Congestion control for cloud gaming over udp based on round-Trip video latency

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksWe describe a network congestion control mechanism for cloud gaming (CG) platforms based on the user datagram protocol (UDP). To minimize the contribution of the downstream transmission delay to the total end-To-end latency in the interaction-perception loop, we first define the round-Trip video latency (RTVL) and develop a congestion model. Based on them, we design and implement an adaptation strategy that detects the early stages of congestion to prevent high values of RTVL and network bufferbloat, thus avoiding packet losses. Using data measured from the network, our strategy modifies the target output bitrate of the video encoder to throttle down or upto the data flow sent by the server to the client. In the presence of sudden downstream channel capacity drops of over 40%, our algorithm reactively manages to satisfy the key CG requirements for interactive games by entirely avoiding the packet losses and keeping the RTVL below 100 ms. In reasonably stable network conditions, our algorithm proactively keeps exploring for higher bitrates and building a 'network state dictionary,' due to which it achieves an effective downstream channel capacity use of 95%This work was supported in part by the Ministerio de Ciencia, Innovación y Universidades (AEI/FEDER) of the Spanish Government through the Project ‘‘Open Graphics Gaming Cloud’’ under Grant RTC-2016-5676-7 and the Project ‘‘Immersive Visual Media Environments’’ under Grant TEC2016-7598

Prognosis Stratification Tools in Early-Stage Endometrial Cancer: Could We Improve Their Accuracy?

There are three prognostic stratification tools used for endometrial cancer: ESMO-ESGO-ESTRO 2016, ProMisE, and ESGO-ESTRO-ESP 2020. However, these methods are not sufficiently accurate to address prognosis. The aim of this study was to investigate whether the integration of molecular classification and other biomarkers could be used to improve the prognosis stratification in early-stage endometrial cancer. Relapse-free and overall survival of each classifier were analyzed, and the c-index was employed to assess accuracy. Other biomarkers were explored to improve the precision of risk classifiers. We analyzed 293 patients. A comparison between the three classifiers showed an improved accuracy in ESGO-ESTRO-ESP 2020 when RFS was evaluated (c-index = 0.78), although we did not find broad differences between intermediate prognostic groups. Prognosis of these patients was better stratified with the incorporation of CTNNB1 status to the 2020 classifier (c-index 0.81), with statistically significant and clinically relevant differences in 5-year RFS: 93.9% for low risk, 79.1% for intermediate merged group/CTNNB1 wild type, and 42.7% for high risk (including patients with CTNNB1 mutation). The incorporation of molecular classification in risk stratification resulted in better discriminatory capability, which could be improved even further with the addition of CTNNB1 mutational evaluation.Peer reviewe

Prognosis Stratification Tools in Early-Stage Endometrial Cancer: Could We Improve Their Accuracy?

There are three prognostic stratification tools used for endometrial cancer: ESMO-ESGO-ESTRO 2016, ProMisE, and ESGO-ESTRO-ESP 2020. However, these methods are not sufficiently accurate to address prognosis. The aim of this study was to investigate whether the integration of molecular classification and other biomarkers could be used to improve the prognosis stratification in early-stage endometrial cancer. Relapse-free and overall survival of each classifier were analyzed, and the c-index was employed to assess accuracy. Other biomarkers were explored to improve the precision of risk classifiers. We analyzed 293 patients. A comparison between the three classifiers showed an improved accuracy in ESGO-ESTRO-ESP 2020 when RFS was evaluated (c-index = 0.78), although we did not find broad differences between intermediate prognostic groups. Prognosis of these patients was better stratified with the incorporation of CTNNB1 status to the 2020 classifier (c-index 0.81), with statistically significant and clinically relevant differences in 5-year RFS: 93.9% for low risk, 79.1% for intermediate merged group/CTNNB1 wild type, and 42.7% for high risk (including patients with CTNNB1 mutation). The incorporation of molecular classification in risk stratification resulted in better discriminatory capability, which could be improved even further with the addition of CTNNB1 mutational evaluation.Peer reviewe

Prognosis Stratification Tools in Early-Stage Endometrial Cancer: Could We Improve Their Accuracy?

There are three prognostic stratification tools used for endometrial cancer: ESMO-ESGO-ESTRO 2016, ProMisE, and ESGO-ESTRO-ESP 2020. However, these methods are not sufficiently accurate to address prognosis. The aim of this study was to investigate whether the integration of molecular classification and other biomarkers could be used to improve the prognosis stratification in early-stage endometrial cancer. Relapse-free and overall survival of each classifier were analyzed, and the c-index was employed to assess accuracy. Other biomarkers were explored to improve the precision of risk classifiers. We analyzed 293 patients. A comparison between the three classifiers showed an improved accuracy in ESGO-ESTRO-ESP 2020 when RFS was evaluated (c-index = 0.78), although we did not find broad differences between intermediate prognostic groups. Prognosis of these patients was better stratified with the incorporation of CTNNB1 status to the 2020 classifier (c-index 0.81), with statistically significant and clinically relevant differences in 5-year RFS: 93.9% for low risk, 79.1% for intermediate merged group/CTNNB1 wild type, and 42.7% for high risk (including patients with CTNNB1 mutation). The incorporation of molecular classification in risk stratification resulted in better discriminatory capability, which could be improved even further with the addition of CTNNB1 mutational evaluation

Central Pathology Review in SENTIX, a Prospective Observational International Study on Sentinel Lymph Node Biopsy in Patients with Early-Stage Cervical Cancer (ENGOT-CX2)

The quality of pathological assessment is crucial for the safety of patients with cervical cancer if pelvic lymph node dissection is to be replaced by sentinel lymph node (SLN) biopsy. Central pathology review of SLN pathological ultrastaging was conducted in the prospective SENTIX/European Network of Gynaecological Oncological Trial (ENGOT)-CX2 study. All specimens from at least two patients per site were submitted for the central review. For cases with major or critical deviations, the sites were requested to submit all samples from all additional patients for second-round assessment. From the group of 300 patients, samples from 83 cases from 37 sites were reviewed in the first round. Minor, major, critical, and no deviations were identified in 28%, 19%, 14%, and 39% of cases, respectively. Samples from 26 patients were submitted for the second-round review, with only two major deviations found. In conclusion, a high rate of major or critical deviations was identified in the first round of the central pathology review (28% of samples). This reflects a substantial heterogeneity in current practice, despite trial protocol requirements. The importance of the central review conducted prospectively at the early phase of the trial is demonstrated by a substantial improvement of SLN ultrastaging quality in the second-round review

Retrieval of biophysical vegetation parameters using simultaneous inversion of high resolution remote sensing imagery constrained by a vegetation index

This study proposes a new method for inverting radiative transfer models (RTM) to retrieve canopy biophysical parameters using remote sensing imagery. The inversion procedure is improved with respect to standard inversion, and achieves simultaneous inversion of leaf area index (LAI), soil reflectance (ρsoil), chlorophyll content (Ca+b) and average leaf angle (ALA). In this approach, LAI is used to constrain modelling conditions during the inversion process, providing information about the phenological state of each plot under study. Due to the small area of the vegetation plots used for the inversion procedure and in order to avoid redundant information and improve computation efficiency, existing plot segmentation was used. All retrieved biophysical parameters, except LAI, were assumed to be invariant within each plot. The proposed methodology, based on the combination of PROSPECT and SAILH models, was tested over 16 cereal fields and 51 plots, on two dates, which were chosen to ensure crop assessment at different phenological stages. Plots were selected to provide a wide range of LAI between 0 and 6. Field measurements of LAI, ALA and Ca+b were conducted and used as ground truth for validation of the proposed model-inversion methodology. The approach was applied to very high spatial resolution (VHR) remote sensing data from the QuickBird 2 satellite. The inversion procedure was successfully applied to the imagery and retrieved LAI with R2=0.83 and RMSE=0.63 when compared to LAI2000 ground measurements. Separate inversions for barley and wheat yielded R2=0.89 (RMSE=0.64) and R2=0.56 (RMSE=0.61), respectively.JRC.H.4-Monitoring Agricultural Resource

CÆLIS: software for assimilation, management and processing data of an atmospheric measurement network

International audienceGiven the importance of the atmospheric aerosol, the number of instruments and measurement networks which focus on its characterization are growing. Many challenges are derived from standardization of protocols, monitoring of the instrument status to evaluate the network data quality and manipulation and distribution of large volume of data (raw and processed). CÆLIS is a software system which aims at simplifying the management of a network, providing tools by monitoring the instruments, processing the data in real time and offering the scientific community a new tool to work with the data. Since 2008 CÆLIS has been successfully applied to the photometer calibration facility managed by the University of Valladolid, Spain, in the framework of Aerosol Robotic Network (AERONET). Thanks to the use of advanced tools, this facility has been able to analyze a growing number of stations and data in real time, which greatly benefits the network management and data quality control. The present work describes the system architecture of CÆLIS and some examples of applications and data processing

Eribulin activity in soft tissue sarcoma monolayer and three-dimensional cell line models: could the combination with other drugs improve its antitumoral effect?

Background Eribulin has shown antitumour activity in some soft tissue sarcomas (STSs), but it has only been approved for advanced liposarcoma (LPS). Methods In this study, we evaluated the effect of eribulin on proliferation, migration and invasion capabilities in LPS, leiomyosarcoma (LMS) and fibrosarcoma (FS) models, using both monolayer (2D) and three-dimensional (3D) spheroid cell cultures. Additionally, we explored combinations of eribulin with other drugs commonly used in the treatment of STS with the aim of increasing its antitumour activity. Results Eribulin showed activity inhibiting proliferation, 2D and 3D migration and invasion in most of the cell line models. Furthermore, we provide data that suggest, for the first time, a synergistic effect with ifosfamide in all models, and with pazopanib in LMS as well as in myxoid and pleomorphic LPS. Conclusions Our results support the effect of eribulin on LPS, LMS and FS cell line models. The combination of eribulin with ifosfamide or pazopanib has shown in vitro synergy, which warrants further clinical research.Peer reviewe

Characterisation of new in vitro models and identification of potentially active drugs in angiosarcoma

Angiosarcoma is a rare soft tissue sarcoma originating from endothelial cells. Given that current treatments for advanced disease have shown limited efficacy, alternative therapies need to be identified. In rare diseases, patient-derived cell models are crucial for screening anti-tumour activity. In this study, cell line models were characterised in 2D and 3D cultures. The cell lines’ growth, migration and invasion capabilities were explored, confirming them as useful tools for preclinical angiosarcoma studies. By screening a drug library, we identified potentially effective compounds: 8-amino adenosine impacted cell growth and inhibited migration and invasion at considerably low concentrations as a single agent. No synergistic effect was detected when combining with paclitaxel, gemcitabine or doxorubicin. These results suggest that this compound could be a potentially useful drug in the treatment of AGS.Peer reviewe

Long-term characterisation of the vertical structure of the Saharan Air Layer over the Canary Islands using lidar and radiosonde profiles: implications for radiative and cloud processes over the subtropical Atlantic Ocean

Every year, large-scale African dust outbreaks frequently pass over the Canary Islands (Spain). Here we describe the seasonal evolution of atmospheric aerosol extinction and meteorological vertical profiles on Tenerife over the period 2007-2018 using long-term micropulse lidar (MPL-3) and radiosonde observations. These measurements are used to categorise the different patterns of dust transport over the subtropical North Atlantic and, for the first time, to robustly describe the dust vertical distribution in the Saharan Air Layer (SAL) over this region. Three atmospheric scenarios dominate the aerosol climatology: dust-free (clean) conditions, the Saharan summer scenario (summer-SAL) and the Saharan winter scenario (winter-SAL).A relatively well-mixed marine boundary layer (MBL) was observed in the case of clean (dust-free) conditions; it was associated with rather constant lidar extinction coefficients (alpha) below 0.036 km(-1) with minimum alpha ( 0.066 km-1 at similar to 2.5 km. Desert dust is present up to similar to 6.0 km, the SAL top based on the altitude of SAL's temperature inversion. In the winter-SAL scenario, the dust layer is confined to lower levels below 2 km altitude. This layer is characterised by a dry anomaly at lower levels (Delta r similar to -38 % in comparison to the clean scenario) and a dust peak at similar to 1.3 km height. Clean FT conditions were found above 2.3 km.Our results reveal the important role that both dust and water vapour play in the radiative balance within the summer-SAL and winter-SAL. The dominant dust-induced shortwave (SW) radiative warming in summer (heating rates up to +0.7 K d(-1)) is found slightly below the dust maximum. However, the dominant contribution of water vapour was observed as a net SW warming observed within the SAL (from 2.1 to 5.7 km) and as a strong cold anomaly near the SAL's top (-0.6 K d(-1)). The higher water vapour content found to be carried on the summer-SAL, despite being very low, represents a high relative variation in comparison to the very dry clean free troposphere in the subtropics. This relevant aspect should be properly taken into account in atmospheric modelling processes. In the case of the winter-SAL, we observed a dust-induced radiative effect dominated by SW heating (maximum heating of +0.7 K d(-1) at 1.5 km, near the dust peak); both dust and atmospheric water vapour impact heating in the atmospheric column. This is the case of the SW heating within the SAL (maximum near the r peak), the dry anomaly at lower levels (Delta r similar to -38 % at 1 km) and the thermal cooling (similar to 0.3 K d(-1)) from the temperature inversion upwards.Finally, we hypothesise that the SAL can impact heterogeneous ice nucleation processes through the frequent occurrence of mid-level clouds observed near the SAL top at relatively warm temperatures. A dust event that affected Tenerife on August 2015 is simulated using the regional DREAM model to assess the role of dust and water vapour carried within SAL in the ice nucleation processes. The modelling results reproduce the arrival of the dust plume and its extension over the island and confirm the observed relationship between the summer-SAL conditions and the formation of mid- and high-level clouds