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Titanium dioxide (TiO2) nanoparticles are efficient photocatalysis for treating organic pollutants in water. Immobilizing TiO2 nanoparticles not only enables the reuse of nanoparticles but also prevents the harmful impact of releasing nanoparticles into the aquatic environment. In this study, a porous composite microfiber membrane based on polyacrylonitrile (PAN) with TiO2 nanoparticles has been synthesized by electrospinning technique. The new membrane system has exhibited excellent adsorptive-photocatalytic property to degrade Methylene blue (MB). Using the nonlinear form of the pseudo-first-order, pseudo-second-order, Elovich, and Intra-particle diffusion models, the adsorption mechanism was analyzed. Coupling with adsorption and photocatalysis, the efficiency of this membrane system was illustrated via the multistage linear form of the pseudo-first-order kinetic; and the electrical energy per order (EEO) confirmed the lowest energy requirements to transfer selected pollutants. Combining the results of SEM, BET, FTIR, XRD and TGA, it revealed the relationship of microstructure, composition, and MB decomposition performance. The finding presents new knowledge for material design and evaluation of polymers/oxides membrane systems for remediating organic pollutants in water.

The complete mitochondrial genome (mtgenome) was determined from the emerged-pupa shell (Noninvasive sampling) of T. aureus wuyiensis Lee. It was 15,234 base pairs in length and contained 13 protein-coding genes (PCGs), 2 rRNA genes, 22 tRNA genes, and a control region. By taking Meandrusa sciron and Teinopalpus imperialis as outgroups, a maximum-likelihood phylogenetic tree was constructed among five geographical populations of Teinopalpus aureus based on 13 PCGs and two rRNA genes. Our results showed that the WYS, MHS and PS populations, locating at or closing to Wuyishan Mountain-range, were in one cluster; while the JLS (locating at Nanling Mountain-range) and DYS (locating at Dayaoshan Mountain closing to Nanling Mountain-range) populations belonged to another cluster. It supported well the subspecies of T. aureus wuyiensis, and suggested that the genetic relationship between T. a. guangxiensis and the nominal subspecies of T. a. aureus were closer enough to combine into one subspecies.

This brief presents a comprehensive analysis of the output-dependent modulation (ODM) in a current-steering digital-to-analog converter (CS-DAC) based on the differential-quad switching (DQS) structure. A mathematical model is proposed to accurately describe ODM, which is categorized into two types: output transition errors and boundary effect errors. A novel approach of adding isolation devices is introduced and reinterpreted to mitigate the effect of ODM. The simulation results indicate that the inclusion of isolation devices efficiently suppresses the odd harmonics at mid-to-high frequency by a value that is 13 dB lower than before. Experimental validation is conducted on a 16-bit 250 MS/s CS-DAC fabricated in a 180 nm process. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to exploit integrated PET/MRI to simultaneously evaluate the morphological, component, and metabolic features of advanced atherosclerotic plaques and explore their incremental value. Methods: In this observational prospective cohort study, patients with advanced plaque in the carotid artery underwent 18F-FDG PET/MRI. Plaque morphological features were measured, and plaque component features were determined via MRI according to AHA lesion-types. Maximum standardized uptake values (SUVmax) and tissue to background ratio (TBR) on PET were calculated. Area under the receiver-operating characteristic curve (AUC) and net reclassification improvement (NRI) were used to compare the incremental contribution of FDG uptake when added to AHA lesion-types for symptomatic plaque classification. Results: A total of 280 patients with advanced plaque in the carotid artery were recruited. A total of 402 plaques were confirmed, and 87 of 402 (21.6%) were symptomatic plaques. 18F-FDG PET/MRI was performed a mean of 38 days (range 1–90) after the symptom. Increased stenosis degree (61.5% vs. 50.0%, p < 0.001) and TBR (2.96 vs. 2.32, p < 0.001) were observed in symptomatic plaques compared with asymptomatic plaques. The performance of the combined model (AHA lesion type VI + stenosis degree + TBR) for predicting symptomatic plaques was the best among all models (AUC = 0.789). The improvement of the combined model (AHA lesion type VII + stenosis degree + TBR) over AHA lesion type VII model for predicting symptomatic plaques was the highest (AUC = 0.757/0.454, combined model/AHA lesion type VII model), and the NRI was 50.7%. Conclusions: Integrated PET/MRI could simultaneously evaluate the morphological component and inflammation features of advanced atherosclerotic plaques and provide supplementary optimization information over AHA lesion-types for identifying vulnerable plaques in atherosclerosis subjects to achieve further stratification of stroke risk. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD). Methods: A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F‐fluorodeoxyglucose (18F‐FDG) PET, 3D arterial spin labeling (ASL), and high‐resolution T1‐weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad‐Score) of logistic regression models were evaluated from 5‐fold cross‐validation. Results: The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single‐modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad‐Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests. Conclusion: Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications. [ABSTRACT FROM AUTHOR]

Generative adversarial network (GAN) has become a research hotspot in generation model, since it can generate realistic images. To cope with the problem that the GAN cannot effectively capture the dependency between local and global features of the image and the dependency between different classes, this paper proposes a new generation model, named twins attention mechanism based generative adversarial network (TAGAN). Driven by twins attention mechanism, the real natural image is modeled by simulating the dependencies between local and global features and the dependencies between categories to create realistic fake images. TAGAN has feature attention and channel attention. The feature attention learns the correlation between similar features by selectively aggregating features. The channel attention learns the internal dependencies of each channel by integrating the relevant features of each channel dimension. The experiments implemented on the MNIST, CIFAR10 and CelebA64 datasets demonstrate that the proposed model is effective.

We have developed a manufacturing-friendly spin-orbit torque magnetic random access memory (SOT-MRAM) technology in CMOS compatible 8-inch fab process. The proposed SOT-MRAM process technology resolves etching non-uniformity and reduction of high resistivity heavy-metal nanowire resistance issues. Besides, we present device size-dependent switching current threshold in the proposed SOT-MRAM cell structure. To realize the potential of our fabricated SOT-MRAM, wafer-level uniformity, cycling and temperature dependence SOT switching have been comprehensively investigated. Furthermore, the thermal stability factor ( ${\Delta }$ ) was calculated from temperature-dependence SOT switching to fulfill the thermal stability criteria, i.e., > 10 years of this emerging SOT-MRAM technology.