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In this paper, a novel particle swarm optimization (PSO) algorithm is put forward where a sigmoid-functionbased weighting strategy is developed to adaptively adjust the acceleration coefficients. The newly proposed adaptive weighting strategy takes into account both the distances from the particle to the global best position and from the particle to its personal best position, thereby having the distinguishing feature of enhancing the convergence rate. Inspired by the activation function of neural networks, the new strategy is employed to update the acceleration coefficients by using the sigmoid function. The search capability of the developed adaptive weighting PSO (AWPSO) algorithm is comprehensively evaluated via eight well-known benchmark functions including both the unimodal and multimodal cases. Experiment results demonstrate that the designed AWPSO algorithm substantially improves the convergence rate of the particle swarm optimizer and also outperforms some currently popular PSO algorithms.

Migraine comorbid with depression is common and is often encountered in clinical practice. The comorbidity may lead to more serious conditions with other symptoms and a longer duration of treatment and it may impose heavy economic and social burdens, directly or indirectly, on patients and their families. Numerous studies have been published on the association of migraine with depression. Numerous literature have showed that the comorbidity may have a common complicated pathogenic mechanism involving biopsychosocial characteristics, including abnormal brain development and shared genetic basis, as well as neurotransmitters, sex hormones and stress. In addition, some studies have identified the multiple, bidirectional relationship between migraine and depressive disorder. We searched the literature for the possible common mechanisms between migraine and depression and classified the research results.

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This paper presents the bed topography of Jakobshavn Isbrae, Greenland, and Byrd Glacier, Antarctica, derived from sounding these glaciers with high-sensitivity radars. To understand the processes causing the speed-up and retreat of outlet glaciers, and to enable the development of nextgeneration ice-sheet models, we need information on bed topography and basal conditions. To this end, we performed measurements with the progressively improved Multichannel Coherent Radar Depth Sounder/Imager (MCoRDS/I). We processed the data from each antenna-array element using synthetic aperture radar algorithms to improve radar sensitivity and reduce along-track surface clutter. We then applied array and image-processing algorithms to extract the weak bed echoes buried in off-vertical scatter (cross-track surface clutter). At Jakobshavn Isbrae, we observed 2.7 km thick ice $ $30 km upstream of the calving front and $850 m thick ice at the calving front. We also observed echoes from multiple interfaces near the bed. We applied the MUSIC algorithm to the data to derive the direction of arrival of the signals. This analysis revealed that clutter is dominated by the ice surface at Jakobshavn Isbrae. At Byrd Glacier, we found $3.62 km thick ice, as well as a subglacial trench $3.05 km below sea level. We used ice thickness information derived from radar data in conjunction with surface elevation data to generate bed maps for these two critical glaciers. The performance of current radars must be improved further by $15 dB to fully sound the deepest part of Byrd Glacier. Unmanned aerial systems equipped with radars that can be flown over lines spaced as close as 5 m apart in the cross-track direction to synthesize a two-dimensional aperture would be ideal for collecting fine-resolution data over glaciers like Jakobshavn near their grounding lines.