On the Relationship Between Iterated Statistical Linearization and Quasi-Newton Methods

This letter investigates relationships between iterated filtering algorithms based on statistical linearization, such as the iterated unscented Kalman filter (IUKF), and filtering algorithms based on quasi-Newton (QN) methods, such as the QN iterated extended Kalman filter (QN-IEKF). Firstly, it is shown that the IUKF and the iterated posterior linearization filter (IPLF) can be viewed as QN algorithms, by finding a Hessian correction in the QN-IEKF such that the IPLF iterate updates are identical to that of the QN-IEKF. Secondly, it is shown that the IPLF/IUKF update can be rewritten such that it is approximately identical to the QN-IEKF, albeit for an additional correction term. This enables a richer understanding of the properties of iterated filtering algorithms based on statistical linearization.Comment: 4 page

The Ordinary Weight conjecture and Dade's Projective Conjecture for p-blocks with an extra-special defect group

Let $p$ be a rational odd prime number, $G$ be a finite group such that $|G|=p^am$, with $p \nmid m$. Let $B$ be a $p$-block of $G$ with a defect group $E$ which is an extra-special $p$-group of order $p^3$ and exponent $p$. Consider a fixed maximal $(G, B)$-subpair $(E, b_E)$. Let $b$ be the Brauer correspondent of $B$ for $N_G(E, b_E)$. For a non-negative integer $d$, let $k_d(B)$ denote the number of irreducible characters $\chi$ in $B$ which have $\chi(1)_p=p^{a-d}$ and let $k_d(b)$ be the corresponding number of $b$. Various generalizations of Alperin's Weight Conjecture and McKay's Conjecture are due to Reinhard Knorr, Geoffrey R. Robinson and Everett C. Dade. We follow Geoffrey R. Robinson's approach to consider the Ordinary Weight Conjecture, and Dade's Projective Conjecture. The general question is whether it follows from either of the latter two conjectures that $k_d(B)=k_d(b)$ for all $d$ for the $p$-block $B$. The objective of this thesis is to show that these conjectures predict that $k_d(B)=k_d(b)$, for all non-negative integers $d$. It is well known that $N_G(E, b_E)/EC_G(E)$ is a p^'-subgroup of the automorphism group of $E$. Hence, we have considered some special cases of the above question.The unique largest normal $p$-subgroup of $G$, $O_p(G)$ is the central focus of our attention. We consider the case that $O_p(G)$ is a central $p$-subgroup of $G$, as well as the case that $O_p(G)$ is not central. In both cases, the common factor is that $O_p(G)$ is strictly contained in the defect group of $B$.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Административно-территориальное устройство БССР в период послевоенного возрождения (1944-1953гг.)

В статье рассмотрено административно-территориальное устройство БССР в период послевоенного возрождения (1944-1953 ГГ.

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)

A mitogenomic timetree for Darwin’s enigmatic South American mammal Macrauchenia patachonica

The unusual mix of morphological traits displayed by extinct South American native ungulates (SANUs) confounded both Charles Darwin, who first discovered them, and Richard Owen, who tried to resolve their relationships. Here we report an almost complete mitochondrial genome for the litoptern Macrauchenia. Our dated phylogenetic tree places Macrauchenia as sister to Perissodactyla, but close to the radiation of major lineages within Laurasiatheria. This position is consistent with a divergence estimate of B66 Ma (95% credibility interval, 56.64–77.83 Ma) obtained for the split between Macrauchenia and other Panperissodactyla. Combined with their morphological distinctiveness, this evidence supports the positioning of Litopterna (possibly in company with other SANU groups) as a separate order within Laurasiatheria. We also show that, when using strict criteria, extinct taxa marked by deep divergence times and a lack of close living relatives may still be amenable to palaeogenomic analysis through iterative mapping against more distant relatives

Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

Visual Inertial Navigation and Calibration

Processing and interpretation of visual content is essential to many systems and applications. This requires knowledge of how the content is sensed and also what is sensed. Such knowledge is captured in models which, depending on the application, can be very advanced or simple. An application example is scene reconstruction using a camera; if a suitable model of the camera is known, then a model of the scene can be estimated from images acquired at different, unknown, locations, yet, the quality of the scene model depends on the quality of the camera model. The opposite is to estimate the camera model and the unknown locations using a known scene model. In this work, two such problems are treated in two rather different applications. There is an increasing need for navigation solutions less dependent on external navigation systems such as the Global Positioning System (GPS). Simultaneous Localisation and Mapping (slam) provides a solution to this by estimating both navigation states and some properties of the environment without considering any external navigation systems. The first problem considers visual inertial navigation and mapping using a monocular camera and inertial measurements which is a slam problem. Our aim is to provide improved estimates of the navigation states and a landmark map, given a slam solution. To do this, the measurements are fused in an Extended Kalman Filter (ekf) and then the filtered estimates are used as a starting solution in a nonlinear least-squares problem which is solved using the Gauss-Newton method. This approach is evaluated on experimental data with accurate ground truth for reference. In Augmented Reality (ar), additional information is superimposed onto the surrounding environment in real time to reinforce our impressions. For this to be a pleasant experience it is necessary to have a good models of the ar system and the environment. The second problem considers calibration of an Optical See-Through Head Mounted Display system (osthmd), which is a wearable ar system. We show and motivate how the pinhole camera model can be used to represent the osthmd and the user’s eye position. The pinhole camera model is estimated using the Direct Linear Transformation algorithm. Results are evaluated in experiments which also compare different data acquisition methods

Exploitation of the Conditionally Linear Structure in Visual-Inertial Estimation

In this work, estimators for platform pose and landmark maps for visual-inertial data are analysed. It is shown that the full, non-linear, visual-inertial problem has a conditionally linear substructure in the 2D case which can be exploited for efficient solutions, e.g., Block Coordinate Descent (BCD). It is also shown that the measurement noise from the non-linear model becomes parameter dependent resulting in biased estimates if that fact is ignored. However, the bias can be accounted for using the Iteratively Reweighted Least Squares (IRLS) method. In the 3D case the conditionally linear substructure is not separable. However, it can be shown that the Jacobian of the non-linear substructure can be calculated recursively resulting in an efficient solution. A simulated 2D visual-inertial example is used to illustrate the theoretical results.Funding: Industry Excellence Center LINKSIC by The Swedish Governmental Agency for Innovation Systems (VINNOVA); Saab ABLink-Si

Prediction Error Method Estimation for Simultaneous Localisation and Mapping

This paper presents a batch estimation method for Simultaneous Localization and Mapping (SLAM) using the Prediction Error Method (PEM). The estimation problem considers landmarks as parameter while treating dynamics using state space models. The gradient needed for parameter estimation is computed recursively using an Extended Kalman Filter (EKF). Results using simulations with a monocular camera and inertial sensors are presented and compared to a Nonlinear Least- Squares (NLS) estimator. The presented method produce both lower RMSE’s and scale better to the batch length. LINK-SI