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The combined results of the two assays (MBA and CS) increased stratification accuracy, while correlation between MBA and CS was not significant, suggesting that the two assays are detecting different CTC subsets. In conclusion, this study suggests that MBA allows detection of both EpCAM-negative and EpCAM-positive, viable and label-free CTCs, which provide clinical information apparently equivalent and complementary to CS. A further validation of proposed method and cut-offs is needed in a larger, separate study.Coagulation factor Xa and factor XIa are proven to be convenient and crucial protein targets for treatment for thrombotic disorders and thereby their inhibitors can serve as effective anticoagulant drugs. In the present work, we focused on the structure-activity relationships of derivatives of pyrrolo[3,2,1-ij]quinolin-2(1H)-one and an evaluation of their activity against factor Xa and factor XIa. For this, docking-guided synthesis of nine compounds based on pyrrolo[3,2,1-ij]quinolin-2(1H)-one was carried out. For the synthesis of new hybrid hydropyrrolo[3,2,1-ij]quinolin-2(1H)-one derivatives, we used convenient structural modification of both the tetrahydro- and dihydroquinoline moiety by varying the substituents at the C6,8,9 positions. In vitro testing revealed that four derivatives were able to inhibit both coagulation factors and three compounds were selective factor XIa inhibitors. An IC50 value of 3.68 μM for was found for the best factor Xa inhibitor and 2 μM for the best factor XIa inhibitor.This study aims to experimentally investigate the pool boiling heat transfer coefficient behavior using tungsten oxide-based deionized water nanofluids and comparing them to deionized water as conventional fluid. The influence of different dilute volumetric concentrations (0.005%-0.05% Vol.) and applied heat fluxes were examined to see the effect of these parameters on the pool boiling heat transfer performance using nanofluids from a typical horizontal heated copper tube at atmospheric pressure conditions. Results demonstrated that the pool boiling heat transfer coefficient (PBHTC) for both deionized water and nanofluids increased with increasing the applied heat flux. The higher PBHTC enhancement ratio was 6.7% for a volume concentration of 0.01% Vol. at a low heat flux compared to the deionized water case. see more Moreover, the PBHTC for nanofluids was degraded compared to the deionized water case, and the maximum reduction ratio was about 15% for a volume concentration of 0.05% Vol. relative to the baseline case. The reduction in PBHTC was attributed to the deposition of tungsten oxide nanoflakes on the heating surface during the boiling process, which led to a decrease in the density of the nucleation sites.Recent advances in sensor technologies and data acquisition systems opened up the era of big data in the field of structural health monitoring (SHM). Data-driven methods based on statistical pattern recognition provide outstanding opportunities to implement a long-term SHM strategy, by exploiting measured vibration data. However, their main limitation, due to big data or high-dimensional features, is linked to the complex and time-consuming procedures for feature extraction and/or statistical decision-making. To cope with this issue, in this article we propose a strategy based on autoregressive moving average (ARMA) modeling for feature extraction, and on an innovative hybrid divergence-based method for feature classification. Data relevant to a cable-stayed bridge are accounted for to assess the effectiveness and efficiency of the proposed method. The results show that the offered hybrid divergence-based method, in conjunction with ARMA modeling, succeeds in detecting damage in cases strongly characterized by big data.The growth of the number of pet products and the pet food industry is continuous. This is partially driven by palatability and perceptions of preference. A preference ranking procedure for dogs has been proposed in order to suggest a more efficient method to study the palatability of food products for dogs. This method was developed based on the assumption that (1) dogs would be more motivated to solve a puzzle for foods that they preferred and (2) the order in which the dogs obtained the treats from the puzzles would indicate the ranking of their preferences. This current study included a validation test that was conducted with 12 dogs to determine if the proposed method was reliable. The validation followed the same procedure as the preliminary test for most parts and dedicated a separate phase each for training, fats, proteins, starches, and complex diets. The results from phases 2 to 4 showed a similar pattern with the preliminary test Fish oil was preferred over lard, liver over beef, and corn over chickpea. The results from phase 5 showed that the ranking of the combination of the ingredients reflected the preference of the dogs for individual ingredients. As a result, this method was concluded to be reliable.To maximize the usage of limited transmission power and wireless spectrum, more communication satellites are adopting precise space-ground beam-forming, which poses a rigorous positioning and timing requirement of the satellite. To fulfill this requirement, a space-borne global navigation satellite system (GNSS) timing receiver with a disciplined high-performance clock is preferable. The space-borne GNSS timing receiver moves with the satellite, in contrast to its stationary counterpart on ground, making it tricky in its positioning algorithm design. Despite abundant existing positioning algorithms, there is a lack of dedicated work that systematically describes the delicate aspects of a space-borne GNSS timing receiver. Based on the experimental work of the LING QIAO (NORAD ID40136) communication satellite's GNSS receiver, we propose a fine-tuned positioning algorithm for space-borne GNSS timing receivers. Specifically, the proposed algorithm includes (1) a filtering architecture that separates the estimation of satellite position and velocity from other unknowns, which allows for a first estimation of satellite position and velocity incorporating any variation of orbit dynamics; (2) a two-threshold robust cubature Kalman filter to counteract the adverse influence of measurement outliers on positioning quality; (3) Reynolds averaging inspired clock and frequency error estimation. Hardware emulation test results show that the proposed algorithm has a performance with a 3D positioning RMS error of 1.2 m, 3D velocity RMS error of 0.02 m/s and a pulse per second (PPS) RMS error of 11.8ns. Simulations with MATLAB show that it can effectively detect and dispose outliers, and further on outperforms other algorithms in comparison.