511 research outputs found

    Prediction of Flood Severity Level Via Processing IoT Sensor Data Using Data Science Approach

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    The ‘riverine flooding’ is deemed a catastrophic phenomenon caused by extreme climate changes and other ecological factors (e.g., amount of sunlight), which are difficult to predict and monitor. However, the use of internet of things (IoT), various types of sensing including social sensing, 5G wireless communication and big data analysis have devised advanced tools for early prediction and management of distrust events. To this end, this paper amalgamates machine learning models and data analytics approaches along-with IoT sensor data to investigate attribute importance for the prediction of risk levels in flood. The paper presents three river levels: normal, medium and high-risk river levels for machine learning models. Performance is evaluated with varying configurations and evaluations setup including training and testing of support vector machine and random forest using principal components analysis-based dimension reduced dataset. In addition, we investigated the use of synthetic minority over-sampling technique to balance the class representations within dataset. As expected, the results indicated that a “balanced” representation of data samples achieved high accuracy (nearly 93%) when benchmarked with “imbalanced” data samples using random forest classifier 10-folds cross-validation

    Clinical and medication profiles stratified by household income in patients referred for diabetes care

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    BACKGROUND: Low income individuals with diabetes are at particularly high risk for poor health outcomes. While specialized diabetes care may help reduce this risk, it is not currently known whether there are significant clinical differences across income groups at the time of referral. The objective of this study is to determine if the clinical profiles and medication use of patients referred for diabetes care differ across income quintiles. METHODS: This cross-sectional study was conducted using a Canadian, urban, Diabetes Education Centre (DEC) database. Clinical information on the 4687 patients referred to the DEC from May 2000 – January 2002 was examined. These data were merged with 2001 Canadian census data on income. Potential differences in continuous clinical parameters across income quintiles were examined using regression models. Differences in medication use were examined using Chi square analyses. RESULTS: Multivariate regression analysis indicated that income was negatively associated with BMI (p < 0.0005) and age (p = 0.023) at time of referral. The highest income quintiles were found to have lower serum triglycerides (p = 0.011) and higher HDL-c (p = 0.008) at time of referral. No significant differences were found in HBA1C, LDL-c or duration of diabetes. The Chi square analysis of medication use revealed that despite no significant differences in HBA1C, the lowest income quintiles used more metformin (p = 0.001) and sulfonylureas (p < 0.0005) than the wealthy. Use of other therapies were similar across income groups, including lipid lowering medications. High income patients were more likely to be treated with diet alone (p < 0.0005). CONCLUSION: Our findings demonstrate that low income patients present to diabetes clinic older, heavier and with a more atherogenic lipid profile than do high income patients. Overall medication use was higher among the lower income group suggesting that differences in clinical profiles are not the result of under-treatment, thus invoking lifestyle factors as potential contributors to these findings

    Locating Functionalized Gold Nanoparticles Using Electrical Impedance Tomography

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    Abstract Objective: An imaging device to locate functionalized nanoparticles, whereby therapeutic agents are transported from the site of administration specifically to diseased tissues, remains a challenge for pharmaceutical research. Here, we show a new method based on electrical impedance tomography (EIT) to provide images of the location of gold nanoparticles (GNPs) and the excitation of GNPs with radio frequencies (RF) to change impedance permitting an estimation of their location in cell models Methods: We have created an imaging system using quantum cluster GNPs as a contrast agent, activated with RF fields to heat the functionalized GNPs, which causes a change in impedance in the surrounding region. This change is then identified with EIT. Results: Images of impedance changes of around 804% are obtained for a sample of citrate stabilized GNPs in a solution of phosphate-buffered saline. A second quantification was carried out using colorectal cancer cells incubated with culture media, and the internalization of GNPs into the colorectal cancer cells was undertaken to compare them with the EIT images. When the cells were incubated with functionalized GNPs, the change was more apparent, approximately 402%. This change was reflected in the EIT image as the cell area was more clearly identifiable from the rest of the area. Significance: EIT can be used as a new method to locate functionalized GNPs in human cells and help in the development of GNP-based drugs in humans to improve their efficacy in the future

    Absence of bias against smokers in access to coronary revascularization after cardiac catheterization

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    OBJECTIVE: Many consider smoking to be a personal choice for which individuals should be held accountable. We assessed whether there is any evidence of bias against smokers in cardiac care decision-making by determining whether smokers were as likely as non-smokers to undergo revascularization procedures after cardiac catheterization. DESIGN: Prospective cohort study. Subjects and setting. All patients undergoing cardiac catheterization in Alberta, Canada. MAIN MEASURE: Patients were categorized as current smokers, former smokers, or never smokers, and then compared for their risk-adjusted likelihood of undergoing revascularization procedures (percutaneous coronary intervention or coronary artery bypass grafting) after cardiac catheterization. RESULTS: Among 20406 patients undergoing catheterization, 25.4% were current smokers at the time of catheterization, 36.6% were former smokers, and 38.0% had never smoked. When compared with never smokers (reference group), the hazard ratio for undergoing any revascularization procedure after catheterization was 0.98 (95% CI 0.93-1.03) for current smokers and 0.98 (0.94-1.03) for former smokers. The hazard ratio for undergoing coronary artery bypass grafting was 1.09 (1.00-1.19) for current smokers and 1.00 (0.93-1.08) for former smokers. For percutaneous coronary intervention, the hazard ratios were 0.93 (0.87-0.99) for current smokers and 1.00 (0.94-1.06) for former smokers. CONCLUSION: Despite potential for discrimination on the basis of smoking status, current and former smokers undergoing cardiac catheterization in Alberta, Canada were as likely to undergo revascularization procedures as catheterization patients who had never smoked

    Admission Hyperglycemia Predicts a Worse Outcome in Stroke Patients Treated With Intravenous Thrombolysis

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    OBJECTIVE: Admission hyperglycemia has been associated with worse outcomes in ischemic stroke. We hypothesized that hyperglycemia (glucose &gt;8.0 mmol/l) in the hyperacute phase would be independently associated with increased mortality, symptomatic intracerebral hemorrhage (SICH), and poor functional status at 90 days in stroke patients treated with intravenous tissue plasminogen activator (IV-tPA). RESEARCH DESIGN AND METHODS: Using data from the prospective, multicenter Canadian Alteplase for Stroke Effectiveness Study (CASES), the association between admission glucose &gt;8.0 mmol/l and mortality, SICH, and poor functional status at 90 days (modified Rankin Scale &gt;1) was examined. Similar analyses examining glucose as a continuous measure were conducted. RESULTS: Of 1,098 patients, 296 (27%) had admission hyperglycemia, including 18% of those without diabetes and 70% of those with diabetes. After multivariable logistic regression, admission hyperglycemia was found to be independently associated with increased risk of death (adjusted risk ratio 1.5 [95% CI 1.2-1.9]), SICH (1.69 [0.95-3.00]), and a decreased probability of a favorable outcome at 90 days (0.7 [0.5-0.9]). An incremental risk of death and SICH and unfavorable 90-day outcomes was observed with increasing admission glucose. This observation held true for patients with and without diabetes. CONCLUSIONS: In this cohort of IV-tPA-treated stroke patients, admission hyperglycemia was independently associated with increased risk of death, SICH, and poor functional status at 90 days. Treatment trials continue to be urgently needed to determine whether this is a modifiable risk factor for poor outcome

    Engineering of quantum dot photon sources via electro-elastic fields

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    The possibility to generate and manipulate non-classical light using the tools of mature semiconductor technology carries great promise for the implementation of quantum communication science. This is indeed one of the main driving forces behind ongoing research on the study of semiconductor quantum dots. Often referred to as artificial atoms, quantum dots can generate single and entangled photons on demand and, unlike their natural counterpart, can be easily integrated into well-established optoelectronic devices. However, the inherent random nature of the quantum dot growth processes results in a lack of control of their emission properties. This represents a major roadblock towards the exploitation of these quantum emitters in the foreseen applications. This chapter describes a novel class of quantum dot devices that uses the combined action of strain and electric fields to reshape the emission properties of single quantum dots. The resulting electro-elastic fields allow for control of emission and binding energies, charge states, and energy level splittings and are suitable to correct for the quantum dot structural asymmetries that usually prevent these semiconductor nanostructures from emitting polarization-entangled photons. Key experiments in this field are presented and future directions are discussed.Comment: to appear as a book chapter in a compilation "Engineering the Atom-Photon Interaction" published by Springer in 2015, edited by A. Predojevic and M. W. Mitchel

    Određivanje aflatoksina, okratoksina A, fumonizina i zearalenona u žitaricama i krmivu primjenom kompetetivnoga direktnog imunoenzimatskog testa (CD-ELISA) i tankoslojne kromatografije (TLC)

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    Aspergillus, Penicillium, and Fusarium species frequently contaminate crops. For this reason mycotoxins such as afl atoxins (AFs), ochratoxin A (OTA), fumonisins (FBs), and zearalenone (ZEA) are found in food and feed in a wide range of concentrations, depending on environmental and storage conditions. Consumption of mycotoxin-contaminated food and feed has been associated with acute and chronic poisoning and carcinoma. The aim of this study was to determine the incidence and co-occurrence of AFs (B1+B2+G1+G2), OTA, FBs (B1+B2+B3), and ZEA in 37 samples of cereals and feed randomly collected in 2007 from households of an endemic nephropathy (EN) area in Croatia. The mycotoxins were determined using the competitive direct ELISA test (CD-ELISA) in combination with thin-layer chromatography (TLC). The most frequent mycotoxin was ZEA (92 %, mean 318.3 μg kg-1), followed by FBs (27 %, 3690 μg kg-1), AFs (24.3 %, 4.6 μg kg-1), and OTA (16.2 %, 9.8 μg kg-1). Levels of AFs, ZEA, and FBs detected by CD-ELISA signifi cantly correlated with the TLC results. However, only one OTA-positive sample was confi rmed by TLC due to its high limit of detection. The levels of these mycotoxins were below the permissible limit for animal feed. Twenty-nine percent of cereals were contaminated with FBs, OTA, or ZEA in mass fractions above the permissible limit for humans. Co-occurrence of two toxins varied between 4.2 % and 54 % and of three between 4.2 % and 7.6 %. Prolonged co-exposure to AFs, OTA, FBs, and ZEA might increase the risk of various chronic diseases.Vrste plijesni iz rodova Aspergillus, Penicillium i Fusarium česti su kontaminanti usjeva te na takvim supstratima tvore mikotoksine. Stoga su žitarice i krmiva često kontaminirana afl atoksinima (AFs), okratoksinom A (OTA), fumonizinima (FBs) i zearalenonom (ZEA) u različitim koncentracijama ovisno o mikroklimatskim uvjetima na polju i u skladištu. Konzumiranje hrane kontaminirane mikotoksinima često je povezano s akutnim ili kroničnim trovanjima, ali i s razvojem karcinoma. Cilj ovog rada bio je odrediti istodobnu pojavnost AFs (B1+B2+G1+G2), OTA, FBs (B1+B2+B3) i ZEA u uzorcima žitarica i krme (N=37) koji su nasumično skupljeni u individualnim domaćinstvima na području endemske nefropatije (EN) u Hrvatskoj (2007). Za određivanje navedenih mikotoksina korišten je kompetitivni direktni ELISA-test (CD-ELISA) u kombinaciji s tankoslojnom kromatografi jom (TLC). Najzastupljeniji mikotoksin bio je ZEA (92 %, srednja koncentracija 318.3 μg kg-1), nakon čega slijede FBs (27 %, 3690 μg kg-1), AFs (24.3 %, 4.6 μg kg-1) te OTA (16.2 %, 9.8 μg kg-1). Koncentracije AFs, FBs i ZEA određene CD-ELISA-testom statistički značajno koreliraju s rezultatima dobivenim s TLC. OTA je potvrđen metodom TLC samo u jednom uzorku zbog visokog limita detekcije. Dokazane koncentracije su ispod razina dopuštenih za krmiva, dok je 29 % uzoraka žitarica sadržavalo FBs, OTA ili ZEA u koncentracijama iznad dopuštenih u hrani za ljude. Kokontaminacija s dvama odnosno trima toksinima varirala je između 4.2 % i 54 % odnosno između 4.2 % i 7.6 %. Dugotrajni unos AFs, OTA, FBs i ZEA putem hrane može povećati rizik od razvoja različitih kroničnih bolesti zbog njihova mogućega sinergističkog djelovanja
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