31 research outputs found

    Pose and Velocity Estimation for Soccer Robots

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    This paper details the design and real-time implementation of a planar state estimator for soccer robots. A camera system, encoders, gyroscope and accelerometer are combined in a two-stage Kalman filter through a constant acceleration model. Inflating Noise Variance is employed to handle slip and ensure convergence in stationary periods. The approach oers substantial improvement w.r.t. the old pose estimator

    Direct Learning for Parameter-Varying Feedforward Control: A Neural-Network Approach

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    The performance of a feedforward controller is primarily determined by the extent to which it can capture the relevant dynamics of a system. The aim of this paper is to develop an input-output linear parameter-varying (LPV) feedforward parameterization and a corresponding data-driven estimation method in which the dependency of the coefficients on the scheduling signal are learned by a neural network. The use of a neural network enables the parameterization to compensate a wide class of constant relative degree LPV systems. Efficient optimization of the neural-network-based controller is achieved through a Levenberg-Marquardt approach with analytic gradients and a pseudolinear approach generalizing Sanathanan-Koerner to the LPV case. The performance of the developed feedforward learning method is validated in a simulation study of an LPV system showing excellent performance.Comment: Final author version, accepted for publication at 62nd IEEE Conference on Decision and Control, Singapore, 202

    Femicide trends at the start of the 21st. century: prevalence, risk factors and national public health actions

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    Lethal violence requires a gender-based analysis which recognises that femicide is different from homicide in many ways. Structural factors such as national income and wealth equality together with government policies may influence the scale of the problem globally. This study is an original attempt to examine associations between femicide rates, these structural factors and national action plans using a longitudinal design. Data from two international surveys were combined to examine anti-femicide actions (n = 133 countries) and temporal femicide prevalence trends (n = 66 countries) in the context of national income and wealth inequality factors. The United Nations Survey of Crime Trends and Operations of Criminal Justice Systems was used to estimate femicide rates per country 2003–2014 and the World Health Organisation Global Status Report on Violence Prevention provided data on policy initiatives in place by 2014. Results indicate that femicide rates decreased by 32% worldwide but increased by 26% in low- and medium-income countries. The structural factors of low income and high inequality were significantly negatively associated with the 2014 femicide rate. Structural factors must be addressed alongside policy and legal initiatives if significant gains are to be made toward eradicating violence against women and girls

    Humibacter ginsengiterrae sp. nov., and Humibacter ginsengisoli sp. nov., isolated from soil of a ginseng field

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    Two novel Gram-staining-positive bacteria, designated DCY60T and DCY90T, were isolated from soil of a ginseng field in the Republic of Korea. 16S rRNA gene sequence comparisons showed the two novel strains were closely related to members of the genus Humibacter with greatest similarity to Humibacter antri KCTC 33009T (98.8 and 98.4 % for DCY60T and DCY90T, respectively). The predominant menaquinones present were MK-11 and MK-12. The major fatty acids were anteiso-C17 : 0 and summed feature 8 containing C18 : 1ω7c and/or C18 : 1ω6c. The DNA G+C contents of strains DCY60T and DCY90T were 62.8 and 66.8 mol%, respectively. The peptidoglycan of both strains contained the amino acids ornithine, 2,4-diaminobutyric acid, alanine, glutamic acid and glycine. The cell-wall sugars of strain DCY60T comprised glucose, galactose, rhamnose and xylose, while strain DCY90T contained glucose, galactose, rhamnose and ribose. The major polar lipids of both strains were phosphatidylglycerol, an unidentified glycolipid, and an unknown phospholipid. On the basis of the phenotypic analysis strains DCY60T and DCY90T represent novel species of the genus Humibacter, for which names Humibacter ginsengiterrae sp. nov. (type strain DCY60T = KCTC 33520T = JCM 30079T) and Humibacter ginsengisoli sp. nov. (type strain DCY90T = KCTC 33521T = JCM 30080T) are proposed

    Prototype multi-biomarker test for point-of-care leprosy diagnostics

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    To end the decade-long, obstinately stagnant number of new leprosy cases, there is an urgent need for field-applicable diagnostic tools that detect infection with Mycobacterium leprae, leprosy's etiologic agent. Since immunity against M. leprae is characterized by humoral and cellular markers, we developed a lateral flow test measuring multiple host proteins based on six previously identified biomarkers for various leprosy phenotypes. This multi-biomarker test (MBT) demonstrated feasibility of quantitative detection of six host serum proteins simultaneously, jointly allowing discrimination of patients with multibacillary and paucibacillary leprosy from control individuals in high and low leprosy endemic areas. Pilot testing of fingerstick blood showed similar MBT performance in point-of-care (POC) settings as observed for plasma and serum. Thus, this newly developed prototype MBT measures six biomarkers covering immunity against M. leprae across the leprosy spectrum. The MBT thereby provides the basis for immunodiagnostic POC tests for leprosy with potential for other (infectious) diseases as well.Diagnostic Technique in Health Technology; Applied Microbiology; Biotechnolog

    Atrasentan and renal events in patients with type 2 diabetes and chronic kidney disease (SONAR): a double-blind, randomised, placebo-controlled trial

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    Background: Short-term treatment for people with type 2 diabetes using a low dose of the selective endothelin A receptor antagonist atrasentan reduces albuminuria without causing significant sodium retention. We report the long-term effects of treatment with atrasentan on major renal outcomes. Methods: We did this double-blind, randomised, placebo-controlled trial at 689 sites in 41 countries. We enrolled adults aged 18–85 years with type 2 diabetes, estimated glomerular filtration rate (eGFR)25–75 mL/min per 1·73 m 2 of body surface area, and a urine albumin-to-creatinine ratio (UACR)of 300–5000 mg/g who had received maximum labelled or tolerated renin–angiotensin system inhibition for at least 4 weeks. Participants were given atrasentan 0·75 mg orally daily during an enrichment period before random group assignment. Those with a UACR decrease of at least 30% with no substantial fluid retention during the enrichment period (responders)were included in the double-blind treatment period. Responders were randomly assigned to receive either atrasentan 0·75 mg orally daily or placebo. All patients and investigators were masked to treatment assignment. The primary endpoint was a composite of doubling of serum creatinine (sustained for ≥30 days)or end-stage kidney disease (eGFR <15 mL/min per 1·73 m 2 sustained for ≥90 days, chronic dialysis for ≥90 days, kidney transplantation, or death from kidney failure)in the intention-to-treat population of all responders. Safety was assessed in all patients who received at least one dose of their assigned study treatment. The study is registered with ClinicalTrials.gov, number NCT01858532. Findings: Between May 17, 2013, and July 13, 2017, 11 087 patients were screened; 5117 entered the enrichment period, and 4711 completed the enrichment period. Of these, 2648 patients were responders and were randomly assigned to the atrasentan group (n=1325)or placebo group (n=1323). Median follow-up was 2·2 years (IQR 1·4–2·9). 79 (6·0%)of 1325 patients in the atrasentan group and 105 (7·9%)of 1323 in the placebo group had a primary composite renal endpoint event (hazard ratio [HR]0·65 [95% CI 0·49–0·88]; p=0·0047). Fluid retention and anaemia adverse events, which have been previously attributed to endothelin receptor antagonists, were more frequent in the atrasentan group than in the placebo group. Hospital admission for heart failure occurred in 47 (3·5%)of 1325 patients in the atrasentan group and 34 (2·6%)of 1323 patients in the placebo group (HR 1·33 [95% CI 0·85–2·07]; p=0·208). 58 (4·4%)patients in the atrasentan group and 52 (3·9%)in the placebo group died (HR 1·09 [95% CI 0·75–1·59]; p=0·65). Interpretation: Atrasentan reduced the risk of renal events in patients with diabetes and chronic kidney disease who were selected to optimise efficacy and safety. These data support a potential role for selective endothelin receptor antagonists in protecting renal function in patients with type 2 diabetes at high risk of developing end-stage kidney disease. Funding: AbbVie

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

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    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

    Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution

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    An increasing trend in the use of neural networks in control systems is being observed. The aim of this paper is to reveal that the straightforward application of learning neural network feedforward controllers with closed-loop data may introduce parameter inconsistency that degrades control performance, and to provide a solution. The proposed method employs instrumental variables to ensure consistent parameter estimates. A nonlinear system example reveals that the developed instrumental variable neural network (IVNN) approach asymptotically recovers the optimal solution, while pre-existing approaches are shown to lead to inconsistent estimates

    Neural Network Training Using Closed-Loop Data: Hazards and an Instrumental Variable (IVNN) Solution

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    An increasing trend in the use of neural networks in control systems is being observed. The aim of this paper is to reveal that the straightforward application of learning neural network feedforward controllers with closed-loop data may introduce parameter inconsistency that degrades control performance, and to provide a solution. The proposed method employs instrumental variables to ensure consistent parameter estimates. A nonlinear system example reveals that the developed instrumental variable neural network (IVNN) approach asymptotically recovers the optimal solution, while pre-existing approaches are shown to lead to inconsistent estimates.Team Jan-Willem van Wingerde
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