4G/LTE channel quality reference signal trace data set

Mobile networks, especially LTE networks, are used more and more for high-bandwidth services like multimedia or video streams. The quality of the data connection plays a major role in the perceived quality of a service. Videos may be presented in a low quality or experience a lot of stalling events, when the connection is too slow to buffer the next frames for playback. So far, no publicly available data s

Alcan Aluminium Limited v. Franchise Tax Board: State Unitary Apportionment of Foreign Parent Income Taxation Will Have to Go to State Court

Viewers using HTTP Adaptive Streaming (HAS) without sufficient bandwidth undergo frequent quality switches that hinder their watching experience. This situation, known as instability, is produced when HAS players are unable to accurately estimate the available bandwidth. Moreover, when several players stream over a bottleneck link, their individual adaptation techniques may result in an unfair share of the channel. These are two detrimental issues in HAS technology, which is otherwise very attractive. To overcome them, a group of solutions are proposed in the literature that can be classified as network-assisted HAS. Solving stability and fairness only in the player is difficult, because a player has a limited view of the network. Using information from network devices can help players in making better adaptation decisions. In this paper we describe our implementation in the form of an HTTP prox

Improving mobile video quality through predictive channel quality based buffering

Frequent variations in throughput make mobile networks a challenging environment for video streaming. Current video players deal with those variations by matching video quality to network throughput. However, this adaptation strategy results in frequent changes of video resolution and bitrate, which negatively impacts the users' streaming experience. Alternatively, keeping the video quality constant would improve the experience, but puts additional demand on the network. Downloading high quality content when channel quality is low requires additional resources, because data transfer efficiency is linked to channel quality. In this paper, we present a predictive Channel Quality based Buffering Strategy (CQBS) that lets the video buffer grow when channel quality is good, and relies on this buffer when channel quality decreases. Our strategy is the outcome of a Markov Decision Process. The underlying Markov chain is conditioned on 377 real-world LTE channel quality traces that we have collected using an Android mobile application. With our strategy, mobile network providers can deliver constant quality video streams, using less network resources

Widespread DNA hypomethylation at gene enhancer regions in placentas associated with early-onset pre-eclampsia.

Pre-eclampsia is a serious complication of pregnancy that can affect both maternal and fetal outcomes. Early-onset pre-eclampsia (EOPET) is a severe form of pre-eclampsia that is associated with altered physiological characteristics and gene expression in the placenta. DNA methylation is a relatively stable epigenetic modification to DNA that can reflect gene expression, and can provide insight into the mechanisms underlying such expression changes. This case-control study focused on DNA methylation and gene expression of whole chorionic villi samples from 20 EOPET placentas and 20 gestational age-matched controls from pre-term births. DNA methylation was also assessed in placentas affected by late-onset pre-eclampsia (LOPET) and normotensive intrauterine growth restriction (nIUGR). The Illumina HumanMethylation450 BeadChip was used to assess DNA methylation at >480 000 cytosine-guanine dinucleotide (CpG) sites. The Illumina HT-12v4 Expression BeadChip was used to assess gene expression of >45 000 transcripts in a subset of cases and controls. DNA methylation analysis by pyrosequencing was used to follow-up the initial findings in four genes with a larger cohort of cases and controls, including nIUGR and LOPET placentas. Bioinformatic analysis was used to identify overrepresentation of gene ontology categories and transcription factor binding motifs. We identified 38 840 CpG sites with significant (false discovery rate 12.5% methylation difference compared with the controls. Significant sites were enriched at the enhancers and low CpG density regions of the associated genes and the majority (74.5%) of these sites were hypomethylated in EOPET. EOPET, but not associated clinical features, such as intrauterine growth restriction (IUGR), presented a distinct DNA methylation profile. CpG sites from four genes relevant to pre-eclampsia (INHBA, BHLHE40, SLC2A1 and ADAM12) showed different extent of changes in LOPET and nIUGR. Genome-wide expression in a subset of samples showed that some of the gene expression changes were negatively correlated with DNA methylation changes, particularly for genes that are responsible for angiogenesis (such as EPAS1 and FLT1). Results could be confounded by altered cell populations in abnormal placentas. Larger sample sizes are needed to fully address the possibility of sub-profiles of methylation within the EOPET cohort. Based on DNA methylation profiling, we conclude that there are widespread DNA methylation alterations in EOPET that may be associated with changes in placental function. This property may provide a useful tool for early screening of such placentas. This study identifies DNA methylation changes at many loci previously reported to have altered gene expression in EOPET placentas, as well as in novel biologically relevant genes we confirmed to be differentially expressed. These results may be useful for DNA- methylation-based non-invasive prenatal diagnosis of at-risk pregnancies