Computing User Reputation in a Social Network of Web 2.0

In the Web 2.0 era, people not only read web contents but create, upload, view, share and evaluate all contents on the web. This leads us to introduce a new type of social network based on user activity and content metadata. We notice that we can determine the quality of related contents using this new social network. Based on this observation, we introduce a user evaluation algorithm for user-generated video sharing website. First, we make a social network of users from video contents and related social activities such as subscription, uploading or favorite. We then use a modified PageRank algorithm to compute user reputation from the social network. We re-calculate the content scores using user reputations and compare the results with a standard BM25 result. We apply the proposed approach to YouTube and demonstrate that the user reputation is closely related to the number of subscriptions and the number of uploaded contents. Furthermore, we show that the new ranking results relied on the user reputation is better than the standard BM25 approach by experiments

Interactive media server with media synchronized raid storage system

We propose an efficient placement algorithm and per-disk prefetching method to effectively support interactive operations in the media server. Our placement policy is incorporated with an encoder having a special bitcount control scheme that repeatedly tunes quantization parameters to adjust the bitcounts of video frames. This encoder can generate coded frames whose sizes are synchronized with the RAID stripe size, so that when various fast-forward levels are accessed we can reduce the seek and rotational latency and enhance the disk throughput of each disk in the RAID system. In the experimental results, the proposed placement policy and bitrate control scheme can significantly improve the average service time, which can enlarge the capacity of the interactive media server

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

Compressed representation of a partially defined integer function over multiple arguments

In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one

Measurement of the production cross section for Z gamma -> nu(nu)over-bar gamma in pp collisions at √s=7 TeV and limits on ZZ gamma and Z gamma gamma triple gauge boson couplings

This article is the pre-print version of the final published paper that is available from the link below.A measurement of the Z → vvγ cross section in pp collisions at root s = 7TeV is presented, using data corresponding to an integrated luminosity of 5.0 fb-1 collected with the CMS detector. This measurement is based on the observation of events with an imbalance of transverse energy in excess of 130 GeV and a single photon in the absolute pseudorapidity range |n| < 1:4 with transverse energy above 145 GeV. The Z →vvγ production cross section is measured to be 21.1±4.2 (stat:)±4.3 (syst:)±0.5 (lum:) fb, which agrees with the standard model prediction of 21.9±1.1 fb. The results are combined with the CMS measurement of Z production in the l+l- γ final state (where l is an electron or a muon) to yield the most stringent limits to date on triple gauge boson couplings: |hZ3|< 2.7 x 10-3, |hZ4| < 1,3 x 10-5 for ZZγ and |hγ3| < 2.9 x10-3, |hγ4| < 1.5 x 10-5 for Zγγ couplings

Measurement of associated production of vector bosons and top quark-antiquark pairs in pp collisions at √s=7 TeV

PubMed ID: 23679709The first measurement of vector-boson production associated with a top quark-antiquark pair in proton-proton collisions at s √ =7  TeV is presented. The results are based on a data set corresponding to an integrated luminosity of 5.0  fb^−1 , recorded by the CMS detector at the LHC in 2011. The measurement is performed in two independent channels through a trilepton analysis of tt ¯ Z events and a same-sign dilepton analysis of tt ¯ V (V=W or Z ) events. In the trilepton channel a direct measurement of the tt ¯ Z cross section σ tt ¯ Z =0.28 [+0.14 −0.11]  (stat) [+0.06 −0.03]  (syst)  pb is obtained. In the dilepton channel a measurement of the tt ¯ V cross section yields σtt¯V=0.43 [+0.17 −0.15]  (stat) [+0.09 −0.07]  (syst)  pb . These measurements have a significance, respectively, of 3.3 and 3.0 standard deviations from the background hypotheses and are compatible, within uncertainties, with the corresponding next-to-leading order predictions of 0.137[+0.012 −0.016] and 0.306 [+0.031 −0.053]   pb

Measurement of the ratio of the inclusive 3-jet cross section to the inclusive 2-jet cross section in pp collisions at root s=7 TeV and first determination of the strong coupling constant in the TeV range

A measurement is presented of the ratio of the inclusive 3-jet cross section to the inclusive 2-jet cross section as a function of the average transverse momentum, , of the two leading jets in the event. The data sample was collected during 2011 at a proton-proton centre-of-mass energy of 7 TeV with the CMS detector at the LHC, corresponding to an integrated luminosity of 5.0 fb(-1). The strong coupling constant at the scale of the Z boson mass is determined to be alpha(S)(M-Z) = 0.1148 +/- 0.0014 (exp.) +/- 0.0018 (PDF) +/- 0.0050 (theory), by comparing the ratio in the range 0.42 < 1.39 TeV to the predictions of perturbative QCD at next-to-leading order. This is the first determination of alpha(S)(M-Z) from measurements at momentum scales beyond 0.6 TeV. The predicted ratio depends only indirectly on the evolution of the parton distribution functions of the proton such that this measurement also serves as a test of the evolution of the strong coupling constant. No deviation from the expected behaviour is observed

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation