Context-aware Services for Mobile Devices: From Architecture Design to Empirical Inference

Currently, mobile devices are aware of user position, which can be provided to mobile apps for the development of tailored services known as Location-Based Services. Further advances on current Location-based Services (LBS), i.e. using any other information from the user such as gender, music preferences etc, may lead to transition from a Location-Based environment to a fully developed ContextAware environment.The current trend towards Context-aware Services (CAS) is reflected in academic research since more than twenty years as well as in the progress in Software Development Kits (SDKs) of the main mobile operating systems, where CAS frameworks are currently being used. However, there is no community agreement for modelling context CAS and little is known about the architecture of these context management frameworks of the mobile operating systems.Based on previous research in the area of CAS, I establish and analyse a reasoning architecture, the Context Engine (CE), that enables the main steps of designing and implementing context-aware services. The chief utility of CAS is their ability to formulate and encapsulate information, obtain user context through context acquisition tools and distribute it to third-party applications that build personalised services based on the provided information. The CE has the responsibility of selecting the optimal context acquisition tool to solve a concrete problem which is discussed in this dissertation.Furthermore, this thesis contributes to the development of context inference tools by studying two particular cases. The first case aims at inferring user (semantic) location information based on mobile phone usage data. This first case has been carried out in collaboration with Microsoft Finland, which provides a similar context inference solution to mobile developers through their Software Development Kit (SDK). The second case aims at inferring user information based on social network information, i.e. infer user information based on his or her connections. Both studies yield positive results and have the potential to be extended to obtain better context acquisition tools and, therefore, better user context

Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects

[EN] Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients¿ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients¿ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.Funding for this study was provided by the authors' various departments, and partially by the CrowdHealth Project (Collective Wisdom Driving Public Health Policies (727560)) and the MTS4up project (DPI2016-80054-R).Asensio Cuesta, S.; Sánchez-García, Á.; Conejero, JA.; Sáez Silvestre, C.; Rivero-Rodriguez, A.; Garcia-Gomez, JM. (2019). Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects. International Journal of Environmental research and Public Health. 16(3):1-18. https://doi.org/10.3390/ijerph16030461S118163Number of Smartphone Users Worldwide from 2014 to 2020 (in Billions)https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/Mirkovic, J., Kaufman, D. R., & Ruland, C. M. (2014). Supporting Cancer Patients in Illness Management: Usability Evaluation of a Mobile App. JMIR mHealth and uHealth, 2(3), e33. doi:10.2196/mhealth.3359Xing Su, Hanghang Tong, & Ping Ji. (2014). Activity recognition with smartphone sensors. Tsinghua Science and Technology, 19(3), 235-249. doi:10.1109/tst.2014.6838194Schmitz Weiss, A. (2013). Exploring News Apps and Location-Based Services on the Smartphone. Journalism & Mass Communication Quarterly, 90(3), 435-456. doi:10.1177/1077699013493788Higgins, J. P. (2016). Smartphone Applications for Patients’ Health and Fitness. The American Journal of Medicine, 129(1), 11-19. doi:10.1016/j.amjmed.2015.05.038Rivenson, Y., Ceylan Koydemir, H., Wang, H., Wei, Z., Ren, Z., Günaydın, H., … Ozcan, A. (2018). Deep Learning Enhanced Mobile-Phone Microscopy. ACS Photonics, 5(6), 2354-2364. doi:10.1021/acsphotonics.8b00146Priye, A., Ball, C. S., & Meagher, R. J. (2018). Colorimetric-Luminance Readout for Quantitative Analysis of Fluorescence Signals with a Smartphone CMOS Sensor. Analytical Chemistry, 90(21), 12385-12389. doi:10.1021/acs.analchem.8b03521Measuring Quality of Life for Cancer Patients: Where Are We Today and Where Are We Headed Tomorrow?http://blog.mdsol.com/measuring-quality-of-life-for-cancer-patients-where-are-we-today-and-where-are-we-headed-tomorrow/Zulueta, J., Piscitello, A., Rasic, M., Easter, R., Babu, P., Langenecker, S. A., … Leow, A. (2018). Predicting Mood Disturbance Severity with Mobile Phone Keystroke Metadata: A BiAffect Digital Phenotyping Study. Journal of Medical Internet Research, 20(7), e241. doi:10.2196/jmir.9775Caruso, R., GiuliaNanni, M., Riba, M. B., Sabato, S., & Grassi, L. (2017). Depressive Spectrum Disorders in Cancer: Diagnostic Issues and Intervention. A Critical Review. Current Psychiatry Reports, 19(6). doi:10.1007/s11920-017-0785-7THE WHOQOL GROUP. (1998). Development of the World Health Organization WHOQOL-BREF Quality of Life Assessment. Psychological Medicine, 28(3), 551-558. doi:10.1017/s0033291798006667Basic Issues Concerning Health-Related Quality of Life. (2017). Central European Journal of Urology, 70(2). doi:10.5173/ceju.2017.923Sloan, J. A. (2011). Metrics to Assess Quality of Life After Management of Early-Stage Lung Cancer. The Cancer Journal, 17(1), 63-67. doi:10.1097/ppo.0b013e31820e15dcBordoni, R., Ciardiello, F., von Pawel, J., Cortinovis, D., Karagiannis, T., Ballinger, M., … Rittmeyer, A. (2018). Patient-Reported Outcomes in OAK: A Phase III Study of Atezolizumab Versus Docetaxel in Advanced Non–Small-cell Lung Cancer. Clinical Lung Cancer, 19(5), 441-449.e4. doi:10.1016/j.cllc.2018.05.011Hartkopf, A. D., Graf, J., Simoes, E., Keilmann, L., Sickenberger, N., Gass, P., … Wallwiener, M. (2017). Electronic-Based Patient-Reported Outcomes: Willingness, Needs, and Barriers in Adjuvant and Metastatic Breast Cancer Patients. JMIR Cancer, 3(2), e11. doi:10.2196/cancer.6996Wallwiener, M., Matthies, L., Simoes, E., Keilmann, L., Hartkopf, A. D., Sokolov, A. N., … Brucker, S. Y. (2017). Reliability of an e-PRO Tool of EORTC QLQ-C30 for Measurement of Health-Related Quality of Life in Patients With Breast Cancer: Prospective Randomized Trial. Journal of Medical Internet Research, 19(9), e322. doi:10.2196/jmir.8210Gresham, G., Hendifar, A. E., Spiegel, B., Neeman, E., Tuli, R., Rimel, B. J., … Shinde, A. M. (2018). Wearable activity monitors to assess performance status and predict clinical outcomes in advanced cancer patients. npj Digital Medicine, 1(1). doi:10.1038/s41746-018-0032-6BOHANNON, R. W. (1997). Comfortable and maximum walking speed of adults aged 20—79 years: reference values and determinants. Age and Ageing, 26(1), 15-19. doi:10.1093/ageing/26.1.15Pérez-García, V. M., Fitzpatrick, S., Pérez-Romasanta, L. A., Pesic, M., Schucht, P., Arana, E., & Sánchez-Gómez, P. (2016). Applied mathematics and nonlinear sciences in the war on cancer. Applied Mathematics and Nonlinear Sciences, 1(2), 423-436. doi:10.21042/amns.2016.2.00036Shin, W., Song, S., Jung, S.-Y., Lee, E., Kim, Z., Moon, H.-G., … Lee, J. E. (2017). The association between physical activity and health-related quality of life among breast cancer survivors. Health and Quality of Life Outcomes, 15(1). doi:10.1186/s12955-017-0706-9Wearable Fitness Monitors Useful in Cancer Treatment, Study Findswww.sciencedaily.com/releases/2018/05/180501130856.htmBade, B. C., Brooks, M. C., Nietert, S. B., Ulmer, A., Thomas, D. D., Nietert, P. J., … Silvestri, G. A. (2016). Assessing the Correlation Between Physical Activity and Quality of Life in Advanced Lung Cancer. Integrative Cancer Therapies, 17(1), 73-79. doi:10.1177/1534735416684016Fortner, B. V., Stepanski, E. J., Wang, S. C., Kasprowicz, S., & Durrence, H. H. (2002). Sleep and Quality of Life in Breast Cancer Patients. Journal of Pain and Symptom Management, 24(5), 471-480. doi:10.1016/s0885-3924(02)00500-6Mishra, S. I., Scherer, R. W., Snyder, C., Geigle, P., & Gotay, C. (2014). Are Exercise Programs Effective for Improving Health-Related Quality of Life Among Cancer Survivors? A Systematic Review and Meta-Analysis. Oncology Nursing Forum, 41(6), E326-E342. doi:10.1188/14.onf.e326-e342Ratcliff, C. G., Lam, C. Y., Arun, B., Valero, V., & Cohen, L. (2014). Ecological momentary assessment of sleep, symptoms, and mood during chemotherapy for breast cancer. Psycho-Oncology, 23(11), 1220-1228. doi:10.1002/pon.3525Cox, S. M., Lane, A., & Volchenboum, S. L. (2018). Use of Wearable, Mobile, and Sensor Technology in Cancer Clinical Trials. JCO Clinical Cancer Informatics, (2), 1-11. doi:10.1200/cci.17.00147Brown, W., Yen, P.-Y., Rojas, M., & Schnall, R. (2013). Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. Journal of Biomedical Informatics, 46(6), 1080-1087. doi:10.1016/j.jbi.2013.08.001Darlow, S., & Wen, K.-Y. (2016). Development testing of mobile health interventions for cancer patient self-management: A review. Health Informatics Journal, 22(3), 633-650. doi:10.1177/1460458215577994Martin Sanchez, F., Gray, K., Bellazzi, R., & Lopez-Campos, G. (2014). Exposome informatics: considerations for the design of future biomedical research information systems. Journal of the American Medical Informatics Association, 21(3), 386-390. doi:10.1136/amiajnl-2013-001772Kim, H. H., Lee, S. Y., Baik, S. Y., & Kim, J. H. (2015). MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices. International Journal of Medical Informatics, 84(12), 1099-1110. doi:10.1016/j.ijmedinf.2015.08.005Kessel, K. A., Vogel, M. M., Alles, A., Dobiasch, S., Fischer, H., & Combs, S. E. (2018). Mobile App Delivery of the EORTC QLQ-C30 Questionnaire to Assess Health-Related Quality of Life in Oncological Patients: Usability Study. JMIR mHealth and uHealth, 6(2), e45. doi:10.2196/mhealth.9486Elsbernd, A., Hjerming, M., Visler, C., Hjalgrim, L. L., Niemann, C. U., Boisen, K., & Pappot, H. (2018). 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High serum levels of tissue inhibitor of matrix metalloproteinase-1 during the first week of a malignant middle cerebral artery infarction in non-surviving patients

Background: Higher circulating levels of tissue inhibitor of matrix metalloproteinases (TIMP)-1 early after ischemic stroke have been associated with lower survival. The objectives of this study were to determine serum TIMP-1 levels during the first week of a severe cerebral infarction in surviving and non-surviving patients, and whether those levels during the first week could be used as a mortality biomarker for these patients. Methods: We included patients with severe malignant middle cerebral artery infarction (MMCAI) defined as computer tomography showing ischaemic changes in more than 50% of the middle cerebral artery territory and Glasgow Coma Scale (GCS) ≤ 8. We measured serum levels of matrix metalloproteinases (MMP)-9 and TIMP-1. End-point study was 30-day mortality. Results: We found higher TIMP-1 concentrations at days 1 (p < 0.001), 4 (p = 0.001), and 8 (p = 0.03) of MMCAI in nonurviving (n = 34) than in surviving (n = 34) patients. We found lower serum MMP-9 concentrations at day 1 (p = 0.03) of MMCAI and no significant differences at days 4 and 8. ROC curve analysis of TIMP-1 concentrations performed at days 1, 4, and 8 of MMCAI showed an area under curve to predict 30-day mortality of 81% (p < 0.001), 80% (p < 0.001) and 72% (p = 0.07) respectively. Conclusions: The new findings of our study were that non-surviving MMCAI patients showed higher serum TIMP-1 levels during the first week of MMCAI that surviving patients, and those levels during the first week of MMCAI could be used as mortality biomarkers

Cabbage and fermented vegetables : From death rate heterogeneity in countries to candidates for mitigation strategies of severe COVID-19

Large differences in COVID-19 death rates exist between countries and between regions of the same country. Some very low death rate countries such as Eastern Asia, Central Europe, or the Balkans have a common feature of eating large quantities of fermented foods. Although biases exist when examining ecological studies, fermented vegetables or cabbage have been associated with low death rates in European countries. SARS-CoV-2 binds to its receptor, the angiotensin-converting enzyme 2 (ACE2). As a result of SARS-CoV-2 binding, ACE2 downregulation enhances the angiotensin II receptor type 1 (AT(1)R) axis associated with oxidative stress. This leads to insulin resistance as well as lung and endothelial damage, two severe outcomes of COVID-19. The nuclear factor (erythroid-derived 2)-like 2 (Nrf2) is the most potent antioxidant in humans and can block in particular the AT(1)R axis. Cabbage contains precursors of sulforaphane, the most active natural activator of Nrf2. Fermented vegetables contain many lactobacilli, which are also potent Nrf2 activators. Three examples are: kimchi in Korea, westernized foods, and the slum paradox. It is proposed that fermented cabbage is a proof-of-concept of dietary manipulations that may enhance Nrf2-associated antioxidant effects, helpful in mitigating COVID-19 severity.Peer reviewe

Nrf2-interacting nutrients and COVID-19 : time for research to develop adaptation strategies

There are large between- and within-country variations in COVID-19 death rates. Some very low death rate settings such as Eastern Asia, Central Europe, the Balkans and Africa have a common feature of eating large quantities of fermented foods whose intake is associated with the activation of the Nrf2 (Nuclear factor (erythroid-derived 2)-like 2) anti-oxidant transcription factor. There are many Nrf2-interacting nutrients (berberine, curcumin, epigallocatechin gallate, genistein, quercetin, resveratrol, sulforaphane) that all act similarly to reduce insulin resistance, endothelial damage, lung injury and cytokine storm. They also act on the same mechanisms (mTOR: Mammalian target of rapamycin, PPAR gamma:Peroxisome proliferator-activated receptor, NF kappa B: Nuclear factor kappa B, ERK: Extracellular signal-regulated kinases and eIF2 alpha:Elongation initiation factor 2 alpha). They may as a result be important in mitigating the severity of COVID-19, acting through the endoplasmic reticulum stress or ACE-Angiotensin-II-AT(1)R axis (AT(1)R) pathway. Many Nrf2-interacting nutrients are also interacting with TRPA1 and/or TRPV1. Interestingly, geographical areas with very low COVID-19 mortality are those with the lowest prevalence of obesity (Sub-Saharan Africa and Asia). It is tempting to propose that Nrf2-interacting foods and nutrients can re-balance insulin resistance and have a significant effect on COVID-19 severity. It is therefore possible that the intake of these foods may restore an optimal natural balance for the Nrf2 pathway and may be of interest in the mitigation of COVID-19 severity

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

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Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Combined searches for the production of supersymmetric top quark partners in proton-proton collisions at root s=13 TeV

A combination of searches for top squark pair production using proton-proton collision data at a center-of-mass energy of 13 TeV at the CERN LHC, corresponding to an integrated luminosity of 137 fb(-1) collected by the CMS experiment, is presented. Signatures with at least 2 jets and large missing transverse momentum are categorized into events with 0, 1, or 2 leptons. New results for regions of parameter space where the kinematical properties of top squark pair production and top quark pair production are very similar are presented. Depending on themodel, the combined result excludes a top squarkmass up to 1325 GeV for amassless neutralino, and a neutralinomass up to 700 GeV for a top squarkmass of 1150 GeV. Top squarks with masses from 145 to 295 GeV, for neutralino masses from 0 to 100 GeV, with a mass difference between the top squark and the neutralino in a window of 30 GeV around the mass of the top quark, are excluded for the first time with CMS data. The results of theses searches are also interpreted in an alternative signal model of dark matter production via a spin-0 mediator in association with a top quark pair. Upper limits are set on the cross section for mediator particle masses of up to 420 GeV

Probing effective field theory operators in the associated production of top quarks with a Z boson in multilepton final states at root s=13 TeV

Peer reviewe