Safe density ratio modeling

An important problem in logistic regression modeling is the existence of the maximum likelihood estimators. In particular, when the sample size is small, the maximum likelihood estimator of the regression parameters does not exist if the data are completely, or quasicompletely separated. Recognizing that this phenomenon has a serious impact on the fitting of the density ratio model–which is a semiparametric model whose profile empirical log-likelihood has the logistic form because of the equivalence between prospective and retrospective sampling–we suggest a linear programming methodology for examining whether the maximum likelihood estimators of the finite dimensional parameter vector of the model exist. It is shown that the methodology can be effectively utilized in the analysis of case–control gene expression data by identifying cases where the density ratio model cannot be applied. It is demonstrated that naive application of the density ratio model yields erroneous conclusions.     

Elimination of motion and pulsation artifacts using BLADE sequences in knee MR imaging

The purpose of this study is to evaluate the ability of proton density (PD)-BLADE sequences in reducing or even eliminating motion and pulsatile flow artifacts in knee magnetic resonance imaging examinations. Eighty consecutive patients, who had been routinely scanned for knee examination, participated in the study. The following pairs of sequences with and without BLADE were compared: (a) PD turbo spin echo (TSE) sagittal (SAG) fat saturation (FS) in 35 patients, (b) PD TSE coronal (COR) FS in 19 patients, (c) T2 TSE axial in 13 patients and (d) PD TSE SAG in 13 patients. Both qualitative and quantitative analyses were performed based on the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and relative contrast (ReCon) measures of normal anatomic structures. The qualitative analysis was performed by experienced radiologists. Also, the presence of image motion and pulsation artifacts was evaluated. Based on the results of the SNR, CRN and ReCon for the different sequences and anatomical structures, the BLADE sequences were significantly superior in 19 cases, whereas the corresponding conventional sequences were significantly superior in only 6 cases. BLADE sequences eliminated motion artifacts in all the cases. However, motion artifacts were shown in (a) six PD TSE SAG FS, (b) three PD TSE COR FS, (c) three PD TSE SAG and (d) two T2 TSE axial conventional sequences. In our results, it was found that, in PD FS sequences (sagittal and coronal), the differences between the BLADE and conventional sequences regarding the elimination of motion and pulsatile flow artifacts were statistically significant. In all the comparisons, the PD FS BLADE sequences (coronal and sagittal) were significantly superior to the corresponding conventional sequences regarding the classification of their image quality. In conclusion, this technique appears to be capable to potentially eliminate motion and pulsatile flow artifacts in MR images.     

A Bayesian Surprise Approach in Designing Cognitive Radar for Autonomous Driving

This article proposes the Bayesian surprise as the main methodology that drives the cognitive radar to estimate a target’s future state (i.e., velocity, distance) from noisy measurements and execute a decision to minimize the estimation error over time. The research aims to demonstrate whether the cognitive radar as an autonomous system can modify its internal model (i.e., waveform parameters) to gain consecutive informative measurements based on the Bayesian surprise. By assuming that the radar measurements are constructed from linear Gaussian state-space models, the paper applies Kalman filtering to perform state estimation for a simple vehicle-following scenario. According to the filter’s estimate, the sensor measures the contribution of prospective waveforms—which are available from the sensor profile library—to state estimation and selects the one that maximizes the expectation of Bayesian surprise. Numerous experiments examine the estimation performance of the proposed cognitive radar for single-target tracking in practical highway and urban driving environments. The robustness of the proposed method is compared to the state-of-the-art for various error measures. Results indicate that the Bayesian surprise outperforms its competitors with respect to the mean square relative error when one-step and multiple-step planning is considered.     

Layered Double Hydroxides as Rising-Star Adsorbents for Water Purification: A Brief Discussion

Within the frame of this article, briefly but comprehensively, we present the existing knowledge, perspectives, and challenges for the utilization of Layered Double Hydroxides (LDHs) as adsorbents against a plethora of pollutants in aquatic matrixes. The use of LDHs as adsorbents was established by considering their significant physicochemical features, including their textural, structural, morphological, and chemical composition, as well as their method of synthesis, followed by their advantages and disadvantages as remediation media. The utilization of LDHs towards the adsorptive removal of dyes, metals, oxyanions, and emerging pollutants is critically reviewed, while all the reported kinds of interactions that gather the removal are collectively presented. Finally, future perspectives on the topic are discussed. It is expected that this discussion will encourage researchers in the area to seek new ideas for the design, development, and applications of novel LDHs-based nanomaterials as selective adsorbents, and hence to further explore the potential of their utilization also for analytic approaches to detect and monitor various pollutants.     

Highly Efficient Production of Nanoporous Block Copolymers with Arbitrary Structural Characteristics for Advanced Membranes

The great significance of boosting the design of percolating nanopore structures in block copolymers (BCPs) for various cases has been widely demonstrated in the past several decades. However, it still remains challenging to prepare the desired porous structures in a rapid, facile, and universal manner. Here we have developed an unconventional and benchtop strategy to rapidly generate the nanoporous polystyrene-based BCPs with arbitrary structural characteristics regardless of the BCP bulk morphology. This universal pore-forming strategy enables the sustainable CO₂-based BCPs to form advanced membranes after 1 s soaking for efficiently rejecting 94.2 % brilliant blue R (826 g mol⁻¹). Meanwhile, the water permeance retains around 1020 L (m² h bar)⁻¹, which is 1–3 orders of magnitude higher than that of other membranes. This strategy may offer an excellent opportunity to introduce percolating pore structures in those newly developed BCPs with which the previously reported pore-forming methods may not deal.