Generic Methods for Adaptive Management of Service Level Agreements in Cloud Computing

The adoption of cloud computing to build and deliver application services has been nothing less than phenomenal. Service oriented systems are being built using disparate sources composed of web services, replicable datastores, messaging, monitoring and analytics functions and more. Clouds augment these systems with advanced features such as high availability, customer affinity and autoscaling on a fair pay-per-use cost model. The challenge lies in using the utility paradigm of cloud beyond its current exploit. Major trends show that multi-domain synergies are creating added-value service propositions. This raises two questions on autonomic behaviors, which are specifically ad- dressed by this thesis. The first question deals with mechanism design that brings the customer and provider(s) together in the procurement process. The purpose is that considering customer requirements for quality of service and other non functional properties, service dependencies need to be efficiently resolved and legally stipulated. The second question deals with effective management of cloud infrastructures such that commitments to customers are fulfilled and the infrastructure is optimally operated in accordance with provider policies. This thesis finds motivation in Service Level Agreements (SLAs) to answer these questions. The role of SLAs is explored as instruments to build and maintain trust in an economy where services are increasingly interdependent. The thesis takes a wholesome approach and develops generic methods to automate SLA lifecycle management, by identifying and solving relevant research problems. The methods afford adaptiveness in changing business landscape and can be localized through policy based controls. A thematic vision that emerges from this work is that business models, services and the delivery technology are in- dependent concepts that can be finely knitted together by SLAs. Experimental evaluations support the message of this thesis, that exploiting SLAs as foundations for market innovation and infrastructure governance indeed holds win-win opportunities for both cloud customers and cloud providers

Low Concordance Between T-Cell Densities in Matched Primary Tumors and Liver Metastases in Microsatellite Stable Colorectal Cancer

Background: The subtype, density and location of tumor infiltrating T-cells are being explored as prognostic and predictive biomarkers in primary colorectal cancer (pCRC) and colorectal liver metastases (CLM). Very limited data exist comparing findings in pCRC and matched CLM. Patients and methods: Fifty-eight patients with available pCRC and matched CLM (57/58 microsatellite stable) were included in this OSLO-COMET substudy. In immunohistochemically stained sections, total (Ttot), helper (TH), cytotoxic (CTL), and regulatory (Treg) T-cells were manually counted in hotspots from the invasive margin (IM), intratumor (IT), and tumor adjacent regions to determine T-cell densities. Results: A striking accumulation of T-cells was found in IM of both pCRC and CLM with much lower densities in the IT region, exemplified by Ttot of 2838 versus 340 cells/mm2, respectively, in CLM. The correlation at the individual level between T-cell densities in pCRC and corresponding CLM was poor for all regions and T-cell subtypes; for instance, the correlation coefficient (R2) for IM Ttot was 0.07. The IT TH : CTL and Treg : TH ratios were 2.94 and 0.44, respectively, in pCRC, and 1.84 and 0.24, respectively, in CLM. Conclusion: The observed accumulation of T-cells in the IM regions of pCRC and CLM with low penetration to the IT regions, combined with high TH : CTL and Treg : TH ratios, point to the presence of an immune suppressive microenvironment. T-cell densities of CLM differed markedly from the matched pCRC, indicating that to evaluate T-cell biomarkers in metastasis, the commonly available pCRC cannot serve as a surrogate for the metastatic tumor

D4.2 Intelligent D-Band wireless systems and networks initial designs

This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project

Low Concordance Between T-Cell Densities in Matched Primary Tumors and Liver Metastases in Microsatellite Stable Colorectal Cancer

BackgroundThe subtype, density and location of tumor infiltrating T-cells are being explored as prognostic and predictive biomarkers in primary colorectal cancer (pCRC) and colorectal liver metastases (CLM). Very limited data exist comparing findings in pCRC and matched CLM.Patients and methodsFifty-eight patients with available pCRC and matched CLM (57/58 microsatellite stable) were included in this OSLO-COMET substudy. In immunohistochemically stained sections, total (Ttot), helper (TH), cytotoxic (CTL), and regulatory (Treg) T-cells were manually counted in hotspots from the invasive margin (IM), intratumor (IT), and tumor adjacent regions to determine T-cell densities.ResultsA striking accumulation of T-cells was found in IM of both pCRC and CLM with much lower densities in the IT region, exemplified by Ttot of 2838 versus 340 cells/mm2, respectively, in CLM. The correlation at the individual level between T-cell densities in pCRC and corresponding CLM was poor for all regions and T-cell subtypes; for instance, the correlation coefficient (R2) for IM Ttot was 0.07. The IT TH : CTL and Treg : TH ratios were 2.94 and 0.44, respectively, in pCRC, and 1.84 and 0.24, respectively, in CLM.ConclusionThe observed accumulation of T-cells in the IM regions of pCRC and CLM with low penetration to the IT regions, combined with high TH : CTL and Treg : TH ratios, point to the presence of an immune suppressive microenvironment. T-cell densities of CLM differed markedly from the matched pCRC, indicating that to evaluate T-cell biomarkers in metastasis, the commonly available pCRC cannot serve as a surrogate for the metastatic tumor

Laparoscopic versus open liver resection for intrahepatic cholangiocarcinoma: a multicenter propensity score-matched study

Background: The role of laparoscopy in the treatment of intrahepatic cholangiocarcinoma (ICC) remains unclear. This multicenter study examined the outcomes of laparoscopic liver resection for ICC. Methods: Patients with ICC who had undergone laparoscopic or open liver resection between 2012 and 2019 at four European expert centers were included in the study. Laparoscopic and open approaches were compared in terms of surgical and oncological outcomes. Propensity score matching was used for minimizing treatment selection bias and adjusting for confounders (age, ASA grade, tumor size, location, number of tumors and underlying liver disease). Results: Of 136 patients, 50 (36.7%) underwent laparoscopic resection, whereas 86 (63.3%) had open surgery. Median tumor size was larger (73.6 vs 55.1 mm, p¼ 0.01) and the incidence of bi-lobar tumors was higher (36.6 vs 6%, p< 0.01) in patients undergoing open surgery. After propensity score matching baseline characteristics were comparable although open surgery was associated with a larger fraction of major liver resections (74 vs 38%, p< 0.01), lymphadenectomy (60 vs 20%, p< 0.01) and longer operative time (294 vs 209 min, p< 0.01). Tumor characteristics were similar. Laparoscopic resection resulted in less complications (30 vs 52%, p¼ 0.025), fewer reoperations (4 vs 16%, p¼ 0.046) and shorter hospital stay (5 vs 8 days, p< 0.01). No differences were found in terms of recurrence, recurrence-free and overall survival. Conclusion: Laparoscopic resection seems to be associated with improved short-term and with similar long-term outcomes compared with open surgery in patients with ICC. However, possible selection criteria for laparoscopic surgery are yet to be defined

Liver resection and ablation for squamous cell carcinoma liver metastases.

Funder: Region StockholmFunder: Region Stockholm (clinical postdoctoral appointment)BACKGROUND: Limited evidence exists to guide the management of patients with liver metastases from squamous cell carcinoma (SCC). The aim of this retrospective multicentre cohort study was to describe patterns of disease recurrence after liver resection/ablation for SCC liver metastases and factors associated with recurrence-free survival (RFS) and overall survival (OS). METHOD: Members of the European-African Hepato-Pancreato-Biliary Association were invited to include all consecutive patients undergoing liver resection/ablation for SCC liver metastases between 2002 and 2019. Patient, tumour and perioperative characteristics were analysed with regard to RFS and OS. RESULTS: Among the 102 patients included from 24 European centres, 56 patients had anal cancer, and 46 patients had SCC from other origin. RFS in patients with anal cancer and non-anal cancer was 16 and 9 months, respectively (P = 0.134). A positive resection margin significantly influenced RFS for both anal cancer and non-anal cancer liver metastases (hazard ratio 6.82, 95 per cent c.i. 2.40 to 19.35, for the entire cohort). Median survival duration and 5-year OS rate among patients with anal cancer and non-anal cancer were 50 months and 45 per cent and 21 months and 25 per cent, respectively. For the entire cohort, only non-radical resection was associated with worse overall survival (hazard ratio 3.21, 95 per cent c.i. 1.24 to 8.30). CONCLUSION: Liver resection/ablation of liver metastases from SCC can result in long-term survival. Survival was superior in treated patients with liver metastases from anal versus non-anal cancer. A negative resection margin is paramount for acceptable outcome

Global Retinoblastoma Presentation and Analysis by National Income Level.

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68]). Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs

Density- and correlation-based table extension

With thousands of data sources available on the Web as well as within organizations, data scientists increasingly spend more time searching for data than analyzing it. In order to ease the task of finding relevant data for data mining projects, this paper presents two data discovery and data integration methods that have been developed in a joint research project by RapidMiner Research and the University of Mannheim. Given a corpus of relational tables, the methods extend a query table with additional attributes and automatically fill these new attributes with data values from the corpus. The first method, densitybased table extension, extends the query table with all attributes that can be filled with data values so that a user-specified density threshold is reached. The second method, correlation-based table extension, extends the query table with all attributes that correlate with a specific attribute of the query table. Both methods are integrated as operators into RapidMiner Studio, a popular data mining environment. This enables data scientists to search for data and apply a wide range of different mining methods to the discovered data within the same environment

Density- and correlation-based table extension

With thousands of data sources available on the Web as well as within organizations, data scientists increasingly spend more time searching for data than analyzing it. In order to ease the task of finding relevant data for data mining projects, this paper presents two data discovery and data integration methods that have been developed in a joint research project by RapidMiner Research and the University of Mannheim. Given a corpus of relational tables, the methods extend a query table with additional attributes and automatically fill these new attributes with data values from the corpus. The first method, densitybased table extension, extends the query table with all attributes that can be filled with data values so that a user-specified density threshold is reached. The second method, correlation-based table extension, extends the query table with all attributes that correlate with a specific attribute of the query table. Both methods are integrated as operators into RapidMiner Studio, a popular data mining environment. This enables data scientists to search for data and apply a wide range of different mining methods to the discovered data within the same environment