financial leverage and performance of farms. Different countries adopt different approaches to evaluating agricultural assets, or the agricultural asset markets simply differ substantially depending on the country in question. This has implications for most of the financial indicators. In those countries that have seen rapidly increasing asset prices at the margin, which were revised accordingly in the accounting systems for the whole stock of assets, firm values increased significantly, even though the firms had been disinvesting. If there is an asset price bubble and it bursts, there may be serious knock-on effects for some countries.

Effects of Economic Factors on Adoption of Robotics and Consequences of Automation for Productivity Growth of Dairy Farms. Factor Markets Working Paper No. 32, December 2012

In the long term, productivity and especially productivity growth are necessary conditions for the survival of a farm. This paper focuses on the technology choice of a dairy farm, i.e. the choice between a conventional and an automatic milking system. Its aim is to reveal the extent to which economic rationality explains investing in new technology. The adoption of robotics is further linked to farm productivity to show how capital-intensive technology has affected the overall productivity of milk production. The empirical analysis applies a probit model and an extended Cobb-Douglas-type production function to a Finnish farm-level dataset for the years 2000–10. The results show that very few economic factors on a dairy farm or in its economic environment can be identified to affect the switch to automatic milking. Existing machinery capital and investment allowances are among the significant factors. The results also indicate that the probability of investing in robotics responds elastically to a change in investment aids: an increase of 1% in aid would generate an increase of 2% in the probability of investing. Despite the presence of non-economic incentives, the switch to robotic milking is proven to promote productivity development on dairy farms. No productivity growth is observed on farms that keep conventional milking systems, whereas farms with robotic milking have a growth rate of 8.1% per year. The mean rate for farms that switch to robotic milking is 7.0% per year. The results show great progress in productivity growth, with the average of the sector at around 2% per year during the past two decades. In conclusion, investments in new technology as well as investment aids to boost investments are needed in low-productivity areas where investments in new technology still have great potential to increase productivity, and thus profitability and competitiveness, in the long run.

Calcareous dinoflagellates in the eastern equatorial Atlantic

Sediments of the Equatorial Atlantic (core GeoB 1105-4) have been investigated for both calcareous dinoflagellates and organic-walled dinoflagellate cysts. In order to determine the ecological affinity of calcareous dinoflagellates the statistical methods of Detrended Correspondence Analysis (DCA) and Redundancy Analysis (RDA) were used. Utilising DCA, distribution patterns of calcareous dinoflagellates have been compared with those of the ecologically much better known organic-walled dinoflagellate cysts. This method was also used to determine which environmental gradients have a major influence on the species composition. By using existing environmental information based on benthic and planktic foraminifera, such as Sea Surface Temperature (SST) and stable oxygen and carbon isotopes, as well as information on the amount of Calcium Carbonate and Total Organic Carbon (TOC) in bottom sediments, these gradients could be interpreted in terms of productivity and glacial-interglacial trends. Using RDA, the direct relationships between the distribution patterns of calcareous dinoflagellates with the above mentioned external variables could be determined. For the studied region and time interval (141-6.7 ka) the calcareous dinoflagellates show enhanced abundances in periods with reduced productivity most probably related to decreased divergence and relatively stratified, oligotrophic oceanic conditions.

Polisen i förändring : En fallstudie om Polismyndighetens upphandling av kommunikationstjänster från PR-byrån Prime

Polismyndigheten har under 2015 påbörjat och ska under 2016 fortsätta undergå en omorganisering. En del av omorganiseringen innefattar att Polismyndigheten skrivit ett fyraårigt kontrakt värderat till 35 miljoner kronor med Prime Public Relations AB med avseende upphandling av strategiska kommunikationstjänster. Studien syftar till att undersöka vad skälen är till att Polismyndigheten har valt att en PR-byrå ska sköta delar av deras kommunikation och vad det hittills fått för konsekvenser. Totalt analyseras 50 artiklar som publicerats under upphandlingstiden i en innehållsanalys för att få en överblick kring olika teman som framkommit. Innehållsanalysen fungerar som ett kvantitativt komplement till två semi-strukturerade intervjuer samt en mailkorrespondens med projektansvarig för samarbetet med Polismyndigheten på Prime. En av intervjuerna hölls med en tidigare presstalesperson för Polismyndigheten som nu är kommunikationskonsult med uppdrag inom bland annat kriskommunikation. Den andra intervjun hölls med ansvarig handläggare för upphandlingen hos Polismyndigheten. En enkät kompletterar materialet med utomstående åsikter kring förändring av förtroendet för polisen i samband med upphandlingen. Tillsammans bidrar metoderna till ett gediget material för fallstudien som blir belyst från olika håll både med hjälp av kvalitativ samt kvantitativ data. Resultaten leder fram till en diskussion kring organisationskommunikation och intern kritik från anställda poliser som en produkt av upphandlingen. Analysen tar även upp de anställdas meningsskapande av den nya kontexten inom myndigheten samt en diskussion om förtroende och huruvida situationen kring upphandlingen skulle kunna ha sköts på ett annat sätt för att undvika negativa konsekvenser. 

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. ^ In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. ^ The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area. ^

A generic model of execution for synthesizing domain-specific models

Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

The role of market knowledge in recognizing and exploiting entrepreneurial opportunities in technology intensive firms

Entrepreneurial opportunity recognition is an increasingly prevalent phenomenon. Of particular interest is the ability of promising technology based ventures to recognize and exploit opportunities. Recent research drawing on the Austrian economic theory emphasizes the importance of knowledge, particularly market knowledge, behind opportunity recognition. While insightful, this research has tended to overlook those interrelationships that exist between different types of knowledge (technology and market knowledge) as well as between a firm’s knowledge base and its entrepreneurial orientation. Additional shortfalls of prior research include the ambiguous definitions provided for entrepreneurial opportunities, oversight of opportunity exploitation with an extensive focus on opportunity recognition only, and the lack of quantitative, empirical evidence on entrepreneurial opportunity recognition. In this dissertation, these research gaps are addressed by integrating Schumpeterian opportunity development view with a Kirznerian opportunity discovery theory as well as insights from literature on entrepreneurial orientation. A sample of 85 new biotechnology ventures from the United States, Finland, and Sweden was analyzed. While leaders in all 85 companies were interviewed for the research in 2003-2004, 42 firms provided data in 2007. Data was analyzed using regression analysis. The results show the value and importance of early market knowledge and technology knowledge as well as an entrepreneurial company posture for subsequent opportunity recognition. The highest numbers of new opportunities are recognized in firms where high levels of market knowledge are combined with high levels of technology knowledge (measured with a number of patents). A firm’s entrepreneurial orientation also enhances its opportunity recognition. Furthermore, the results show that new ventures with more market knowledge are able to gather more equity investments, license out more technologies, and achieve higher sales than new ventures with lower levels of market knowledge. Overall, the findings of this dissertation help further our understanding of the sources of entrepreneurial opportunities, and should encourage further research in this area.

Enhanced Volatile Organic Compounds emissions and organic aerosol mass increase the oligomer content of atmospheric aerosols

Secondary organic aerosol (SOA) accounts for a dominant fraction of the submicron atmospheric particle mass, but knowledge of the formation, composition and climate effects of SOA is incomplete and limits our understanding of overall aerosol effects in the atmosphere. Organic oligomers were discovered as dominant components in SOA over a decade ago in laboratory experiments and have since been proposed to play a dominant role in many aerosol processes. However, it remains unclear whether oligomers are relevant under ambient atmospheric conditions because they are often not clearly observed in field samples. Here we resolve this long-standing discrepancy by showing that elevated SOA mass is one of the key drivers of oligomer formation in the ambient atmosphere and laboratory experiments. We show for the first time that a specific organic compound class in aerosols, oligomers, is strongly correlated with cloud condensation nuclei (CCN) activities of SOA particles. These findings might have important implications for future climate scenarios where increased temperatures cause higher biogenic volatile organic compound (VOC) emissions, which in turn lead to higher SOA mass formation and significant changes in SOA composition. Such processes would need to be considered in climate models for a realistic representation of future aerosol-climate-biosphere feedbacks.

A Generic Model of Execution for Synthesizing Domain-Specific Models

Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code. Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process. The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources. At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM’s synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise. This dissertation investigates how to decouple the DSK from the MoE and sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions. This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.