Deceleration and Dispersion of Large-scale Coronal Bright Fronts

One of the most dramatic manifestations of solar activity are large-scale coronal bright fronts (CBFs) observed in extreme ultraviolet (EUV) images of the solar atmosphere. To date, the energetics and kinematics of CBFs remain poorly understood, due to the low image cadence and sensitivity of previous EUV imagers and the limited methods used to extract the features. In this paper, the trajectory and morphology of CBFs was determined in order to investigate the varying properties of a sample of CBFs, including their kinematics and pulse shape, dispersion, and dissipation. We have developed a semi-automatic intensity profiling technique to extract the morphology and accurate positions of CBFs in 2.5-10 min cadence images from STEREO/EUVI. The technique was applied to sequences of 171A and 195A images from STEREO/EUVI in order to measure the wave properties of four separate CBF events. Following launch at velocities of ~240-450kms^{-1} each of the four events studied showed significant negative acceleration ranging from ~ -290 to -60ms^{-2}. The CBF spatial and temporal widths were found to increase from ~50 Mm to ~200 Mm and ~100 s to ~1500 s respectively, suggesting that they are dispersive in nature. The variation in position-angle averaged pulse-integrated intensity with propagation shows no clear trend across the four events studied. These results are most consistent with CBFs being dispersive magnetoacoustic waves.Comment: 15 pages, 18 figure

On-line PCA with Optimal Regrets

We carefully investigate the on-line version of PCA, where in each trial a learning algorithm plays a k-dimensional subspace, and suffers the compression loss on the next instance when projected into the chosen subspace. In this setting, we analyze two popular on-line algorithms, Gradient Descent (GD) and Exponentiated Gradient (EG). We show that both algorithms are essentially optimal in the worst-case. This comes as a surprise, since EG is known to perform sub-optimally when the instances are sparse. This different behavior of EG for PCA is mainly related to the non-negativity of the loss in this case, which makes the PCA setting qualitatively different from other settings studied in the literature. Furthermore, we show that when considering regret bounds as function of a loss budget, EG remains optimal and strictly outperforms GD. Next, we study the extension of the PCA setting, in which the Nature is allowed to play with dense instances, which are positive matrices with bounded largest eigenvalue. Again we can show that EG is optimal and strictly better than GD in this setting

The perceptron algorithm versus winnow: linear versus logarithmic mistake bounds when few input variables are relevant

AbstractWe give an adversary strategy that forces the Perceptron algorithm to make Ω(kN) mistakes in learning monotone disjunctions over N variables with at most k literals. In contrast, Littlestone's algorithm Winnow makes at most O(k log N) mistakes for the same problem. Both algorithms use thresholded linear functions as their hypotheses. However, Winnow does multiplicative updates to its weight vector instead of the additive updates of the Perceptron algorithm. In general, we call an algorithm additive if its weight vector is always a sum of a fixed initial weight vector and some linear combination of already seen instances. Thus, the Perceptron algorithm is an example of an additive algorithm. We show that an adversary can force any additive algorithm to make (N + k −1)2 mistakes in learning a monotone disjunction of at most k literals. Simple experiments show that for k ⪡ N, Winnow clearly outperforms the Perceptron algorithm also on nonadversarial random data

Precedence-constrained scheduling problems parameterized by partial order width

Negatively answering a question posed by Mnich and Wiese (Math. Program. 154(1-2):533-562), we show that P2|prec,$p_j{\in}\{1,2\}$|$C_{\max}$, the problem of finding a non-preemptive minimum-makespan schedule for precedence-constrained jobs of lengths 1 and 2 on two parallel identical machines, is W[2]-hard parameterized by the width of the partial order giving the precedence constraints. To this end, we show that Shuffle Product, the problem of deciding whether a given word can be obtained by interleaving the letters of $k$ other given words, is W[2]-hard parameterized by $k$, thus additionally answering a question posed by Rizzi and Vialette (CSR 2013). Finally, refining a geometric algorithm due to Servakh (Diskretn. Anal. Issled. Oper. 7(1):75-82), we show that the more general Resource-Constrained Project Scheduling problem is fixed-parameter tractable parameterized by the partial order width combined with the maximum allowed difference between the earliest possible and factual starting time of a job.Comment: 14 pages plus appendi

Craniopharyngioma

Craniopharyngiomas are rare malformational tumours of low histological malignancy arising along the craniopharyngeal duct. The two histological subtypes, adamantinomatous craniopharyngioma (ACP) and papillary craniopharyngioma (PCP), differ in genesis and age distribution. ACPs are diagnosed with a bimodal peak of incidence (5-15 years and 45-60 years), whereas PCPs are restricted to adults mainly in the fifth and sixth decades of life. ACPs are driven by somatic mutations in CTNNB1 (encoding β-catenin) that affect β-catenin stability and are predominantly cystic in appearance. PCPs frequently harbour somatic BRAFV600E mutations and are typically solid tumours. Clinical manifestations due to increased intracranial pressure, visual impairment and endocrine deficiencies should prompt imaging investigations, preferentially MRI. Treatment comprises neurosurgery and radiotherapy; intracystic chemotherapy is used in monocystic ACP. Although long-term survival is high, quality of life and neuropsychological function are frequently impaired due to the close anatomical proximity to the optic chiasm, hypothalamus and pituitary gland. Indeed, hypothalamic involvement and treatment-related hypothalamic lesions frequently result in hypothalamic obesity, physical fatigue and psychosocial deficits. Given the rarity of these tumours, efforts to optimize infrastructure and international collaboration should be research priorities