how accurately the test can discriminate the disease. Different cut points result in different sensitivities and specificities. For a given test, there is a tradeoff between the sensitivity and specificity. For example, if a higher test score indicates greater likelihood of being diseased, the lower cutoff will yield highersensitivity but lower specificity, in which case the test can correctly classify most of the diseased subjects as diseased, but also gives a high chance of misclassifying the non-diseased subjects as diseased, and vice versa for a higher cutoff. An ROC curve provides us with a full picture of how the test discriminates between diseased and non-diseased, with the portion closer to the top left corner being better able to discriminate. The diagonal line shows no ability of discrimination.
As shown in Figure 7, the dynamic range of precursor intensity for peptides identified by the Q Exactive mass spectrometer is at least one order of magnitude larger than that generated by the TripleTOF 5600. This suggests that, compared to TripleTOF 5600, the Q Exactive instrument not only has lower detection limits in full-scan MS thus giving access to more low-abundance precursors, but also has highersensitivity MS/MS, generating higher quality fragmentation spectra from those precursors.
benchmark datasets while PSO-DCA performed better only on two datasets. Likewise, GA-DCA led overall highersensitivity performances on seven datasets, better than PSO-DCA which performed better only on three datasets. The highest and lowest sensitivity produced by the GA-DCA are 99.18% on the Heart Statlog datset (STAT), and 95.18% on the Blood Transfusion dataset (BTSC), respectively, while the PSO-DCA produced highest and lowest sensitivity of 100.0% on Blood Transfusion Service Centre (BTSC) and 84.37% on Liver Disorders (LD), respectively. Although the performances of PSO-DCA regarding specificity for majority of the datasets are comparable to those of the GA-PSO, GA-DCA outperformed the PSO-DCA on four datasets and produced similar or no significantly different performances on the rest of the datasets. Therefore, the GA-DCA is more preferable in terms of clas- sification accuracy, sensitivity and specificity when compared to PSO-DCA. Furthermore, it is clear that GA is applicable for optimising the parameters of the DCA with effective classification performances.
MAC model ensure confidentiality and integrity of data by controlling information flow, this does not feature in DAC model. It has a policy that is centrally controlled by security policy administrator and cannot be violated by the users ((Punithasurya et al, 2012). The classification of all subject and object in a MAC model for the process of access decision are based on predefined sensitivity levels. To achieve information integrity in MAC model one of the rules is that there is a restriction to the flow of information. It ensures that information in highersensitivity level is restricted to that level alone. There is no cross link of information from highersensitivity level to lower sensitivity level (Sandh, 2000). For a cloud based applications multilevel classification of information is required by the cloud service provider in other to differentiate between the users and the resources being accessed. It is easy to monitor the current access state of the object in MAC model because each object to be accessed has an attached security code (Ferraiolo et al, 1999 &2000). It is used in military and government application where the security is very strict and tight. MAC model are more robust than DAC model for data protection, however enforcement of MAC policies is difficult for cloud based application. Also the security code once identified to a particular subject in the hierarchy will not be modified. These entire shortcomings are addressed by RBAC.
-731- diagnosis was based on the history, clinical examination, serial cardiac cTnI results, and data from medical records. The sensitivity of IMA at presentation for an ischemic origin of chest pain was 82%, the specificity was 46%, the negative predictive value was 59%, and the positive predictive value was 72%. Furthermore, IMA had a highersensitivity than the 12-lead ECG and initial cTnI levels for the diagnosis of ACS, whereas the combination of ECG, cTnI and IMA identified 95% of patients whose chest pain was attributable to ischemic heart disease.
We also evaluated the relationship between ex vivo phenotype and PFS (represented by time to tumor progression). Among the 45 patients from whom we successfully established LCLs, 10 patients were lost to follow-up. Using AUC obtained from the remaining 35 patient-derived LCLs, Cox regression and Kaplan-Meier analysis showed that patients with lower 5ʹ-DFUR AUC (highersensitivity) had significantly better outcomes (Figure 1). These patients whose LCLs were more sensitive to 5ʹ-DFUR (defined as the lower halves of AUC distribution curve, Supplementary Figure 4), had a significantly longer PFS when compared to those patients whose LCLs were less sensitive to 5ʹ-DFUR (median PFS: 9-month vs. 6-month, log rank p = 0.017). In addition, after adjusting for other known important prognostic clinical variables such as presence of hepatic metastases and age, the positive correlation between ex vivo phenotype and clinical survival remained significant (p = 0.025). Overall, these data suggest that ex vivo capecitabine sensitivity obtained from patient-derived LCL models may predict patients’ clinical responses.
under any mass distribution and for all flexural modes. We demonstrated the applicability of the equations for the first four flexural modes in the case mass can adsorb over the full length of a cantilever and for two different types of can- tilevers. Small amounts of mass can be determined accu- rately and precisely for thermally driven cantilevers, in par- ticular when using higher flexural modes, since they show a highersensitivity toward an accreted mass than the first flexural mode. The simultaneous measurement of (ω n 2 ) /ω 2 n
Indeed, the IO-return relation is significantly positive and economically substantial even after adjusting for plausible levels of transaction costs (see Table IA.III in the Internet Appendix). Since all portfolios are formed at the end of June and rebalanced at the end of next June, we adjust for transaction costs as in Chan and Lakonishok (1997), Stoll (2000), and Mitchell and Pulvino (2001) by first subtracting the one-way transaction cost ratio (estimated transaction costs per share for each trade divided by the stock price) from individual stocks’ monthly returns in June and July. The portfolios’ transaction-cost adjusted returns are then computed as the value-weighted average of these individual stocks’ adjusted returns. We find that the hedge portfolio still has significantly positive returns and alphas. For example, following Stoll (2000), the transaction-cost adjusted alpha (from the four-factor model) of the hedge portfolio is 0.32% per month, which is highly significant. Moreover, using the approach of Hirshleifer and Shumway (2003), we find that the monthly alphas of the hedge portfolio are statistically significant unless the one-way transaction cost is 45 basis points or higher.
Climate change is driven by an increase in greenhouse gases which leads to higher incoming long-wave radiation, resulting in warmer surface and air temperatures. This, added to a lower diurnal amplitude of surface temperature, will af- fect both the VPD and the gradients between the surface and the atmosphere. Although rainfall and actual evaporation will experience changes as well, they are only expected to affect ET P in an indirect way.
both on the outer layer and the number of bilayers. A heat treatment process was applied to the sensor to reduce the effect on the deposited layers during the testing of the probe. As a result of these series of experiments, it could be concluded that the probe design on which were deposited structured layers comprising six double layers of (PAH/BY) showed the best sensitivity for a pH range from 6.80 to 9.00 (with an accuracy of ±0.20) and showing an average wavelength shift of 4.65 nm per 0.2 pH units, while the concentration of the BY and the PAH solutions was maintained as 0.25mM and 2.5mM respectively.
The main moments of interest are discussed in Panel D of Table 2. First, the model continues to generate a large increase in the CV of house prices for a given increase in the CV of wages. The increase is 60 points compared to 51 points in the benchmark. Second, it generates a larger increase in house prices: 19% increase compared to 11% in the benchmark. Third, the sensitivity coefficient increases strongly from 0.81 in 1975 to 11.95 in 2007. Fourth, and most significantly, this calibration generates population dynamics close to those observed in the data. The fraction of people working and living in the top-20% regions in terms of wage is 64.88% in the initial steady state and rises to 74.77% after 32 periods. This is close to the 73.09% in the 2007 data. This calibration avoids the steep drop in Q5 in the first period of the transition, which we noted for the benchmark model. Instead, the 1976 value for Q5 in the model is 64.62%, close to the initial steady state value. The population then gradually relocates towards the newly productive regions. In the final steady state, Q5 reaches a value of 80.37%, similar to the benchmark model. The key difference with the benchmark model, therefore, is the transition path of Q5. Because it avoids the initial drop in population, this model generates a higher increase in population-weighted house prices and a higher population-weighted sensitivity of prices to wages. By the same token, this version of our model matches the rank correlation of wages between adjacent years. It is 99.55% on average in the model and 99.22% on average in the data. Finally, the model generates an R 2
Many of the predictors identified in our analysis have previously been associated with LTFU. We found that a lower level of education and being a housewife or unemployed predicted LTFU. Higher education, which may influence employment status, has been shown to improve cART adherence, as well as retention in care (Ayuo et al., 2013; Bardeguez et al., 2008; Panditrao et al., 2011). We also found that fewer ANC visits and shorter duration of cART during pregnancy predicted LTFU, which aligns with previous findings that late presentation to ANC is associated with postpartum LTFU (Panditrao et al., 2011). We were unable to assess whether initiating treatment with a CD4 count >350 cells/uL predicted LTFU, because of existent thresholds for CD4 eligibility during the study period. However, as Option B+ is scaled up, the need for CD4 count monitoring may become obsolete, since women will initiate treatment regardless of CD4 count. In our analysis, WHO stage 1 or 2 was associated with LTFU, suggesting that women who are otherwise asymptomatic and healthy (ie. CD4 >350 cells/uL) may be at an increased risk of LTFU (Clouse et al., 2013; Tenthani et al., 2014). As seen in other studies (Boyles et al., 2011), enrollment in pre-ART care prior to pregnancy strongly predicted LTFU; however very few women met this definition.
The performance of the PLD sensor layers has been evalu- ated in test gas measurements. The three high-priority VOCs, benzene, formaldehyde and naphthalene, have been applied in concentrations below, at and above the respective guide- line values, and ethanol has been added as an interferent gas in much higher concentrations in order to simulate typical IAQ applications with background gases from, e.g., clean- ing agents or alcoholic beverages. The sensors were oper- ated in dynamic operation using temperature cycled opera- tion (TCO), which is a well-known method for increasing
Platinum and palladium indium oxide were investigated for the detection of oxygen in a humid environment. The sensors materials were deposited onto alumina substrates via screen printing. Results showed our sensors exhibited good sensitivity toward oxygen, following traditional power law over 0–20% concentration range. In comparison with Pd-In 2 O 3 , Pt-In 2 O 3 showed a much higher
One-dimensional (1D) nanomaterials are attractive build- ing blocks for future high-performance nanoscale devices and sensors [1-3]. With their unique structural charac- teristics and versatile physical properties, semiconductor nanowires and nanoribbons have been applied to photo- detectors , nanolasers , surface-enhanced Raman scattering (SERS) , solar cells , sensors, and so on [8,9]. It is well known that 1D nanomaterials possess high surface-to-volume ratio, which is crucial to show high sen- sitivity . Therefore, special attention has been focused on the application of 1D nanomaterials for detecting toxic, flammable, explosive gases and volatile organic compounds (VOCs). For instance, ZnO-CdS coaxial nanocables have shown to enhance sensitivity toward NH 3 . In 2 O 3 -ZnO
the number of oxygen vacancies is expected to increase in lower annealing temperature under certain oxygen flows and annealing time (confirmed by the results of XRD pattern and Raman spectra above), higher concen- tration of the oxygen vacancies will give higher probabil- ity of the adsorption of oxygen molecules onto the surface of SnO x films, leading to the fast decreasing of the photocurrent. Second, the increase in the oxygen vacancies is expected to decrease the bending of the semiconductor near the surface . Electrons and holes recombine more easily with less bended band, inducing a shorter carrier lifetime. So the photocurrent decay after switching off UV is faster for the sample at lower annealing temperature.
Infertility is a relatively common disorder around the world with much higher prevalence rates in regions such as Middle East (1). Although the incidence rate of infertility remains constant in the past decades (2), there is significant improvement in the management strategies via assistive reproductive technology (ART). Such growing utility of these techniques will also lead to an increased rate of complications which need a more restrictive approach to prevent them effectively. The most common complication of ART is ovarian hyper- stimulation syndrome (OHSS) with reported incidence rate of 3-8% for in vitro fertilization (IVF) (3, 4). OHSS presented with sign and symptoms of ovarian enlargement and excess fluid in the third spaces of body due to increased vascular permeability (4). Since the management of this syndrome is almost supportive and no definite treatment for handling of underlying pathophysiologic process is not available, preventive strategies and consequently recognition of risk factors and prediction of this syndrome play an important role in the management and work up of patients who will be undergo ART (3, 4). Although various parameters such as age, serum estradiol and follicle stimulating hormone (FSH) level and antral follicle count (AFC) have been known as predictors of OHSS, however, none of these parameters can independently predict OHSS and attempts are still made to provide a more constructive approach for prediction and prevention of OHSS (4-6). Recently, serum anti-mullerian hormone (AMH) level has been recognized as a valuable marker for evaluation of ovarian follicular reserve before ART (7, 8). Since AMH is produced by granulosa cells of small antral follicles, lower serum AMH level is in favor of a weaker response to ovarian stimulation. Regarding this direct dose-dependent response, some investigators suggested that higher levels of basal serum AMH would also related to higher possibility of ovarian hyper-stimulation (9-11). This study was performed to evaluate the role of AMH alone and in combination with other known risk factors in the prediction of OHSS.
rate of 10.6%, and Zhang reported a rate of 12.03% [5, 6]. Although peripheral blood analysis can facilitate a diagno- sis of sepsis [7, 8], the sensitivity and specificity are low, thus increasing the difficulty associated with clinical diag- nosis and treatment; furthermore, NS is likely to be com- plicated by purulent meningitis, for which the prognosis was poor . All of the above-mentioned factors require clinicians to provide a correct diagnosis and treatment for affected children as soon as possible to avoid unnecessary disability and death, and therefore an understanding of the pathogens and antibiotic resistance associated with the cases of NS admitted at our hospital and in nearby re- gions would be necessary. This study selected clinical data from 96 NS newborns with positive blood culture results who were treated in our department from January 2010 to August 2014 for a retrospective analysis.
A thorough ear, nose, and throat examination was performed in the patients with tinnitus on admission to the otolaryngology clinic. An audiovestibular test battery, including complete audiology and vestibular examinations, was performed in each subject. The Anxiety Sensitivity Index (ASI)-3, State-Trait Anxiety Inventory-1 (STAI-state) and State-Trait Anxiety Inventory-2 (STAI-trait), and Symptom Check List-90-Revised (SCL-90-R) were administered to all patients and healthy volunteers. ASI-3, STAI-trait, and Global Symptom Index (GSI) scores with SCL-90-R soma- tization, depression, anxiety, and phobic anxiety subscale scores were used in this study.