Acumen : an open-source testbed for cyber-physical systems research

Developing Cyber-Physical Systems requires methods and tools to support simulation and verification of hybrid (both continuous and discrete) models. The Acumen modeling and simulation language is an open source testbed for exploring the design space of what rigorousbut- practical next-generation tools can deliver to developers of Cyber- Physical Systems. Like verification tools, a design goal for Acumen is to provide rigorous results. Like simulation tools, it aims to be intuitive, practical, and scalable. However, it is far from evident whether these two goals can be achieved simultaneously. This paper explains the primary design goals for Acumen, the core challenges that must be addressed in order to achieve these goals, the “agile research method” taken by the project, the steps taken to realize these goals, the key lessons learned, and the emerging language design

Affective recognition from EEG signals: an integrated data-mining approach

Emotions play an important role in human communication, interaction, and decision making processes. Therefore, considerable efforts have been made towards the automatic identification of human emotions, in particular electroencephalogram (EEG) signals and Data Mining (DM) techniques have been then used to create models recognizing the affective states of users. However, most previous works have used clinical grade EEG systems with at least 32 electrodes. These systems are expensive and cumbersome, and therefore unsuitable for usage during normal daily activities. Smaller EEG headsets such as the Emotiv are now available and can be used during daily activities. This paper investigates the accuracy and applicability of previous affective recognition methods on data collected with an Emotiv headset while participants used a personal computer to fulfill several tasks. Several features were extracted from four channels only (AF3, AF4, F3 and F4 in accordance with the 10–20 system). Both Support Vector Machine and Naïve Bayes were used for emotion classification. Results demonstrate that such methods can be used to accurately detect emotions using a small EEG headset during a normal daily activity

A Dynamic, Cost-Aware, Optimized Maintenance Policy for Interactive Exploration of Linked Data

Vast amounts of data, especially in biomedical research, are being published as Linked Data. Being able to analyze these data sets is essential for creating new knowledge and better decision support solutions. Many of the current analytics solutions require continuous access to these data sets. However, accessing Linked Data at query time is prohibitive due to high latency in searching the content and the limited capacity of current tools to connect to these databases. To reduce this overhead cost, modern database systems maintain a cache of previously searched content. The challenge with Linked Data is that databases are constantly evolving and cached content quickly becomes outdated. To overcome this challenge, we propose a Change-Aware Maintenance Policy (CAMP) for updating cached content. We propose a Change Metric that quantifies the evolution of a Linked Dataset and determines when to update cached content. We evaluate our approach on two datasets and show that CAMP can reduce maintenance costs, improve maintenance quality and increase cache hit rates compared to standard approaches

Promoting work ability with a wearable activity tracker in working age individuals with hip and/or knee osteoarthritis : a randomized controlled trial

Background: Physical activity (PA) may improve work ability and health in individuals with hip and/or knee osteoarthritis (OA). The use of wearable activity trackers (WATs) has been shown to increase PA and improve other health outcomes but little is known concerning their effect on work ability. The objectives of this study were to examine the effect of self-monitoring PA with a WAT on work ability, PA and work productivity among individuals of working age with hip and/or knee OA. Methods: Individuals (n = 160) were included and cluster-randomized to a Supported Osteoarthritis Self-management Program (SOASP) with the addition of self-monitoring PA using a commercial WAT for 12 weeks (n = 86), or only the SOASP (n = 74). Primary outcome was self-reported work ability measured with the Work Ability Index (WAI) and secondary outcomes were self-reported PA measured with the International Physical Activity Questionnaire – Short Form (IPAQ-SF) and work productivity, measured with the Work Productivity and Activity Impairment scale: Osteoarthritis (WPAI:OA) at baseline and after 3, 6 and 12 months. Data was primarily analysed with linear mixed models. Results: Participants with data from baseline and at least one follow-up were included in the analyses (n = 124). Linear mixed models showed no statistically significant difference between groups regarding pattern of change in work ability or PA, from baseline to follow-ups. Also, neither group had a statistically significant difference in work ability between baseline and each follow-up. Conclusion: The SOASP together with self-monitoring PA with a WAT did not have any effect on the primary outcome variable work ability. Participants already at baseline had good work ability and were physically active, which could have reduced the possibility for improvements. Future interventions should target a population with lower work ability and PA-level. Trial registration: ClinicalTrials.gov, NCT03354091. Registered 15/11/2017

Physical activity patterns, adherence to using a wearable activity tracker during a 12-week period and correlation between self-reported function and physical activity in working age individuals with hip and/or knee osteoarthritis

Background: A majority of individuals with osteoarthritis (OA) are insufficiently physically active. Self-monitoring with wearable activity trackers (WAT) could promote physical activity (PA), and increased knowledge of PA patterns and adherence to using a WAT is needed. The aim of this study was to describe PA patterns and adherence to WAT-use during an intervention among participants of working age with hip and/or knee OA. The study further explores the correlation between self-reported joint function and PA. Methods: Individuals of working age with hip and/or knee OA who used a WAT, Fitbit Flex 2, for 12 weeks were included. Participants monitored their PA in the Fitbit-app. An activity goal of 7,000 steps/day was set. Steps and minutes in light (L), moderate and vigorous (MV) PA were collected from the Fitbit. Self-reported joint function (HOOS/KOOS) was completed. Data was analyzed with linear mixed models and Spearman’s rank correlation. Results: Seventy-five participants (45–66 years) walked on average 10 593 (SD 3431) steps/day, spent 248.5 (SD 42.2) minutes in LPA/day, 48.1 (SD 35.5) minutes in MVPA/day, 336.0 (SD 249.9) minutes in MVPA/week and used the Fitbit for an average of 88.4 % (SD 11.6) of the 12-week period. 86.7 % took > 7,000 steps/day and 77.3 % spent > 150 min in MVPA/week. Mean daily steps/week decreased significantly over the 12 weeks (β-coefficient − 117, 95 % CI -166 to -68, p = < 0.001) as well as mean daily minutes in LPA/week (β-coefficient − 2.3, 95 % CI -3.3 to -1.4, p = < 0.001), mean daily minutes in MVPA/week (β-coefficient − 0.58, 95 % CI -1.01 to -0.16, p = 0.008) and mean adherence to Fitbit-use per week (β-coefficient − 1.3, 95 % CI -1.8 to -0.8, p = < 0.001). There were no significant correlations between function (HOOS/KOOS) and PA. Conclusions: The majority of participants reached 7,000 steps/day and the recommended 150 min in MVPA per week. However, PA decreased slightly but gradually over time. Adherence to using the Fitbit was high but also decreased during the intervention. Understanding PA patterns and the use of a Fitbit to promote PA could be beneficial in tailoring interventions for individuals with hip and/or knee OA

Associations Between Physical Activity, Self-reported Joint Function, and Molecular Biomarkers in Working Age Individuals With Hip and/or Knee Osteoarthritis

Objective: Previous research has suggested an association between physical activity (PA), joint function, and molecular biomarkers, but more studies are needed. The aim of this study was to explore the associations between PA or self-reported joint function and molecular biomarkers of cartilage and inflammation in individuals with hip and/or knee osteoarthritis (OA). Specific objectives were to explore the correlations between (1) the change over 3 months in self-reported PA/joint function and the change in molecular biomarkers (2) objectively measured PA and molecular biomarkers measured at 3-month follow-up. Design: Working age participants (n = 91) were recruited from a cluster randomized controlled trial. Self-reported PA, joint function, and serum samples were collected at baseline and after 3 months. Serum concentrations of the inflammatory marker C-reactive protein (CRP) and the cartilage markers Alanine-Arginine-Glycine-Serine (ARGS)-aggrecan, cartilage oligomeric matrix protein (COMP), and type II collagen C2C were analyzed by immunoassays. Objectively measured PA (steps/day) was collected during 12 weeks from activity trackers used by 53 participants. Associations were analyzed with Spearman’s rank correlation. Results: There was a weak negative correlation between the change in self-reported PA and the change in COMP (rs = −0.256, P =.040) but not for the other molecular biomarkers. There were no correlations between the change in self-reported joint function and the change in molecular biomarkers or between the average steps/day and the molecular biomarkers at follow-up (rs ⩽ −0.206, P ⩾.06). Conclusion: In general, no or only weak associations were found between PA/joint function and molecular biomarkers. Future research recommends including participants with lower PA, extend the follow-up, and use a design that allows comparisons

Clinical and Evolutionary Implications of Dynamic Coagulotoxicity Divergences in Bothrops (Lancehead Pit Viper) Venoms

Despite coagulotoxicity being a primary weapon for prey capture by Bothrops species (lancehead pit vipers) and coagulopathy being a major lethal clinical effect, a genus-wide comparison has not been undertaken. To fill this knowledge gap, we used thromboelastography to compare 37 venoms, from across the full range of geography, taxonomy, and ecology, for their action upon whole plasma and isolated fibrinogen. Potent procoagulant toxicity was shown to be the main venom effect of most of the species tested. However, the most basal species (B. pictus) was strongly anticoagulant; this is consistent with procoagulant toxicity being a novel trait that evolved within Bothrops subsequent to their split from anticoagulant American pit vipers. Intriguingly, two of the arboreal species studied (B. bilineatus and B. taeniatus) lacked procoagulant venom, suggesting differential evolutionary selection pressures. Notably, some terrestrial species have secondarily lost the procoagulant venom trait: the Mogi Mirim, Brazil locality of B. alternatus; San Andres, Mexico locality of B. asper; B. diporus; and the S&atilde;o Roque of B. jararaca. Direct action on fibrinogen was extremely variable; this is consistent with previous hypotheses regarding it being evolutionary decoupled due to procoagulant toxicity being the primary prey-capture weapon. However, human patients live long enough for fibrinogen depletion to be clinically significant. The extreme variability may be reflective of antivenom variability, with these results thereby providing a foundation for such future work of clinical relevance. Similarly, the venom diversification trends relative to ecological niche will also be useful for integration with natural history data, to reconstruct the evolutionary pressures shaping the venoms of these fascinating snakes

Environmental and genetic factors support the dissociation between α-synuclein aggregation and toxicity

Synucleinopathies are a group of progressive disorders characterized by the abnormal aggregation and accumulation of α-synuclein (aSyn), an abundant neuronal protein that can adopt different conformations and biological properties. Recently, aSyn pathology was shown to spread between neurons in a prion-like manner. Proteins like aSyn that exhibit self-propagating capacity appear to be able to adopt different stable conformational states, known as protein strains, which can be modulated both by environmental and by protein-intrinsic factors. Here, we analyzed these factors and found that the unique combination of the neurodegeneration-related metal copper and the pathological H50Q aSyn mutation induces a significant alteration in the aggregation properties of aSyn. We compared the aggregation of WT and H50Q aSyn with and without copper, and assessed the effects of the resultant protein species when applied to primary neuronal cultures. The presence of copper induces the formation of structurally different and less-damaging aSyn aggregates. Interestingly, these aggregates exhibit a stronger capacity to induce aSyn inclusion formation in recipient cells, which demonstrates that the structural features of aSyn species determine their effect in neuronal cells and supports a lack of correlation between toxicity and inclusion formation. In total, our study provides strong support in favor of the hypothesis that protein aggregation is not a primary cause of cytotoxicity