1,409 research outputs found

    The efficiency of fan-pad cooling system in greenhouse and building up of internal greenhouse temperature map

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    During summer periods, high temperature values that are being formed in greenhouses can greatly influence the efficiency of production workers and also decrease the productivity of plants grown there. A greenhouse production without the cooling systems can be sustained at the desirable level by imposing summer restrictions in the areas with warm climate, and by starting cooling in the areas with cold climate. A statement can be made regarding both utility and efficiency of fan-pad cooling systems that they tend to go up in the areas with low relative air humidity. The present study has been carried out in order to either prove or disprove this statement. We have attempted to create a map of internal greenhouse temperature distribution via determining the system’s efficiency. As a result of this study, it was determined that since air temperature and relative humidity in the air tend to decrease during summer months by using fan-pad cooling system, temperatures in the greenhouse can be consequently lowered down to 10-12°C. Statistical analysis revealed remarkable differences (

    Predicting invasive breast cancer versus DCIS in different age groups.

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    BackgroundIncreasing focus on potentially unnecessary diagnosis and treatment of certain breast cancers prompted our investigation of whether clinical and mammographic features predictive of invasive breast cancer versus ductal carcinoma in situ (DCIS) differ by age.MethodsWe analyzed 1,475 malignant breast biopsies, 1,063 invasive and 412 DCIS, from 35,871 prospectively collected consecutive diagnostic mammograms interpreted at University of California, San Francisco between 1/6/1997 and 6/29/2007. We constructed three logistic regression models to predict the probability of invasive cancer versus DCIS for the following groups: women ≥ 65 (older group), women 50-64 (middle age group), and women < 50 (younger group). We identified significant predictors and measured the performance in all models using area under the receiver operating characteristic curve (AUC).ResultsThe models for older and the middle age groups performed significantly better than the model for younger group (AUC = 0.848 vs, 0.778; p = 0.049 and AUC = 0.851 vs, 0.778; p = 0.022, respectively). Palpability and principal mammographic finding were significant predictors in distinguishing invasive from DCIS in all age groups. Family history of breast cancer, mass shape and mass margins were significant positive predictors of invasive cancer in the older group whereas calcification distribution was a negative predictor of invasive cancer (i.e. predicted DCIS). In the middle age group--mass margins, and in the younger group--mass size were positive predictors of invasive cancer.ConclusionsClinical and mammographic finding features predict invasive breast cancer versus DCIS better in older women than younger women. Specific predictive variables differ based on age

    Qualitative characterization of healthcare wastes

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    The biological hazard inherent in the clinical wastes should be considered during the management and treatment process as well as the disposal into the environment. In this chapter, the risks associated with the clinical wastes as well as the management of these wastes are discussed. The chapter focused on reviewing the types of healthcare wastes generated from hospitals and clinics as well as the regulations and management practices used for these wastes. Moreover, the health risk associated with the infectious agents which have the potential to be transmitted into the environment. It has appeared that the clinical wastes represent real hazards for the human health and the environment if they were not managed properly

    Cost-effectiveness of adjuvant paclitaxel and trastuzumab for early-stage node-negative, HER2-positive breast cancer

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    Adjuvant paclitaxel and trastuzumab has been shown to be an effective regimen with low risk of cancer recurrence and treatment-related toxicities in early-stage node-negative, HER2-positive breast cancer. We investigated the cost-effectiveness of this regimen

    Testbeam and Laboratory Characterization of CMS 3D Pixel Sensors

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    The pixel detector is the innermost tracking device in CMS, reconstructing interaction vertices and charged particle trajectories. The sensors located in the innermost layers of the pixel detector must be upgraded for the ten-fold increase in luminosity expected with the High- Luminosity LHC (HL-LHC) phase. As a possible replacement for planar sensors, 3D silicon technology is under consideration due to its good performance after high radiation fluence. In this paper, we report on pre- and post- irradiation measurements for CMS 3D pixel sensors with different electrode configurations. The effects of irradiation on electrical properties, charge collection efficiency, and position resolution of 3D sensors are discussed. Measurements of various test structures for monitoring the fabrication process and studying the bulk and surface properties, such as MOS capacitors, planar and gate-controlled diodes are also presented.Comment: 14 page

    Gamma Ray Bursts: Observations and Theoretical Conjectures

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    Gamma Ray Bursts (GRBs) are short bursts of very high energy photons which were discovered in the late 1960s. Ever since their discovery, scientists have wondered about their origin. Nowadays it is known that they originate outside the Milky Way because of their high red shift rst measured in the afterglows thanks to the Beppo-SAX satellite and ground-based observations. However, theoreticians still do not agree about the mechanism that generates the bursts, and different competing models are animatedly debated. Current GRB experiments include the Swift satellite and the Pierre Auger Observatory that could detect GRBs with an increase of the background. A forthcoming dedicated experiment is GLAST, a satellite observatory for detecting gamma rays with energies up to 300 GeV, whose launch is scheduled for early 2008

    Deficiency in origin licensing proteins impairs cilia formation: implications for the aetiology of meier-gorlin syndrome

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    Mutations in ORC1, ORC4, ORC6, CDT1, and CDC6, which encode proteins required for DNA replication origin licensing, cause Meier-Gorlin syndrome (MGS), a disorder conferring microcephaly, primordial dwarfism, underdeveloped ears, and skeletal abnormalities. Mutations in ATR, which also functions during replication, can cause Seckel syndrome, a clinically related disorder. These findings suggest that impaired DNA replication could underlie the developmental defects characteristic of these disorders. Here, we show that although origin licensing capacity is impaired in all patient cells with mutations in origin licensing component proteins, this does not correlate with the rate of progression through S phase. Thus, the replicative capacity in MGS patient cells does not correlate with clinical manifestation. However, ORC1-deficient cells from MGS patients and siRNA-mediated depletion of origin licensing proteins also have impaired centrosome and centriole copy number. As a novel and unexpected finding, we show that they also display a striking defect in the rate of formation of primary cilia. We demonstrate that this impacts sonic hedgehog signalling in ORC1-deficient primary fibroblasts. Additionally, reduced growth factor-dependent signaling via primary cilia affects the kinetics of cell cycle progression following cell cycle exit and re-entry, highlighting an unexpected mechanism whereby origin licensing components can influence cell cycle progression. Finally, using a cell-based model, we show that defects in cilia function impair chondroinduction. Our findings raise the possibility that a reduced efficiency in forming cilia could contribute to the clinical features of MGS, particularly the bone development abnormalities, and could provide a new dimension for considering developmental impacts of licensing deficiency

    A comprehensive methodology for determining the most informative mammographic features

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    This study aims to determine the most informative mammographic features for breast cancer diagnosis using mutual information (MI) analysis. Our Health Insurance Portability and Accountability Act-approved database consists of 44,397 consecutive structured mammography reports for 20,375 patients collected from 2005 to 2008. The reports include demographic risk factors (age, family and personal history of breast cancer, and use of hormone therapy) and mammographic features from the Breast Imaging Reporting and Data System lexicon. We calculated MI using Shannon's entropy measure for each feature with respect to the outcome (benign/malignant using a cancer registry match as reference standard). In order to evaluate the validity of the MI rankings of features, we trained and tested naïve Bayes classifiers on the feature with tenfold cross-validation, and measured the predictive ability using area under the ROC curve (AUC). We used a bootstrapping approach to assess the distributional properties of our estimates, and the DeLong method to compare AUC. Based on MI, we found that mass margins and mass shape were the most informative features for breast cancer diagnosis. Calcification morphology, mass density, and calcification distribution provided predictive information for distinguishing benign and malignant breast findings. Breast composition, associated findings, and special cases provided little information in this task. We also found that the rankings of mammographic features with MI and AUC were generally consistent. MI analysis provides a framework to determine the value of different mammographic features in the pursuit of optimal (i.e., accurate and efficient) breast cancer diagnosis. © 2013 Society for Imaging Informatics in Medicine

    Effect of time to diagnostic testing for breast, cervical, and colorectal cancer screening abnormalities on screening efficacy: A modeling study

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    Background: Patients who receive an abnormal cancer screening result require follow-up for diagnostic testing, but the time to follow-up varies across patients and practices. Methods: We used a simulation study to estimate the change in lifetime screening benefits when time to follow-up for breast, cervical, and colorectal cancers was increased. Estimates were based on four independently developed microsimulation models that each simulated the life course of adults eligible for breast (women ages 50–74 years), cervical (women ages 21–65 years), or colorectal (adults ages 50–75 years) cancer screening. We assumed screening based on biennial mammography for breast cancer, triennial Papanicolaou testing for cervical cancer, and annual fecal immunochemical testing for colorectal cancer. For each cancer type, we simulated diagnostic testing immediately and at 3, 6, and 12 months after an abnormal screening exam. Results: We found declines in screening benefit with longer times to diagnostic testing, particularly for breast cancer screening. Compared to immediate diagnostic testing, testing at 3 months resulted in reduced screening benefit, with fewer undiscounted life years gained per 1,000 screened (breast: 17.3%, cervical: 0.8%, colorectal: 2.0% and 2.7%, from two colorectal cancer models), fewer cancers prevented (cervical: 1.4% fewer, colorectal: 0.5% and 1.7% fewer, respectively), and, for breast and colorectal cancer, a less favorable stage distribution. Conclusions: Longer times to diagnostic testing after an abnormal screening test can decrease screening effectiveness, but the impact varies substantially by cancer type. Impact: Understanding the impact of time to diagnostic testing on screening effectiveness can help inform quality improvement efforts. Cancer Epidemiol Biomarkers Prev; 27(2); 158–64. 2017 AACR
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