Blending the physical and the digital through conceptual spaces

The rise of the Internet facilitates an ever increasing growth of virtual, i.e. digital spaces which co-exist with the physical environment, i.e. the physical space. In that, the question arises, how physical and digital space can interact synchronously. While sensors provide a means to continuously observe the physical space, several issues arise with respect to mapping sensor data streams to digital spaces, for instance, structured linked data, formally represented through symbolic Semantic Web (SW) standards such as OWL or RDF. The challenge is to bridge between symbolic knowledge representations and the measured data collected by sensors. In particular, one needs to map a given set of arbitrary sensor data to a particular set of symbolic knowledge representations, e.g. ontology instances. This task is particularly challenging due to the vast variety of possible sensor measurements. Conceptual Spaces (CS) provide a means to represent knowledge in geometrical vector spaces in order to enable computation of similarities between knowledge entities by means of distance metrics. We propose an approach which allows to refine symbolic concepts as CS and to ground ontology instances to so-called prototypical members which are vectors in the CS. By computing similarities in terms of spatial distances between a given set of sensor measurements and a finite set of CS members, the most similar instance can be identified. In that, we provide a means to bridge between the physical space, as observed by sensors, and the digital space made up of symbolic representations

Music identification by Leadsheets

Most experimental research on content-based automatic recognition and identification of musical documents is founded on statistical distribution of timbre or simple retrieval mechanisms like comparison of melodic segments. Therefore often a vast number of relevant and irrelevant hits including multiple appearances of the same documents are returned or the actual document can’t be revealed at all. To improve this situation we propose a model for recognition of music that enables identification and comparison of musical documents without dependence on their actual instantiation. The resulting structures enclose musical meaning and can be used for estimation of identity and semantic relationship between musical documents

A self-adaptive insert strategy for content-based multidimensional database storage

In this paper, we present the current development progress of our dynamic insert strategy based on the Intelligent Cluster Index (ICIx), which is a new type of multidimensional database storage. Opposite to purely value-based interval methods, ICIx performs a semantic clustering of the data objects in a database and keeps the clustering results as basis for storing in a special tree structure (V-Tree). Our paper aims at the quality problem caused by a trade-off between the static clustering that results from the initial training data set and the continuous insertion of data into a database which requires a continuous classification. The strategy that we propose will solve this problem through a continuous and effcient content-based growing of the initially static clustering. We have developed an additional structure - the C-Tree - which stores the knowlege of the hierarchical clustering component, i.e. hierarchical Growing Neural Gas (GNG), for unsupervised content based classification. In contrast to other methods (e.g. dynamic versions of R-Trees) we use the C-Tree to process the new tuple. Furthermore, we use a Bayesian approach to determine the degree of adaptation of the knowledge base. Using this value, we update the knowlege base and propagate the resulting changes to the V-Tree. As a result, we obtain a continuous content-based growing

A New Approach to Cluster Visualization Methods Based on Self-Organizing Maps

The Self-Organizing Map (SOM) is one of the artificial neural networks that perform vector quantization and vector projection simultaneously. Due to this characteristic, a SOM can be visualized twice: through the out-put space, which means considering the vector projection perspective, and through the input data space, em-phasizing the vector quantization process. This paper aims at the idea of presenting high-dimensional clusters that are ‘disjoint objects’ as groups of pairwise disjoint simple geometrical objects – like 3D-spheres for in-stance. We expand current cluster visualization methods to gain better overview and insight into the existing clusters. We analyze the classical SOM model, insisting on the topographic product as a measure of degree of topology preservation and treat that measure as a judge tool for admissible neural net dimension in dimension reduction process. To achieve better performance and more precise results we use the SOM batch algorithm with toroidal topology. Finally, a software solution of the approach for mobile devices like iPad is presente

Profillinie 4: Kundenorientierte Gestaltung von vernetzten Wertschöpfungsketten:

Wertschöpfungsstrukturen in der Gesellschaft passen sich vor dem Hintergrund globaler Herausforderungen sehr flexibel und dynamisch an ständig neue Anforderungen an. Innovative Wertschöpfung kann dabei immer weniger von einzelnen Akteuren in Wissenschaft, Technik, Wirtschaft und Gesellschaft geleistet werden, sondern verschiedene interdisziplinäre Kompetenzen müssen gebündelt werden, die zielorientierte Vernetzung von Wissen und Ressourcen muss gestaltet werden. Unbestechlicher Maßstab für den Erfolg jeglicher wirtschaftlicher Unternehmung und damit auch von vernetzten Wertschöpfungsketten ist der Kunde mit seinen individuellen Bedürfnissen, das heißt letztlich die Akzeptanz und Absatzchancen von Produkten und Dienstleistungen am Markt

Mitochondrial DNA haplogroup T is associated with coronary artery disease and diabetic retinopathy: a case control study

<p>Abstract</p> <p>Background</p> <p>There is strong and consistent evidence that oxidative stress is crucially involved in the development of atherosclerotic vascular disease. Overproduction of reactive oxygen species (ROS) in mitochondria is an unifying mechanism that underlies micro- and macrovascular atherosclerotic disease. Given the central role of mitochondria in energy and ROS production, mitochondrial DNA (mtDNA) is an obvious candidate for genetic susceptibility studies on atherosclerotic processes. We therefore examined the association between mtDNA haplogroups and coronary artery disease (CAD) as well as diabetic retinopathy.</p> <p>Methods</p> <p>This study of Middle European Caucasians included patients with angiographically documented CAD (n = 487), subjects with type 2 diabetes mellitus with (n = 149) or without (n = 78) diabetic retinopathy and control subjects without clinical manifestations of atherosclerotic disease (n = 1527). MtDNA haplotyping was performed using multiplex PCR and subsequent multiplex primer extension analysis for determination of the major European haplogroups. Haplogroup frequencies of patients were compared to those of control subjects without clinical manifestations of atherosclerotic disease.</p> <p>Results</p> <p>Haplogroup T was significantly more prevalent among patients with CAD than among control subjects (14.8% vs 8.3%; p = 0.002). In patients with type 2 diabetes, the presence of diabetic retinopathy was also significantly associated with a higher prevalence of haplogroup T (12.1% vs 5.1%; p = 0.046).</p> <p>Conclusion</p> <p>Our data indicate that the mtDNA haplogroup T is associated with CAD and diabetic retinopathy in Middle European Caucasian populations.</p

Bifunctional Anti-Huntingtin Proteasome-Directed Intrabodies Mediate Efficient Degradation of Mutant Huntingtin Exon 1 Protein Fragments

Huntington's disease (HD) is a fatal autosomal dominant neurodegenerative disorder caused by a trinucleotide (CAG)n repeat expansion in the coding sequence of the huntingtin gene, and an expanded polyglutamine (>37Q) tract in the protein. This results in misfolding and accumulation of huntingtin protein (htt), formation of neuronal intranuclear and cytoplasmic inclusions, and neuronal dysfunction/degeneration. Single-chain Fv antibodies (scFvs), expressed as intrabodies that bind htt and prevent aggregation, show promise as immunotherapeutics for HD. Intrastriatal delivery of anti-N-terminal htt scFv-C4 using an adeno-associated virus vector (AAV2/1) significantly reduces the size and number of aggregates in HDR6/1 transgenic mice; however, this protective effect diminishes with age and time after injection. We therefore explored enhancing intrabody efficacy via fusions to heterologous functional domains. Proteins containing a PEST motif are often targeted for proteasomal degradation and generally have a short half life. In ST14A cells, fusion of the C-terminal PEST region of mouse ornithine decarboxylase (mODC) to scFv-C4 reduces htt exon 1 protein fragments with 72 glutamine repeats (httex1-72Q) by ∼80–90% when compared to scFv-C4 alone. Proteasomal targeting was verified by either scrambling the mODC-PEST motif, or via proteasomal inhibition with epoxomicin. For these constructs, the proteasomal degradation of the scFv intrabody proteins themselves was reduced<25% by the addition of the mODC-PEST motif, with or without antigens. The remaining intrabody levels were amply sufficient to target N-terminal httex1-72Q protein fragment turnover. Critically, scFv-C4-PEST prevents aggregation and toxicity of httex1-72Q fragments at significantly lower doses than scFv-C4. Fusion of the mODC-PEST motif to intrabodies is a valuable general approach to specifically target toxic antigens to the proteasome for degradation

Lifelong Reduction of LDL-Cholesterol Related to a Common Variant in the LDL-Receptor Gene Decreases the Risk of Coronary Artery Disease—A Mendelian Randomisation Study

Rare mutations of the low-density lipoprotein receptor gene (LDLR) cause familial hypercholesterolemia, which increases the risk for coronary artery disease (CAD). Less is known about the implications of common genetic variation in the LDLR gene regarding the variability of cholesterol levels and risk of CAD.Imputed genotype data at the LDLR locus on 1 644 individuals of a population-based sample were explored for association with LDL-C level. Replication of association with LDL-C level was sought for the most significant single nucleotide polymorphism (SNP) within the LDLR gene in three European samples comprising 6 642 adults and 533 children. Association of this SNP with CAD was examined in six case-control studies involving more than 15 000 individuals.Each copy of the minor T allele of SNP rs2228671 within LDLR (frequency 11%) was related to a decrease of LDL-C levels by 0.19 mmol/L (95% confidence interval (CI) [0.13-0.24] mmol/L, p = 1.5x10(-10)). This association with LDL-C was uniformly found in children, men, and women of all samples studied. In parallel, the T allele of rs2228671 was associated with a significantly lower risk of CAD (Odds Ratio per copy of the T allele: 0.82, 95% CI [0.76-0.89], p = 2.1x10(-7)). Adjustment for LDL-C levels by logistic regression or Mendelian Randomisation models abolished the significant association between rs2228671 with CAD completely, indicating a functional link between the genetic variant at the LDLR gene locus, change in LDL-C and risk of CAD.A common variant at the LDLR gene locus affects LDL-C levels and, thereby, the risk for CAD

Repositioning of the global epicentre of non-optimal cholesterol

High blood cholesterol is typically considered a feature of wealthy western countries(1,2). However, dietary and behavioural determinants of blood cholesterol are changing rapidly throughout the world(3) and countries are using lipid-lowering medications at varying rates. These changes can have distinct effects on the levels of high-density lipoprotein (HDL) cholesterol and non-HDL cholesterol, which have different effects on human health(4,5). However, the trends of HDL and non-HDL cholesterol levels over time have not been previously reported in a global analysis. Here we pooled 1,127 population-based studies that measured blood lipids in 102.6 million individuals aged 18 years and older to estimate trends from 1980 to 2018 in mean total, non-HDL and HDL cholesterol levels for 200 countries. Globally, there was little change in total or non-HDL cholesterol from 1980 to 2018. This was a net effect of increases in low- and middle-income countries, especially in east and southeast Asia, and decreases in high-income western countries, especially those in northwestern Europe, and in central and eastern Europe. As a result, countries with the highest level of non-HDL cholesterol-which is a marker of cardiovascular riskchanged from those in western Europe such as Belgium, Finland, Greenland, Iceland, Norway, Sweden, Switzerland and Malta in 1980 to those in Asia and the Pacific, such as Tokelau, Malaysia, The Philippines and Thailand. In 2017, high non-HDL cholesterol was responsible for an estimated 3.9 million (95% credible interval 3.7 million-4.2 million) worldwide deaths, half of which occurred in east, southeast and south Asia. The global repositioning of lipid-related risk, with non-optimal cholesterol shifting from a distinct feature of high-income countries in northwestern Europe, north America and Australasia to one that affects countries in east and southeast Asia and Oceania should motivate the use of population-based policies and personal interventions to improve nutrition and enhance access to treatment throughout the world.Peer reviewe

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions