Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly ...

OBJECTIVE To evaluate the efficacy and safety of triple fixed-combination bimatoprost 0.01%/brimonidine 0.15%/timolol 0.5% (TFC) versus dual fixed-combination brimonidine 0.2%/timolol 0.5% (DFC) in primary open-angle glaucoma and ocular hypertension. METHODS Patients with intraocular pressure (IOP) ≥23 and ≤34 mmHg were randomized to twice-daily TFC or DFC. The primary variable is the change ...

Brain networks can be defined and explored through their connectivity. Here, we analyzed the relationship between structural connectivity (SC) across 2,514 regions that cover entire brain brainstem, dynamic functional (DFC). To do so, focused on a combination of two metrics: first assesses degree SC-DFC similarity -i.e. extent to which correlations explained by pathways-; second is intrinsic va...

The main objective of this research is to analyze the bifurcation phenomenon in Internet congestion model for Transmission Control Protocol (TCP) with Random Early Detection (RED). This problem can be divided to many categories considering different viewpoints. Different approaches of modeling (continuous and discrete models) and various system structures (control in end node or routers) are so...

a t t e r n T h e o r e t i c L e a r n i n g Abstract The goal of learning from sample data is to extract a concept that captures the underlying pattern while still representing it in a way useful to the investigator. A new approach based on function decomposition in the Pattern Theory framework is presented here. The objective of this extended abstract is threefold. The rst is to provide an o...

The goal of learning from sample data is to extract a concept that captures the underlying pattern while still representing it in a way useful to the investigator. A new approach based on function decomposition in the Pattern Theory framework is presented here. The objective of this extended abstract is three-fold. The first is to provide an overview of our new approach to learning. Specificall...

Range ambiguity resolving and deceptive jamming suppression are both challenges for high-resolution wide-swath SAR imagery. With the accommodation of digital beamforming (DBF) techniques, agile waveforms potential to tackle ambiguity-resolving antijamming tasks simultaneously. In this article, an algorithm blending elevation DBF is proposed imagery adaptive suppression. A shift-stepped Costas D...

This paper describes our contribution to the English Entrance Exams task of CLEF 2015, which requires participating systems to automatically solve multiple choice reading comprehension tasks. We use a combination of text segmentation and different similarity measures with the aim of exploiting two observed aspects of tests: 1) the often linear relationship between reading text and test question...

Resting-state functional connectivity is a powerful tool for studying human functional brain networks. Temporal fluctuations in functional connectivity, i.e., dynamic functional connectivity (dFC), are thought to reflect dynamic changes in brain organization and non-stationary switching of discrete brain states. However, recent studies have suggested that dFC might be attributed to sampling var...