A personal voice analyzer and trainer

This paper presents a personal voice analyzer and trainer that allow the user to perform four daily exercises to improve the voice capacity. The system grades how well the user is performing the exercises by analyzing the duration, the intensity and the pitch of the user’s voice

A European industrial development policy for prosperity and zero emissions

The objective of this paper is to outline and discuss the key elements of an EU industrial development policy consistent with the Paris Agreement. We also assess the current EU Industrial Strategy proposal against these elements. The “well below 2 °C” target sets a clear limit for future global greenhouse gas emissions and thus strict boundaries for the development of future material demand, industrial processes and the sourcing of feedstock; industry must evolve to zero emissions or pay for expensive negative emissions elsewhere. An industrial policy for transformation to net-zero emissions must include attention to directed technological and economic structural change, the demand for emissions intensive products and services, energy and material efficiency, circular economy, electrification and other net-zero fuel switching, and carbon capture and use or storage (CCUS). It may also entail geographical relocation of key basic materials industries to regions endowed with renewable energy. In this paper we review recent trends in green industrial policy. We find that it has generally focused on promoting new green technologies (e.g., PVs, batteries, fuel cells and biorefineries) rather than on decarbonizing the emissions intensive basic materials industries, or strategies for handling the phase-out or repurposing of sunset industries (e.g., replacing fossil fuel feedstocks for chemicals). Based on knowledge about industry and potential mitigation options, and insights from economics, governance and innovation studies, we propose a framework for the purpose of developing and evaluating industrial policy for net-zero emissions. This framework recognizes the need for: directionality; innovation; creating lead markets for green materials and reshaping existing markets; building capacity for governance and change; coherence with the international climate policy regime; and finally the need for a just transition. We find the announced EU Industrial Strategy to be strong on most elements, but weak on transition governance approaches, the need for capacity building, and creating lead markets

Analysis of Factors that Affect Player Performance in E-Sports

I denna rapport presenteras en analys av hur olika faktorer påverkar en spelares prestanda inom E-sport. Fokus ligger på tre välkända FPS (first-person shooter) spel och målet med studien är att konstatera vilka faktorer som utmärker spelare som presterar på den högsta möjliga nivån. De faktorer som används som förklaringsvariabler i analysen anses vara speloberoende och dessa är bland andra muskänslighet, skärmupplösning, skärmuppdateringsfrekvens, nerlagd tid på spelet och spelarens ålder. Prestandan mäts på olika sätt fär olika spel i analysen på grund av spelegenskaper och tillgängliga statistiska data för spelen. Den största delen av datan har hämtats från olika hemsidor där information om spelares inställningar och resultat från turneringar finns tillgängligt. Datan undersöks sedan med hjälp av teori från regressionsanalys för att bekräfta lämpligheten och därefter tillämpas en multivariat linjär regressionsanalys. Totalt undersöks 11 modeller i denna studie och resultaten från dessa modeller har olika förklaringsgrad. De faktorer som visade sig ha betydelse för prestationsmåtten var framför allt spelarens muskänslighet, nerlagd tid på spelet ochskärmupplösning. Vidare diskuteras resultatens giltighet utifrån litteraturstudier och fakta om spelen som används i studien. Slutligen ges även rekommendationer för framtida studier och möjligaförbättringar.This report presents an analysis of how different factors influence a players performance in E-sports. Focus is put on three well-known FPS (first-person shooter) games and the aim of the study is to establish which factors distinguish players who perform at the highest possible level. The factors being used as explanatory variables are assumed to be game-independent and these are, among others, mouse sensitivity, screen resolution, screen refresh rate, time spent on the game and players age. Performance is measured differently for different games in the analysis due to properties of games and available statistical data for the games. The main portion of the data has been gathered from different websites where player settings information and results from tournaments are available. The data is examined through the lens of theory from regression analysis in order to deem its suitability and thereafter a multivariate linear regression analysis is applied. In total 11 models are investigated in this study and results from these models have various degress of explanatory power. The factors shown to have meaning for performance measures was primarily mouse sensitivity, time spent on the game och screen resolution. Further the validity of the results are discussed based on literature reviews and knowledge of the games used in the study. Finally recommendations are given for future studies and possible improvements

Analysis of Factors that Affect Player Performance in E-Sports

I denna rapport presenteras en analys av hur olika faktorer påverkar en spelares prestanda inom E-sport. Fokus ligger på tre välkända FPS (first-person shooter) spel och målet med studien är att konstatera vilka faktorer som utmärker spelare som presterar på den högsta möjliga nivån. De faktorer som används som förklaringsvariabler i analysen anses vara speloberoende och dessa är bland andra muskänslighet, skärmupplösning, skärmuppdateringsfrekvens, nerlagd tid på spelet och spelarens ålder. Prestandan mäts på olika sätt fär olika spel i analysen på grund av spelegenskaper och tillgängliga statistiska data för spelen. Den största delen av datan har hämtats från olika hemsidor där information om spelares inställningar och resultat från turneringar finns tillgängligt. Datan undersöks sedan med hjälp av teori från regressionsanalys för att bekräfta lämpligheten och därefter tillämpas en multivariat linjär regressionsanalys. Totalt undersöks 11 modeller i denna studie och resultaten från dessa modeller har olika förklaringsgrad. De faktorer som visade sig ha betydelse för prestationsmåtten var framför allt spelarens muskänslighet, nerlagd tid på spelet ochskärmupplösning. Vidare diskuteras resultatens giltighet utifrån litteraturstudier och fakta om spelen som används i studien. Slutligen ges även rekommendationer för framtida studier och möjligaförbättringar.This report presents an analysis of how different factors influence a players performance in E-sports. Focus is put on three well-known FPS (first-person shooter) games and the aim of the study is to establish which factors distinguish players who perform at the highest possible level. The factors being used as explanatory variables are assumed to be game-independent and these are, among others, mouse sensitivity, screen resolution, screen refresh rate, time spent on the game and players age. Performance is measured differently for different games in the analysis due to properties of games and available statistical data for the games. The main portion of the data has been gathered from different websites where player settings information and results from tournaments are available. The data is examined through the lens of theory from regression analysis in order to deem its suitability and thereafter a multivariate linear regression analysis is applied. In total 11 models are investigated in this study and results from these models have various degress of explanatory power. The factors shown to have meaning for performance measures was primarily mouse sensitivity, time spent on the game och screen resolution. Further the validity of the results are discussed based on literature reviews and knowledge of the games used in the study. Finally recommendations are given for future studies and possible improvements

Assessing Low Carbon Transitions : A Conceptual Model

The present report presents a conceptual assessment model or framework for policy relevant analysis of low carbon transitions. The aim of the study is not to present specific guidelines for how to design assessments of low carbon transitions, but rather to give food for thought on aspects that should be regarded in the design process. The exact design would then depend on the purpose of the assessment, the scope and priorities set for the assessment, and the resources (personal and financial) available for the assessments.We find that there are at least three elements of an assessment model that are important to provide policy relevant knowledge: i) monitoring, ii) policy evaluation, and iii) domain knowledge building processes, including research. Monitoring is here understood as a process that is intended to inform whether society is on track on meeting set-up political priorities. Policy evaluation concentrates on the effects of low carbon transition policies and effects of other policies. Domain knowledge building through research and other processes is important both for identifying relevant assessment criteria and designing monitoring systems, as well as for policy evaluations. A domain knowledge base can include knowledge of i) drivers and barriers for low carbon transitions, ii) the sustainability of various technologies, policies and practices, iii) previous policy experiences, and iv) contextual knowledge of the market, actors, mitigation technologies and pathways, etc. in various sectors. This information and background knowledge will help inform how policies can be redesigned for overcoming the barriers and enable change in various contexts while safeguarding that the changes are not in conflict with other key societal goals and sustainability aspects. Monitoring can cover direct outcomes such as greenhouse gas emissions or diffusion of low carbon technologies. But with a long-term transitions perspective it is also important to look into the preparedness for change with regard to existence of factors such as visions and expectations, knowledge, feasible policies and policy instruments (taking into account stringency as well as coverage and policy coherence), societal norms, innovation networks, or the readiness of key technologies.Evaluation of policies can in turn cover several aspects beyond policy relevance and effectiveness including synergies and conflicts with other objectives. It could also evaluate the consistency of targets with overarching objectives as well as specific strategies, policy instruments or policy packages. In the conceptual assessment model, policy adjustments are expected to be informed by the monitoring process regarding what is needed and by policy evaluation with regard to what works. Together these processes can inform on how both the stringency and the design of policies could be developed over time

A Personal Voice Analyzer and Trainer

This paper presents a personal voice analyzer and trainer that allow the user to perform four daily exercises to improve the voice capacity. The system grades how well the user is performing the exercises by analyzing the duration, the intensity and the pitch of the user’s voice

Streptococcal M protein promotes IL-10 production by cGAS-independent activation of the STING signaling pathway

From an evolutionary point of view a pathogen might benefit from regulating the inflammatory response, both in order to facilitate establishment of colonization and to avoid life-threatening host manifestations, such as septic shock. In agreement with this notion Streptococcus pyogenes exploits type I IFN-signaling to limit detrimental inflammation in infected mice, but the host-pathogen interactions and mechanisms responsible for induction of the type I IFN response have remained unknown. Here we used a macrophage infection model and report that S. pyogenes induces anti-inflammatory IL-10 in an M protein-dependent manner, a function that was mapped to the B- and C-repeat regions of the M5 protein. Intriguingly, IL-10 was produced downstream of type I IFN-signaling, and production of type I IFN occurred via M protein-dependent activation of the STING signaling pathway. Activation of STING was independent of the cytosolic double stranded DNA sensor cGAS, and infection did not induce detectable release into the cytosol of either mitochondrial, nuclear or bacterial DNA–indicating DNA-independent activation of the STING pathway in S. pyogenes infected macrophages. These findings provide mechanistic insight concerning how S. pyogenes induces the type I IFN response and identify a previously unrecognized macrophage-modulating role for the streptococcal M protein that may contribute to curb the inflammatory response to infection

Serum from patients with systemic vasculitis induces alternatively activated macrophage M2c polarization.

Anti-neutrophil cytoplasmic antibody associated vasculitides (AAV) are conditions defined by an autoimmune small vessel inflammation. Dying neutrophils are found around the inflamed vessels and the balance between infiltrating neutrophils and macrophages is important to prevent autoimmunity. Here we investigate how sera from AAV patients may regulate macrophage polarization and function. Macrophages from healthy individuals were differentiated into M0, M1, M2a, M2b or M2c macrophages using a standardized protocol, and phenotyped according to their expression surface markers and cytokine production. These phenotypes were compared with those of macrophages stimulated with serum from AAV patients or healthy controls. While the healthy control sera induced a M0 macrophage, AAV serum promoted polarization towards the M2c subtype. No sera induced M1, M2a or M2b macrophages. The M2c subtype showed increased phagocytosis capacity compared with the other subtypes. The M2c polarization found in AAV is consistent with previous reports of increased levels of M2c-associated cytokines

M5 protein-dependent type I IFN-signaling is required for secretion of IL-10.

<p><b>A)</b> B6 macrophages were infected with M5 or ΔM5 bacteria, as indicated. Macrophages were lysed at the indicated time points (hours) post infection and analyzed for activation of Stat1 and Stat2 by Western blot. Uninfected (UI) macrophages were analyzed as control. Activated (<i>i</i>.<i>e</i>. phosphorylated) transcription factors were detected with phospho-specific primary antibodies (indicated with p). Shown is one experiment representative of three. <b>B)</b> B6 macrophages were infected with M5 or ΔM5 for 4 hours, and IFNβ transcripts were measured by RTqPCR. mRNA levels are presented as fold-change relative to UI control macrophages. Results shown (mean and SD; <i>n</i> = 3 per group) are representative of three independent experiments. <b>C)</b> Kinetic analysis of IFNβ secretion from B6 macrophages infected as indicated. Results shown (mean; <i>n</i> = 2 per group) are representative of two independent experiments. <b>D)</b> B6 and IFNAR-KO macrophages were infected with M5 or ΔM5, or UI, as indicated. Culture supernatants were collected 24 hpi and assayed for indicated cytokines. Results shown (mean and SD; <i>n</i> = 3 per group) are representative of three independent experiments. <b>E)</b> B6 macrophages were infected with wild type M5 bacteria in the presence of titrated amounts (final concentration indicated) of a neutralizing anti-mouse IFNAR mAb or mouse IgG1 isotype control, as indicated. UI macrophages treated with the anti-IFNAR mAb were analyzed as control. Cytokines were assayed 24 hpi. Results shown (mean and SD; <i>n</i> = 3 per group) are representative of two independent experiments. <b>F)</b> B6 and IFNAR-KO macrophages were infected with <i>S</i>. <i>pyogenes</i> strains of six different serotypes (two that are serum opacity factor positive [OF⁺], and four that are OF^-), as indicated. Cytokines were assayed 24 hpi. Results shown (mean and SD; <i>n</i> = 3 per group) are representative of two independent experiments. ANOVA (*<0.033; **<0.002; ***<0.001).</p

<i>S</i>. <i>pyogenes</i> does not cause detectable release of DNA of any origin into the cytosol of infected macrophages.

<p><b>A)</b> B6 macrophages were infected with M5 or ΔM5, and UI macrophages served as control. At the indicated time points post infection the levels of mitochondrial (<i>Dloop1</i>), nuclear (<i>Tert</i>) or <i>S</i>. <i>pyogenes</i> (<i>SortA</i>) DNA in the cytosolic compartment was analyzed by qPCR as described in materials and methods. <b>B)</b> Same analysis as A) above, but in macrophages infected with wild type <i>M</i>. <i>marinum</i> (Mmar) or an isogenic ESX-1-deficient mutant (MmarΔRD1). <i>FurA</i> was measured to determine the level of <i>M</i>. <i>marinum</i> DNA in the cytosolic compartment of infected macrophages. For A) and B) the results shown (mean and SD; <i>n</i> = 3 per group) are representative of three independent experiments. <b>C)</b> B6, cGAS-KO and STING-KO macrophages were infected with Mmar or MmarΔRD1 as indicated, and cytokine output was assayed 24 hpi. Results shown (mean and SD; <i>n</i> = 3 per group) are representative of two independent experiments. ANOVA (*<0.033; **<0.002; ***<0.001).</p