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Breast cancer treatment can be improved with biomarkers for early detection and individualized therapy. A set of 86 microRNAs (miRNAs) were identified to separate breast cancer tumors from normal breast tissues (n = 52) with an overall accuracy of 90.4%. Six miRNAs had concordant expression in both tumors and breast cancer patient blood samples compared with the normal control samples. Twelve miRNAs showed concordant expression in tumors vs. normal breast tissues and patient survival (n = 1093), with seven as potential tumor suppressors and five as potential oncomiRs. From experimentally validated target genes of these 86 miRNAs, pan-sensitive and pan-resistant genes with concordant mRNA and protein expression associated with in-vitro drug response to 19 NCCN-recommended breast cancer drugs were selected. Combined with in-vitro proliferation assays using CRISPR-Cas9/RNAi and patient survival analysis, MEK inhibitors PD19830 and BRD-K12244279, pilocarpine, and tremorine were discovered as potential new drug options for treating breast cancer. Multi-omics biomarkers of response to the discovered drugs were identified using human breast cancer cell lines. This study presented an artificial intelligence pipeline of miRNA-based discovery of biomarkers, therapeutic targets, and repositioning drugs that can be applied to many cancer types. [ABSTRACT FROM AUTHOR]

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer. [ABSTRACT FROM AUTHOR]

In this study, an intelligent vehicle (IV) path tracking control method based on curvature optimisation is proposed to reduce the comprehensive performance conflict of the system. This system conflict is caused by the mutual restriction between the path tracking accuracy and the body stability during the movement of the intelligent automobile. First, the working principle of the new IV path tracking control algorithm is briefly introduced. Then, a three-degrees-of-freedom vehicle dynamics model and a preview error model considering vehicle roll are established. In addition, a path tracking control method based on curvature optimisation is designed to solve the deterioration of vehicle stability even when the path tracking accuracy of the IV is improved. Finally, the effectiveness of the IV path tracking control system is validated through simulations and the Hardware in the Loop (HIL) test with various conditions forms. Results clearly show that the optimisation amplitude of the IV lateral deviation is up to 84.10%, and the stability is improved by approximately 2% under the vx = 10 m/s and ρ = 0.15 m−1 condition; the optimisation amplitude of the lateral deviation is up to 66.80%, and the stability is improved by approximately 4% under the vx = 10 m/s and ρ = 0.2 m−1 condition; the body stability is improved by 20–30% under the vx = 15 m/s and ρ = 0.15 m−1 condition, and the boundary conditions of body stability are triggered. The curvature optimisation controller can effectively improve the tracking accuracy of the fuzzy sliding mode controller. The body stability constraint can also ensure the smooth running of the vehicle in the optimisation process. [ABSTRACT FROM AUTHOR]

The extraction of titanium-bearing components in the form of CaTiO3 is an efficient utilization of blast furnace slag. The photocatalytic performance of this obtained CaTiO3 (MM-CaTiO3) as a catalyst for methylene blue (MB) degradation was evaluated in this study. The analyses indicated that the MM-CaTiO3 had a completed structure with a special length–diameter ratio. Furthermore, the oxygen vacancy was easier to generate on a MM-CaTiO3(110) plane during the photocatalytic process, contributing to improving photocatalytic activity. Compared with traditional catalysts, MM-CaTiO3 has a narrower optical band gap and visible-light responsive performance. The degradation experiments further confirmed that the photocatalytic degradation efficiency of pollutants by using MM-CaTiO3 was 3.2 times that of pristine CaTiO3 in optimized conditions. Combined with molecular simulation, the degradation mechanism clarified that acridine of MB molecular was stepwise destroyed by using MM-CaTiO3 in short times, which is different from demethylation and methylenedioxy ring degradation by using TiO2. This study provided a promising routine for using solid waste to obtain catalysts with excellent photocatalytic activity and was found to be in keeping with sustainable environmental development. [ABSTRACT FROM AUTHOR]

Simple Summary: This study identified a set of 73 microRNAs (miRNAs) that can accurately detect lung cancer tumors from normal lung tissues. Based on the consistent expression patterns associated with patient survival outcomes and in tumors vs. normal lung tissues, 10 miRNAs were considered to be putatively tumor suppressive and 4 miRNAs were deemed as oncogenic in lung cancer. From the list of genes that were targeted by the 73 diagnostic miRNAs, DGKE and WDR47 had significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated network, we discovered three drugs—BX-912, daunorubicin, and midostaurin—that can be repositioned to treat lung cancer, which was not known before. The majority of lung cancer patients are diagnosed with metastatic disease. This study identified a set of 73 microRNAs (miRNAs) that classified lung cancer tumors from normal lung tissues with an overall accuracy of 96.3% in the training patient cohort (n = 109) and 91.7% in unsupervised classification and 92.3% in supervised classification in the validation set (n = 375). Based on association with patient survival (n = 1016), 10 miRNAs were identified as potential tumor suppressors (hsa-miR-144, hsa-miR-195, hsa-miR-223, hsa-miR-30a, hsa-miR-30b, hsa-miR-30d, hsa-miR-335, hsa-miR-363, hsa-miR-451, and hsa-miR-99a), and 4 were identified as potential oncogenes (hsa-miR-21, hsa-miR-31, hsa-miR-411, and hsa-miR-494) in lung cancer. Experimentally confirmed target genes were identified for the 73 diagnostic miRNAs, from which proliferation genes were selected from CRISPR-Cas9/RNA interference (RNAi) screening assays. Pansensitive and panresistant genes to 21 NCCN-recommended drugs with concordant mRNA and protein expression were identified. DGKE and WDR47 were found with significant associations with responses to both systemic therapies and radiotherapy in lung cancer. Based on our identified miRNA-regulated molecular machinery, an inhibitor of PDK1/Akt BX-912, an anthracycline antibiotic daunorubicin, and a multi-targeted protein kinase inhibitor midostaurin were discovered as potential repositioning drugs for treating lung cancer. These findings have implications for improving lung cancer diagnosis, optimizing treatment selection, and discovering new drug options for better patient outcomes. [ABSTRACT FROM AUTHOR]

There are insufficient accurate biomarkers and effective therapeutic targets in current cancer treatment. Multi-omics regulatory networks in patient bulk tumors and single cells can shed light on molecular disease mechanisms. Integration of multi-omics data with large-scale patient electronic medical records (EMRs) can lead to the discovery of biomarkers and therapeutic targets. In this review, multi-omics data harmonization methods were introduced, and common approaches to molecular network inference were summarized. Our Prediction Logic Boolean Implication Networks (PLBINs) have advantages over other methods in constructing genome-scale multi-omics networks in bulk tumors and single cells in terms of computational efficiency, scalability, and accuracy. Based on the constructed multi-modal regulatory networks, graph theory network centrality metrics can be used in the prioritization of candidates for discovering biomarkers and therapeutic targets. Our approach to integrating multi-omics profiles in a patient cohort with large-scale patient EMRs such as the SEER-Medicare cancer registry combined with extensive external validation can identify potential biomarkers applicable in large patient populations. These methodologies form a conceptually innovative framework to analyze various available information from research laboratories and healthcare systems, accelerating the discovery of biomarkers and therapeutic targets to ultimately improve cancer patient survival outcomes. [ABSTRACT FROM AUTHOR]

The formation shear-wave (S-wave)'s velocity information around a borehole is of great importance in evaluating borehole stability, reflecting fluid invasion, and selecting perforation positions. Dipole acoustic logging is an effective method for determining a formation S-wave's velocity radial profile around the borehole. Currently, the formation S-wave's radial-profile inversion methods are mainly based on the impacts of radial velocity changes of formations outside the borehole on the dispersion characteristics of dipole waveforms, without considering the impacts of an acoustic tool on the dispersion curves in the inversion methods. Accordingly, the inversion accuracy is greatly impacted in practical data-processing applications. In this paper, a novel inversion algorithm, which introduces equivalent-tool theory into the shear-velocity radial profile constrained-inversion method, is proposed to obtain the S-wave's slowness radial profile. Based on the equivalent-tool theory, the acoustic tool can be modeled using two parameters, radius and elastic modulus. The tool's impact on the dipole waveform's dispersion is eliminated first by using the equivalent-tool theory. Then, the corrected dispersion curve is used to carry out the constrained inversion processing. The results of this processing on the simulation data and the real logging data show the validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Catalase (CAT) is an important antioxidant enzyme in plants that plays a key role in plant growth and stress responses. CAT is usually encoded by a small gene family that has been cloned and functionally studied in some species, such as Arabidopsis, wheat and cucumber, but its specific roles in rice are not clear at present. In this study, we identified three CAT family genes (OsCAT1, OsCAT2 and OsCAT3) in the rice genome and performed a systematic bioinformatics analysis. RT−PCR analysis revealed that OsCAT1–OsCAT3 was primarily expressed in vegetative tissues such as roots, stems and leaves. Since OsCAT3 showed the highest expression level among the three OsCAT genes, we then focused on its related functions. OsCAT3 prokaryotic expression protein has an obvious ability to remove H2O2. The OsCAT3crispr plant was short and had a low survival rate, the leaves were small with brown lesions, and the activities of the CAT, POD and SOD enzymes were significantly reduced. A microarray analysis showed that differentially expressed genes were primarily enriched in toxin metabolism and photosynthesis. This study laid a foundation for further understanding the function of the rice OsCAT gene. [ABSTRACT FROM AUTHOR]

There are currently no effective biomarkers for prognosis and optimal treatment selection to improve non-small cell lung cancer (NSCLC) survival outcomes. This study further validated a seven-gene panel for diagnosis and prognosis of NSCLC using RNA sequencing and proteomic profiles of patient tumors. Within the seven-gene panel, ZNF71 expression combined with dendritic cell activities defined NSCLC patient subgroups (n = 966) with distinct survival outcomes (p = 0.04, Kaplan–Meier analysis). ZNF71 expression was significantly associated with the activities of natural killer cells (p = 0.014) and natural killer T cells (p = 0.003) in NSCLC patient tumors (n = 1016) using Chi-squared tests. Overexpression of ZNF71 resulted in decreased expression of multiple components of the intracellular intrinsic and innate immune systems, including dsRNA and dsDNA sensors. Multi-omics networks of ZNF71 and the intracellular intrinsic and innate immune systems were computed as relevant to NSCLC tumorigenesis, proliferation, and survival using patient clinical information and in-vitro CRISPR-Cas9/RNAi screening data. From these networks, pan-sensitive and pan-resistant genes to 21 NCCN-recommended drugs for treating NSCLC were selected. Based on the gene associations with patient survival and in-vitro CRISPR-Cas9, RNAi, and drug screening data, MEK1/2 inhibitors PD-198306 and U-0126, VEGFR inhibitor ZM-306416, and IGF-1R inhibitor PQ-401 were discovered as potential targeted therapy that may also induce an immune response for treating NSCLC. [ABSTRACT FROM AUTHOR]

There are currently no accurate biomarkers for optimal treatment selection in early-stage non-small cell lung cancer (NSCLC). Novel therapeutic targets are needed to improve NSCLC survival outcomes. This study systematically evaluated the association between genome-scale regulatory network centralities and NSCLC tumorigenesis, proliferation, and survival in early-stage NSCLC patients. Boolean implication networks were used to construct multimodal networks using patient DNA copy number variation, mRNA, and protein expression profiles. T statistics of differential gene/protein expression in tumors versus non-cancerous adjacent tissues, dependency scores in in vitro CRISPR-Cas9/RNA interference (RNAi) screening of human NSCLC cell lines, and hazard ratios in univariate Cox modeling of the Cancer Genome Atlas (TCGA) NSCLC patients were correlated with graph theory centrality metrics. Hub genes in multi-omics networks involving gene/protein expression were associated with oncogenic, proliferative potentials and poor patient survival outcomes (p < 0.05, Pearson's correlation). Immunotherapy targets PD1, PDL1, CTLA4, and CD27 were ranked as top hub genes within the 10th percentile in most constructed multi-omics networks. BUB3, DNM1L, EIF2S1, KPNB1, NMT1, PGAM1, and STRAP were discovered as important hub genes in NSCLC proliferation with oncogenic potential. These results support the importance of hub genes in NSCLC tumorigenesis, proliferation, and prognosis, with implications in prioritizing therapeutic targets to improve patient survival outcomes. [ABSTRACT FROM AUTHOR]

The recycling and regeneration of Fe(III) is the key point for promoting the oxidation reaction of ore to produce acidic mine drainage (AMD). Hydroxyapatite (HAP) has excellent adsorption ability of Fe(III), which has good biocompatibility and is widely distributed in nature. In order to achieve the source treatment of AMD, the migration and transformation of Fe(III) in the presence of HAP were systematically investigated. In this study, the influence of HAP on the migration of Fe(III) was evaluated though the transformation capacity of Fe(III) by HAP. The adsorption transformation kinetic, equilibrium and thermodynamics of Fe(III) using HAP were also systematic investigated. The transformation efficiency of Fe(III) increased with the increasing initial pH value and reached 99.8% at a pH of 5 due to the hydrolysis reaction. The transformation efficiency was also up to 99% at an initial pH of 2 when the reaction temperature increased to 313 K. However, the transformation capability of Fe(III) decreases with reaction temperature. The kinetics of the adsorption of Fe(III) fitted the pseudo second order kinetic model. Experimental results were also analyzed by the Langmuir isotherm equations at room temperatures. RL separation factor for Langmuir isotherm showed that the migration of Fe(III) is successfully hindered by HAP. Various thermodynamic parameters such as enthalpy (ΔH), Gibbs free energy (ΔG) and entropy (ΔS) changes were computed, which showed that the transport lag of Fe(III) caused by HAP is spontaneous and endothermic. [ABSTRACT FROM AUTHOR]

Simple Summary: This study presents novel insights on dysregulated B cell proliferation networks in non-small cell lung cancer (NSCLC). Within this network, a nine-gene signature demonstrated prognostic and predictive indications in more than 1400 NSCLC patients using their gene and protein expression profiles in bulk tumors. Furthermore, novel therapeutic candidates are identified to improve NSCLC treatment outcomes. In NSCLC, there is a pressing need for immunotherapy predictive biomarkers. The processes underlying B-cell dysfunction, as well as their prognostic importance in NSCLC, are unknown. Tumor-specific B-cell gene co-expression networks were constructed by comparing the Boolean implication modeling of single-cell RNA sequencing of NSCLC tumor B cells and normal B cells. Proliferation genes were selected from the networks using in vitro CRISPR-Cas9/RNA interfering (RNAi) screening data in more than 92 human NSCLC epithelial cell lines. The prognostic and predictive evaluation was performed using public NSCLC transcriptome and proteome profiles. A B cell proliferation and prognostic gene co-expression network was present only in normal lung B cells and missing in NSCLC tumor B cells. A nine-gene signature was identified from this B cell network that provided accurate prognostic stratification using bulk NSCLC tumor transcriptome (n = 1313) and proteome profiles (n = 103). Multiple genes (HLA-DRA, HLA-DRB1, OAS1, and CD74) differentially expressed in NSCLC B cells, peripheral blood lymphocytes, and tumor T cells had concordant prognostic indications at the mRNA and protein expression levels. The selected genes were associated with drug sensitivity/resistance to 10 commonly used NSCLC therapeutic regimens. Lestaurtinib was discovered as a potential repositioning drug for treating NSCLC. [ABSTRACT FROM AUTHOR]

In the field of intelligent connected vehicles, the precise and real-time identification of speed bumps is critically important for the safety of autonomous driving. To address the issue that existing visual perception algorithms struggle to simultaneously maintain identification accuracy and real-time performance amidst image distortion and complex environmental conditions, this study proposes an enhanced lightweight neural network framework, YOLOv5-FPNet. This framework strengthens perception capabilities in two key phases: feature extraction and loss constraint. Firstly, FPNet, based on FasterNet and Dynamic Snake Convolution, is developed to adaptively extract structural features of distorted speed bumps with accuracy. Subsequently, the C3-SFC module is proposed to augment the adaptability of the neck and head components to distorted features. Furthermore, the SimAM attention mechanism is embedded within the backbone to enhance the ability of key feature extraction. Finally, an adaptive loss function, Inner–WiseIoU, based on a dynamic non-monotonic focusing mechanism, is designed to improve the generalization and fitting ability of bounding boxes. Experimental evaluations on a custom speed bumps dataset demonstrate the superior performance of FPNet, with significant improvements in key metrics such as the mAP, mAP50_95, and FPS by 38.76%, 143.15%, and 51.23%, respectively, compared to conventional lightweight neural networks. Ablation studies confirm the effectiveness of the proposed improvements. This research provides a fast and accurate speed bump detection solution for autonomous vehicles, offering theoretical insights for obstacle recognition in intelligent vehicle systems. [ABSTRACT FROM AUTHOR]

Gel foam extinguishing agent (gel foam) has promising applications in the prevention and management of mine coal spontaneous combustion. Based on the research on coal spontaneous combustion and prevention technology, this article discusses recent studies on using gel foam to extinguish coal mines. The structural properties and principles of gel foam are described briefly. The research developments of three significant varieties of gel foam are then presented in detail, including silicate gel foam, acrylamide copolymer gel foam, and natural polymer gel foam. Meanwhile, the research status of gel foam anti-fire technology's rheological properties, stability property, plugging property, and inhibitory properties are introduced. Furthermore, in conjunction with the research state, the prospects of the research direction of gel foam are proposed, which serve as a reference for future research on gel foam. [ABSTRACT FROM AUTHOR]

Bearings are widely used in various electrical and mechanical equipment. As their core components, failures often have serious consequences. At present, most parameter adjustment methods are still manual adjustments of parameters. This adjustment method is easily affected by prior knowledge, easily falls into the local optimal solution, cannot obtain the global optimal solution, and requires a lot of resources. Therefore, this paper proposes a new method for bearing fault diagnosis based on wavelet packet transform and convolutional neural network optimized by a simulated annealing algorithm. Firstly, the original bearing vibration signal is extracted by wavelet packet transform to obtain the spectrogram, and then the obtained spectrogram is sent to the convolutional neural network for parameter adjustment, and finally the simulated annealing algorithm is used to adjust the parameters. To verify the effectiveness of the method, the bearing database of Case Western Reserve University is used for testing, and the traditional intelligent bearing fault diagnosis methods are compared. The results show that the new method for bearing fault diagnosis proposed in this paper has a better and more reliable diagnosis effect than the existing machine learning and deep learning methods. [ABSTRACT FROM AUTHOR]

There is an unmet clinical need to identify patients with early-stage non-small cell lung cancer (NSCLC) who are likely to develop recurrence and to predict their therapeutic responses. Our previous study developed a qRT-PCR-based seven-gene microfluidic assay to predict the recurrence risk and the clinical benefits of chemotherapy. This study showed it was feasible to apply this seven-gene panel in RNA sequencing profiles of The Cancer Genome Atlas (TCGA) NSCLC patients (n = 923) in randomly partitioned feasibility-training and validation sets (p < 0.05, Kaplan–Meier analysis). Using Boolean implication networks, DNA copy number variation-mediated transcriptional regulatory network of the seven-gene signature was identified in multiple NSCLC cohorts (n = 371). The multi-omics network genes, including PD-L1, were significantly correlated with immune infiltration and drug response to 10 commonly used drugs for treating NSCLC. ZNF71 protein expression was positively correlated with epithelial markers and was negatively correlated with mesenchymal markers in NSCLC cell lines in Western blots. PI3K was identified as a relevant pathway of proliferation networks involving ZNF71 and its isoforms formulated with CRISPR-Cas9 and RNA interference (RNAi) profiles. Based on the gene expression of the multi-omics network, repositioning drugs were identified for NSCLC treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: There are currently no effective biomarkers to select chemotherapy, immunotherapy, and radiotherapy for treating lung cancer patients. This study identified genetic networks containing major immune-checkpoint inhibitors CD27, PD1, and PDL1, and their associated prognostic genes and proliferation genes in lung cancer tumors. A 5-gene prognostic model was developed and validated in extensive cohorts to select patients at a high risk for developing metastasis. CRISPR-Cas9 and RNA interference screening data were used in the selection of proliferation genes. These genes were associated with chemoresponse and radiotherapy response in lung cancer cell lines and patient tumors. This immune-omics network led to the discovery of repositioning drugs for improving lung cancer treatment. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. Major immune-checkpoint inhibitors (ICIs) have more DNA copy number variations (CNV) than mutations in The Cancer Genome Atlas (TCGA) NSCLC tumors. Nevertheless, CNV-mediated dysregulated gene expression in NSCLC is not well understood. Integrated CNV and transcriptional profiles in NSCLC tumors (n = 371) were analyzed using Boolean implication networks for the identification of a multi-omics CD27, PD1, and PDL1 network, containing novel prognostic genes and proliferation genes. A 5-gene (EIF2AK3, F2RL3, FOSL1, SLC25A26, and SPP1) prognostic model was developed and validated for patient stratification (p < 0.02, Kaplan–Meier analyses) in NSCLC tumors (n = 1163). A total of 13 genes (COPA, CSE1L, EIF2B3, LSM3, MCM5, PMPCB, POLR1B, POLR2F, PSMC3, PSMD11, RPL32, RPS18, and SNRPE) had a significant impact on proliferation in 100% of the NSCLC cell lines in both CRISPR-Cas9 (n = 78) and RNA interference (RNAi) assays (n = 92). Multiple identified genes were associated with chemoresponse and radiotherapy response in NSCLC cell lines (n = 117) and patient tumors (n = 966). Repurposing drugs were discovered based on this immune-omics network to improve NSCLC treatment. [ABSTRACT FROM AUTHOR]

This study developed a novel methodology to correlate genome-scale microRNA (miRNA) expression profiles in a lung squamous cell carcinoma (LUSC) cohort (n = 57) with Surveillance, Epidemiology, and End Results (SEER)-Medicare LUSC patients (n = 33,897) as a function of composite tumor progression indicators of T, N, and M cancer stage and tumor grade. The selected prognostic and chemopredictive miRNAs were extensively validated with miRNA expression profiles of non-small-cell lung cancer (NSCLC) patient samples collected from US hospitals (n = 156) and public consortia including NCI-60, The Cancer Genome Atlas (TCGA; n = 1016), and Cancer Cell Line Encyclopedia (CCLE; n = 117). Hsa-miR-142-3p was associated with good prognosis and chemosensitivity in all the studied datasets. Hsa-miRNA-142-3p target genes (NUP205, RAN, CSE1L, SNRPD1, RPS11, SF3B1, COPA, ARCN1, and SNRNP200) had a significant impact on proliferation in 100% of the tested NSCLC cell lines in CRISPR-Cas9 (n = 78) and RNA interference (RNAi) screening (n = 92). Hsa-miR-142-3p-mediated pathways and functional networks in NSCLC short-term survivors were elucidated. Overall, the approach integrating SEER-Medicare data with comprehensive external validation can identify miRNAs with consistent expression patterns in tumor progression, with potential implications for prognosis and prediction of chemoresponse in large NSCLC patient populations. [ABSTRACT FROM AUTHOR]

The development of high efficient stacks is critical for the wide spread application of proton exchange membrane fuel cells (PEMFCs) in transportation and stationary power plant. Currently, the favorable operation conditions of PEMFCs are with single cell voltage between 0.65 and 0.7 V, corresponding to energy efficiency lower than 57%. For the long term, PEMFCs need to be operated at higher voltage to increase the energy efficiency and thus promote the fuel economy for transportation and stationary applications. Herein, PEMFC single cell was investigated to demonstrate its capability to working with voltage and energy efficiency higher than 0.8 V and 65%, respectively. It was demonstrated that the PEMFC encountered a significant performance degradation after the 64 h operation. The cell voltage declined by more than 13% at the current density of 1000 mA cm−2, due to the electrode de-activation. The high operation potential of the cathode leads to the corrosion of carbon support and then causes the detachment of Pt nanoparticles, resulting in significant Pt agglomeration. The catalytic surface area of cathode Pt is thus reduced for oxygen reduction and the cell performance decreased. Therefore, electrochemically stable Pt catalyst is highly desirable for efficient PEMFCs operated under cell voltage higher than 0.8 V. [ABSTRACT FROM AUTHOR]

Our previous study found that zinc finger protein 71 (ZNF71) mRNA expression was associated with chemosensitivity and its protein expression was prognostic of non-small-cell lung cancer (NSCLC). The Krüppel associated box (KRAB) transcriptional repression domain is commonly present in human zinc finger proteins, which are linked to imprinting, silencing of repetitive elements, proliferation, apoptosis, and cancer. This study revealed that ZNF71 KRAB had a significantly higher expression than the ZNF71 KRAB-less isoform in NSCLC tumors (n = 197) and cell lines (n = 117). Patients with higher ZNF71 KRAB expression had a significantly worse survival outcome than patients with lower ZNF71 KRAB expression (log-rank p = 0.04; hazard ratio (HR): 1.686 [1.026, 2.771]), whereas ZNF71 overall and KRAB-less expression levels were not prognostic in the same patient cohort. ZNF71 KRAB expression was associated with epithelial-to-mesenchymal transition (EMT) in both patient tumors and cell lines. ZNF71 KRAB was overexpressed in NSCLC cell lines resistant to docetaxel and paclitaxel treatment compared to chemo-sensitive cell lines, consistent with its association with poor prognosis in patients. Therefore, ZNF71 KRAB isoform is a more effective prognostic factor than ZNF71 overall and KRAB-less expression for NSCLC. Functional analysis using CRISPR-Cas9 and RNA interference (RNAi) screening data indicated that a knockdown/knockout of ZNF71 did not significantly affect NSCLC cell proliferation in vitro. [ABSTRACT FROM AUTHOR]

Global warming might expand crop growth areas for the prevailing single and double rice cropping systems in Southern China. Based on historical weather and crop data from 1981 to 2015, we evaluated the economic benefit and environmental cost for single and double rice cropping systems (SRCS and DRCS) in areas that are sensitive to climate variability in the middle and lower reaches of the Yangtze River. The five chosen indices were: net profit, agronomic nitrogen use efficiency (ANUE), water use efficiency (WUE), total amount, and global warming potential (GWP) of greenhouse gas (GHG). The goal of this study is to provide scientific evidence for local policymakers to use in selecting the most suitable rice cropping systems to maximize economic profits while adapting to climate change. The results showed that net profit was $171.4 per hectare higher for DRCS than for SRCS in the study region. In addition, output per unit nitrogen usage was $0.25 per kg N higher for DRCS than for SRCS. Net profit would increase if DRCS replaced SRCS, and the maximum amplitude of increase in net profit for this replacement occurred under the settings of 150 kg ha−1 nitrogen fertilizer level and continuous irrigation when the paddy water layer started to fade. On the other hand, annual variation in net profit for SRCS was consistently smaller than DRCS, regardless of changes in nitrogen fertilizer level and irrigation regime settings. SRCS showed better WUE than DRCS in both rainfed and irrigated situations, as well as lower seasonal CH4 and N2O emissions during the study period. Therefore, we conclude that SRCS is superior to DRCS for the sake of maximizing economic profit while maintaining sustainable agriculture in areas that are sensitive to climate variability in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Collecting multi-channel sensory signals is a feasible way to enhance performance in the diagnosis of mechanical equipment. In this article, a deep learning method combined with feature fusion on multi-channel sensory signals is proposed. First, a deep neural network (DNN) made up of auto-encoders is adopted to adaptively learn representative features from sensory signal and approximate non-linear relation between symptoms and fault modes. Then, Locality Preserving Projection (LPP) is utilized in the fusion of features extracted from multi-channel sensory signals. Finally, a novel diagnostic model based on multiple DNNs (MDNNs) and softmax is constructed with the input of fused deep features. The proposed method is verified in intelligent failure recognition for automobile final drive to evaluate its performance. A set of contrastive analyses of several intelligent models based on the Back-Propagation Neural Network (BPNN), Support Vector Machine (SVM) and the proposed deep architecture with single sensory signal and multi-channel sensory signals is implemented. The proposed deep architecture of feature extraction and feature fusion on multi-channel sensory signals can effectively recognize the fault patterns of final drive with the best diagnostic accuracy of 95.84%. The results confirm that the proposed method is more robust and effective than other comparative methods in the contrastive experiments. [ABSTRACT FROM AUTHOR]

The Ce-Cu-SAPO-18 catalysts were prepared using the ion exchange method. The impact of sulfur dioxide on catalytic performance of Ce-Cu-SAPO-18 for the selective catalytic reduction (SCR) of NO with NH3 was examined. Detailed characterization of the fresh and sulfur-poisoning Cu-SAPO-18 and Ce-Cu-SAPO-18 samples was conducted. XRD and BET results show that SO2 treatment of the Ce-doped Cu-SAPO-18 (Ce-Cu-SAPO-18-S) sample did not induce a remarkable change in structure, as compared with that of the fresh counterpart. According to in situ DRIFT, H2-TPR, SEM, and EDS results, it is found that the sulfation species attached preferentially to the cerium species, rather than the isolated Cu2+ species. In particular, the TG/DSC results confirm that the sulfate species on the Ce-Cu-SAPO-18-S sample was easier to decompose than that on the Cu-SAPO-18-S sample. The catalytic active sites of Ce-Cu-SAPO-18 were less influenced after SO2 treatment, as demonstrated by the TPR and XPS results. All of the above results show that the Ce-Cu-SAPO-18 sample exhibited better sulfur-resistant performance than the Cu-SAPO-18 sample. [ABSTRACT FROM AUTHOR]

Human interaction recognition technology is a hot topic in the field of computer vision, and its application prospects are very extensive. At present, there are many difficulties in human interaction recognition such as the spatial complexity of human interaction, the differences in action characteristics at different time periods, and the complexity of interactive action features. The existence of these problems restricts the improvement of recognition accuracy. To investigate the differences in the action characteristics at different time periods, we propose an improved fusion time-phase feature of the Gaussian model to obtain video keyframes and remove the influence of a large amount of redundant information. Regarding the complexity of interactive action features, we propose a multi-feature fusion network algorithm based on parallel Inception and ResNet. This multi-feature fusion network not only reduces the network parameter quantity, but also improves the network performance; it alleviates the network degradation caused by the increase in network depth and obtains higher classification accuracy. For the spatial complexity of human interaction, we combined the whole video features with the individual video features, making full use of the feature information of the interactive video. A human interaction recognition algorithm based on whole–individual detection is proposed, where the whole video contains the global features of both sides of action, and the individual video contains the individual detail features of a single person. Making full use of the feature information of the whole video and individual videos is the main contribution of this paper to the field of human interaction recognition and the experimental results in the UT dataset (UT–interaction dataset) showed that the accuracy of this method was 91.7%. [ABSTRACT FROM AUTHOR]

The sodium-treated sepiolite (NaSep)-supported rare earth oxide (RE/NaSep; RE = La, Eu, Dy, and Tm) samples were prepared using the rotary evaporation method. Physicochemical properties of these materials were characterized by XRD, SEM, BET, FTIR, XPS, H2–TPR, NH3–TPD, and in situ DRIFTS, and their catalytic activities for formaldehyde (HCHO) (2000 ppm) oxidation were evaluated. The results show that loading of the rare earth oxide on NaSep improved its catalytic performance. Among all the samples, Eu/NaSep performed the best, and complete HCHO conversion was achieved at a temperature of 150 °C and a gas hourly space velocity of 240,000 mL/(g h); a good catalytic activity was still maintained after 45 h of stability test. The catalytic oxidation mechanism of HCHO was studied using the in situ DRIFTS technique. As a result, the effective and stable catalytic performance of the Eu/NaSep sample was mainly due to the presence of hydroxyl groups on the sepiolite surface and the doped rare earth oxides, which contributed to its high performance. HCHO oxidation underwent via the steps of HCHO + O2 → HCOO− + OH− → H2O + CO2. It is concluded that the optimal catalytic activity of Eu/NaSep was associated with the highest Oads/Olatt atomic ratio, the largest amount of hydroxyl groups, the highest acidity, and the best reducibility. The present work may provide new insights into the application in the removal of high-concentration HCHO over the rare earth oxides supported on natural low-cost clays. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor efficiency of the intelligent fault diagnosis method of the main reducer and the poor effectiveness of multichannel data fusion, this paper proposes a multichannel data fusion method based on deep belief networks and random forest fusion for fault diagnosis. Multiple deep belief networks (MDBNs) are constructed to obtain deep representative features from multiple modalities of multichannel data. Random forest can fuse deep representative features achieved from MDBNs to construct the model of multiple deep belief networks fusion (MDBNF). The proposed method is applied to fault diagnosis of the main reducer and evaluation of the performance. Multiple deep belief network model fusions (MD BN F) are constructed to improve the multichannel data fusion effect. Single sensory data, multichannel data, and two intelligent models based on support vector machine and deep belief networks are used as comparison in the experiments. The results indicate that the classification accuracy of the test set collected by sensor 1 and sensor 2 is 88.35% and 88.73%, respectively. The comparison results show that the method has good convergence. The data fusion of the proposed diagnostic model can effectively improve the correlation between the collected vibration signals and the failure mode, thereby improving the diagnostic performance by nearly 8%, representing improved diagnostic accuracy. [ABSTRACT FROM AUTHOR]

Since E. coli is the most prevalent sepsis bacterium, studying its pathogenic molecular pathways may help with its early diagnosis and individualized treatment. However, few studies have investigated the molecular characterization of E. coli infection only. We extracted E. coli infection-specific genes and indicators from published data and clinical laboratory results in this study. GSE65088 showed 277, 377, and 408 DEGs for E. coli and other bacteria, E. coli and healthy groups, and other bacteria and healthy groups, respectively. DEGs, the MEgreen module with the highest relevance in WGCNA, and the first three MCODE subnetworks were used to find E. coli infection-specific hub genes. HSPA1B and TNF were verified in GSE6269 with ROC-AUCs of 0.7038 and 0.7116, respectively. CIBERSORT showed increased B-cell naive and T-cell CD4 naive infiltration in E. coli infectious sepsis. Patients infected with E. coli were younger than those infected with other pathogens. Compared to the other bacterially infectious sepsis patients, the E. coli patients had low globulin, prealbumin, creatine kinase, and high bilirubin levels. The clinically significant difference indicator IL-2, in combination with hub genes, better differentiated the healthy and E. coli groups, with an ROC-AUC of 0.8793. The study suggested that HSPA1B and TNF may be E.-coli-infection-specific genes, which may help explain the molecular mechanism of infectious sepsis. [ABSTRACT FROM AUTHOR]

Punding is a rare condition triggered by dopaminergic therapy in Parkinson's disease (PD), characterized by a complex, excessive, repetitive, and purposeless abnormal movement, and its pathogenesis remains unclear. We aimed to assess the brain structure alterations related to punding by using multipametric magnetic resonance imaging (MRI). Thirty-eight PD patients (19 with punding and 19 without punding) from the Parkinson's Progression Marker Initiative (PPMI) were included in this study. Cortical thickness was assessed with FreeSurfer, and the integrity of white matter fiber tracts and network topologies were analyzed by using FMRIB Software Library (FSL) and Pipeline for Analyzing braiN Diffusion imAges (PANDA). PD patients with punding showed a higher apathy score and more severe cortical atrophy in the left superior parietal, right inferior parietal, and right superior frontal gyrus, and worse integrity of the right cingulum cingulate tract compared to those without punding. On the other hand, no significant difference in structural network topologies was detected between the two groups. These data suggest that the specific area of destruction may be an MRI biomarker of punding risk, and these findings may have important implications for understanding the neural mechanisms of punding in PD. [ABSTRACT FROM AUTHOR]

Low temperatures restrict the growth of the grapevine industry. The DREB transcription factors are involved in the abiotic stress response. Here, we isolated the VvDREB2A gene from Vitis vinifera cultivar 'Zuoyouhong' tissue culture seedlings. The full-length VvDREB2A cDNA was 1068 bp, encoding 355 amino acids, which contained an AP2 conserved domain belonging to the AP2 family. Using transient expression in leaves of tobacco, VvDREB2A was localized to the nucleus, and it potentiated transcriptional activity in yeasts. Expression analysis revealed that VvDREB2A was expressed in various grapevine tissues, with the highest expression in leaves. VvDREB2A was induced by cold and the stress-signaling molecules H2S, nitric oxide, and abscisic acid. Furthermore, VvDREB2A-overexpressing Arabidopsis was generated to analyze its function. Under cold stress, the Arabidopsis overexpressing lines exhibited better growth and higher survival rates than the wild type. The content of oxygen free radicals, hydrogen peroxide, and malondialdehyde decreased, and antioxidant enzyme activities were enhanced. The content of raffinose family oligosaccharides (RFO) also increased in the VvDREB2A-overexpressing lines. Moreover, the expression of cold stress-related genes (COR15A, COR27, COR6.6, and RD29A) was also enhanced. Taken together, as a transcription factor, VvDREB2A improves plants resistance to cold stress by scavenging reactive oxygen species, increasing the RFO amount, and inducing cold stress-related gene expression levels. [ABSTRACT FROM AUTHOR]

Strontium marking technology is commonly used for extensive marking in stock enhancement and releasing activities. In order to explore the feasibility of this technology for juvenile Takifugu obscurus, five different concentrations of strontium (0, 12, 18, 36, and 72 mg/L) were set up by strontium chloride hexahydrate (SrCl2·6H2O) and T. obscurus were immersed for 7 days. Then, T. obscurus were reared in non-additive water for 25 days. The results showed that the survival rate of all groups was 100%, except the 72 mg/L group, after 7 days of immersion. Moreover, the growths of all the marked groups were better than that of the control group. There was no significant difference between the control and marked groups, except for the 18 mg/L group, indicating that the appropriate concentration of strontium might have positive effect for T. obscurus. The strontium to calcium (Sr/Ca) ratios of otoliths in the marked groups increased with increasing concentration and time, which were higher than the baseline, respectively. Then, the Sr/Ca ratios returned to the original level, but the peak value was still retained, suggesting that the success rate of the strontium marking reached 100%. Notably, the residual strontium content of 18 mg/L group was insufficient for causing negative effects for T. obscurus after 25 days. Therefore, in consideration of the growth, survival, and effect of strontium marking on otolith, 18 mg/L is an appropriate concentration for strontium marking of juvenile T. obscurus. This study confirmed the feasibility of strontium marking for T. obscurus and provided a new approach to rationally and scientifically evaluate the stock enhancement and releasing efficiency of T. obscurus. [ABSTRACT FROM AUTHOR]

CRISPR-Cas systems empower prokaryotes with adaptive immunity against invasive mobile genetic elements. At the first step of CRISPR immunity adaptation, short DNA fragments from the invaders are integrated into CRISPR arrays at the leader-proximal end. To date, the mechanism of recognition of the leader-proximal end remains largely unknown. Here, in the Sulfolobus islandicus subtype I-A system, we show that mutations destroying the proximal region reduce CRISPR adaptation in vivo. We identify that a stem-loop structure is present on the leader-proximal end, and we demonstrate that Cas1 preferentially binds the stem-loop structure in vitro. Moreover, we demonstrate that the integrase activity of Cas1 is modulated by interacting with a CRISPR-associated factor Csa3a. When translocated to the CRISPR array, the Csa3a-Cas1 complex is separated by Csa3a binding to the leader-distal motif and Cas1 binding to the leader-proximal end. Mutation at the leader-distal motif reduces CRISPR adaptation efficiency, further confirming the in vivo function of leader-distal motif. Together, our results suggest a general model for binding of Cas1 protein to a leader motif and modulation of integrase activity by an accessory factor. [ABSTRACT FROM AUTHOR]

Simple Summary: Immunity combined with ferroptosis is being considered as a new tumor treatment modality, and its regulation in head and neck squamous cell carcinoma is still unknown. The purpose of this study was to look into the potential molecular biological roles of immune ferroptosis genes in head and neck squamous cell carcinoma. The 12-IFRM signatures were successfully constructed and classified into high- and low-risk groups using the TCGA database and related data resources. In patients with head and neck squamous cell carcinoma, feature-based risk scores were more predictive of survival than traditional clinicopathological features. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. The expression of TNFSF9 and CD44 in the high-risk groups was significantly increased compared with the low-risk groups. Next, we found a higher proportion of high-risk mutations than in the low-risk group. In addition, the high-risk group was more sensitive to some chemotherapy drugs. Finally, we performed correlation analysis on the model genes. In this paper, the 12-IFRM signatures was developed with promising application prospects for predicting the clinical outcomes and treatment outcomes in head and neck squamous cell carcinoma. Ferroptosis is a new type of programmed cell death that plays a pivotal role in a variety of tumors. Moreover, immunity is closely related to ferroptosis. However, immune-ferroptosis-related mRNAs (IFRMs) are still not fully understood in the regulation of head and neck squamous cell carcinoma (HNSC). The purpose of this paper was to investigate the IFRMs prediction of HNSC and its possible molecular biological role. RNA-Seq and related clinical data were mined from the TCGA database, ImmPort database, GeneCards database, FerrDb database, and previous data. In R software, the "DESeq2" package was used to analyze the differential expression of IFRMs. We used univariate Cox analysis to judge the prognosis of the IFRMs. Using the least absolute shrinkage and selection operator (LASSO) and Cox regression, a prediction model for 12 IFRMs was established. In this study, the Kaplan–Meier survival curve and receiver operating characteristic (ROC) curve analysis were used to evaluate the prediction results. Moreover, factors such as immune landscape, somatic mutations, and drug susceptibility are also discussed. We successfully constructed the signature of 12-IFRMs. The two risk groups were classified according to the risk score obtained by this signature. Compared with conventional clinicopathological features, the characteristic-based risk score was more predictive of survival in patients with HNSC. Furthermore, the expression of CD8+T cells and macrophage M0 differed significantly between the two groups. Moreover, the expression of TNFSF9 and CD44 in high-risk groups was significantly increased compared with the low-risk groups. Then, we found a higher proportion of high-risk mutations than in the low-risk group. Next, the high-risk group was more sensitive to chemotherapy drugs such as bosutinib, docetaxel, erlotinib, gefitinib, imatinib, lapatinib, and sorafenib. Finally, an in-depth analysis of the association and potential value of the 12 genes was performed. In summary, the 12-IFRM signatures established in this paper had good application prospects and could be effectively used to predict the clinical outcome and treatment response of head and neck squamous cell carcinoma. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H2S) has been shown to participate in various stress responses in plants, including drought, salinity, extreme temperatures, osmotic stress, and heavy metal stress. Manganese (Mn), as a necessary nutrient for plant growth, plays an important role in photosynthesis, growth, development, and enzymatic activation of plants. However, excessive Mn2+ in the soil can critically affect plant growth, particularly in acidic soil. In this study, the model plant Arabidopsis thaliana was used to explore the mechanism of H2S participation and alleviation of Mn stress. First, using wild-type Arabidopsis with excessive Mn2+ treatment, the following factors were increased: H2S content, the main H2S synthetase L-cysteine desulfhydrase enzyme (AtLCD) activity, and the expression level of the AtLCD gene. Further, using the wild-type, AtLCD deletion mutant (lcd) and overexpression lines (OE5 and OE32) as materials, the phenotype of Arabidopsis seedlings was observed by exogenous application of hydrogen sulfide donor sodium hydrosulfide (NaHS) and scavenger hypotaurine (HT) under excessive Mn2+ treatment. The results showed that NaHS can significantly alleviate the stress caused by Mn2+, whereas HT aggravates this stress. The lcd mutant is more sensitive to Mn stress than the wild type, and the overexpression lines are more resistant. Moreover, the mechanism of H2S alleviating Mn stress was determined. The Mn2+ content and the expression of the Mn transporter gene in the mutant were significantly higher than those of the wild-type and overexpression lines. The accumulation of reactive oxygen species was significantly reduced in NaHS-treated Arabidopsis seedlings and AtLCD overexpression lines, and the activities of various antioxidant enzymes (SOD, POD, CAT, APX) also significantly increased. In summary, H2S is involved in the response of Arabidopsis to Mn stress and may alleviate the inhibition of Mn stress on Arabidopsis seedling growth by reducing Mn2+ content, reducing reactive oxygen species content, and enhancing antioxidant enzyme activity. This study provides an important basis for further study of plant resistance to heavy metal stress. [ABSTRACT FROM AUTHOR]

As a heavy metal, Pb is one component in coal-fired flue gas and is widely considered to have a strong negative effect on catalyst activity in the selective catalytic reduction of NOx by NH3 (NH3-SCR). In this paper, we investigated the deactivation mechanism of the Mo-Ce/Zr-PILC catalyst induced by Pb in detail. We found that NO conversion over the 3Mo4Ce/Zr-PILC catalyst decreased greatly after the addition of Pb. The more severe deactivation induced by Pb was attributed to low surface area, lower amounts of chemisorbed oxygen species and surface Ce3+, and lower redox ability and surface acidity (especially a low number of Brønsted acid sites). Furthermore, the addition of Pb inhibited the formation of highly active intermediate nitrate species generated on the surface of the catalyst, hence decreasing the NH3-SCR activity. [ABSTRACT FROM AUTHOR]

Different Cu contents (x wt%) were supported on the cryptomelane-type manganese oxide octahedral molecular sieve (OMS-2) (xCu/OMS-2; x = 1, 5, 15, and 20) via a pre-incorporation method. Physicochemical properties of the OMS-2 and xCu/OMS-2 samples were characterized by means of the XRD, FT-IR, SEM, TG/DTG, ICP-OES, XPS, O2-TPD, H2-TPR, and in situ DRIFTS techniques, and their catalytic activities were measured for the oxidation of CO, ethyl acetate, and toluene. The results show that the Cu species were homogeneously dispersed in the tunnel and framework structure of OMS-2. Among all of the samples, 15Cu/OMS-2 sample exhibited the best activities with the T50% of 65, 165, and 240 °C as well as the T90% of 85, 215, and 290 °C for CO, ethyl acetate and toluene oxidation, respectively, which was due to the existence of the Cu species and Mn3+/Mn4+ redox couples, rich oxygen vacancies, good oxygen mobility, low-temperature reducibility, and strong interaction between the Cu species and the OMS-2 support. The reaction mechanisms were also deduced by analyzing the in situ DRIFTS spectra of the 15Cu/OMS-2 sample. The excellent oxygen mobility associated with the electron transfer between Cu species and Mn3+/Mn4+ redox couples might be conducive to the continuous replenishment of active oxygen species and the constantly generated reactant intermediates, thereby increasing the reactant reaction rate. [ABSTRACT FROM AUTHOR]

The Ni-loaded cryptomelane-type manganese oxide octahedral molecular sieve (OMS-2) catalysts (xNi/OMS-2: x = 1, 3, 5, and 10 wt%) were prepared by a pre-incorporation method. Physicochemical properties of the as-synthesized materials were characterized by means of various techniques, and their catalytic activities for CO, ethyl acetate, and toluene oxidation were evaluated.The loading of Ni played an important role in improving physicochemical propertiesof OMS-2. Among all of the samples, 5Ni/OMS-2 exhibited the best catalytic activity, with the T90 being 155 °C for CO oxidation at a space velocity (SV) of 60,000 mL/(g·h), 225 °C for ethyl acetate oxidation at an SV of 240,000 mL/(g·h), and 300 °C for toluene oxidation at an SV of 240,000 mL/(g·h), which was due to its high Mn3+ content and Oads concentration, good low-temperature reducibility and lattice oxygen mobility, and strong interaction between the Ni species and the OMS-2 support. In addition, catalytic mechanisms of the oxidation of three pollutants over 5Ni/OMS-2 were also studied. The oxidation of CO, ethyl acetate, and toluene over the catalysts took place first via the activated adsorption, then intermediates formation, and finally complete conversion of the formed intermediates to CO2 and H2O. [ABSTRACT FROM AUTHOR]

The poisoning effects of alkali metals (K and Na) and alkaline earth metals (Ca and Mg) on catalytic performance of the 2Nb4Ce/Zr-PILC catalyst for the selective catalytic reduction of NOx with NH3 (NH3-SCR) were investigated, and physicochemical properties of the catalysts were characterized by means of the X-ray diffraction XRD (XRD), Brunner−Emmet−Teller (BET), hydrogen temperature-programmed reduction (H2-TPR), X-ray Photoelectron Spectroscopy (XPS), ammonia temperature-programmed desorption (NH3-TPD), and in situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTS) techniques. Doping of M (M = K, Na, Ca, and Mg) deactivated the 2Nb4Ce/Zr-PILC catalyst according to the sequence of 0.8 K > 0.8 Na > 0.8 Ca > 0.8 Mg (M/Ce molar ratio = 0.8). The characterization results showed that the decreases in redox ability, NH3 adsorption, Ce3+/Ce4+ atomic ratio, and amount of the chemisorbed oxygen (Oβ) were the important factors influencing catalytic activities of the alkali metal-and alkaline earth metal-doped samples. Consequently, compared with the Mg- and Ca-doped samples, doping of K caused the 2Nb4Ce/Zr-PILC sample to possess the lowest redox ability, NH3 adsorption, and amount of the Oβ species, which resulted in an obvious deactivation effect. [ABSTRACT FROM AUTHOR]

Distributed fiber acoustic sensing (DAS) technology can continuously spatially detect disturbances along the sensing fiber over long distance in real time. It has many unique advantages, including, large coverage, high time-and-space resolution, convenient implementation, strong environment adaptability, etc. Nowadays, DAS becomes a versatile technology in many fields, such as, intrusion detection, railway transportation, seismology, structure health monitoring, etc. In this paper, the sensing principle and some common performance indexes are introduced, and a brief overview of recent DAS researches in Shanghai Institute of Optics and Fine Mechanics (SIOM) is presented. Some representative research advances are explained, including, quantitative demodulation, interference fading suppression, frequency response boost, high spatial resolution, and distributed multi-dimension localization. The engineering applications of DAS, carried out by SIOM and other groups, are summarized and reviewed. Finally, possible future directions are discussed and concluded. It is believed that, DAS has great development potential and application prospect. [ABSTRACT FROM AUTHOR]

Lanthanide (La, Ce, Nd, Gd, Tb, Ho or Lu)-doped Cu-SAPO-18 samples were prepared using the ion-exchange method. Physicochemical properties of the samples were systematically characterized by a number of analytical techniques, and the effects of lanthanide doping on catalytic activity and hydrothermal stability of the Cu-SAPO-18 catalysts for the NH3-SCR reaction were examined. It is shown that the doping of lanthanide elements could affect the interaction between the active components (copper ions) and the AEI-structured SAPO-18 support. The inclusion of some lanthanides significantly slowed down hydrolysis of the catalyst during hydrothermal aging treatment process, leading to an enhanced catalytic activity at both low and high temperatures and hydrothermal stability. In particular, Ce doping promoted the Cu2+ ions to migrate to the energetically favorable sites for enhancement in catalytic activity, whereas the other lanthanide ions exerted little or an opposite effect on the migration of Cu2+ ions. Additionally, Ce doping could improve hydrothermal stability of the Cu-SAPO-18 catalyst by weakening hydrolysis of the catalyst during the hydrothermal aging treatment process. Ce doping increased the catalytic activity of Cu-SAPO-18 at low and high temperatures, which was attributed to modifications of the redox and/or isolated Cu2+ active centers. [ABSTRACT FROM AUTHOR]

It is a basic task in Brillouin distributed fiber sensors to extract the peak frequency of the scattering spectrum, since the peak frequency shift gives information on the fiber temperature and strain changes. Because of high-level noise, quadratic fitting is often used in the data processing. Formulas of the dependence of the minimum detectable Brillouin frequency shift (BFS) on the signal-to-noise ratio (SNR) and frequency step have been presented in publications, but in different expressions. A detailed deduction of new formulas of BFS variance and its average is given in this paper, showing especially their dependences on the data range used in fitting, including its length and its center respective to the real spectral peak. The theoretical analyses are experimentally verified. It is shown that the center of the data range has a direct impact on the accuracy of the extracted BFS. We propose and demonstrate an iterative fitting method to mitigate such effects and improve the accuracy of BFS measurement. The different expressions of BFS variances presented in previous papers are explained and discussed. [ABSTRACT FROM AUTHOR]

Phase-sensitive optical time domain reflectometer (Φ-OTDR) has attracted attention in scientific research and industry because of its distributed dynamic linear response to external disturbances. However, the signal-to-noise ratio (SNR) of Φ-OTDR is still a limited factor by the weak Rayleigh Backscattering coefficient. Here, the multi-transverse modes heterodyne matched-filtering technology is proposed to improve the system SNR. The capture efficiency and nonlinear threshold are increased with multiple transverse modes in few-mode fibers; the incident light energy is permitted to be enlarged by a wider probe pulse by using heterodyne matched-filtering without spatial resolution being deteriorated. As far as we know, this is the first time that both multi-transverse modes integration method and digital heterodyne matched filtering method have been used to improve the SNR of Φ-OTDR simultaneously. Experimental results show that the noise floor is reduced by 11.4 dB, while the target signal is kept. We believe that this proposed method will help DAS find important applications in marine acoustic detection and seismic detection. [ABSTRACT FROM AUTHOR]

The reactions of electron-rich organosilicon compounds 1,4-bis(trimethylsilyl)-1,4-diaza-2,5-cyclohexadiene (1), 2,3,5,6-tetramethyl-1,4-bis(trimethylsilyl)-1,4-diaza-2,5-cyclohexadiene (2), and 1,1′-bis(trimethylsilyl)-1,1′-dihydro-4,4′-bipyridine (12) with B-amino and B-aryl dihaloboranes afforded a series of novel B=N-bond-containing compounds 3–11 and 13. The B=N rotational barriers of 7 (>71.56 kJ/mol), 10 (58.79 kJ/mol), and 13 (58.65 kJ/mol) were determined by variable-temperature 1H-NMR spectroscopy, thus reflecting different degrees of B=N double bond character in the corresponding compounds. In addition, ring external olefin isomers 11 were obtained by a reaction between 2 and DurBBr2. All obtained B=N-containing products were characterized by multinuclear NMR spectroscopy. Compounds 5, 9, 10a, 11, and 13a were also characterized by single-crystal X-ray diffraction analysis. [ABSTRACT FROM AUTHOR]

Laser printer-emitted nanoparticles (PEPs) generated from toners during printing represent one of the most common types of life cycle released particulate matter from nano-enabled products. Toxicological assessment of PEPs is therefore important for occupational and consumer health protection. Our group recently reported exposure to PEPs induces adverse cardiovascular responses including hypertension and arrythmia via monitoring left ventricular pressure and electrocardiogram in rats. This study employed genome-wide mRNA and miRNA profiling in rat lung and blood integrated with metabolomics and lipidomics profiling in rat serum to identify biomarkers for assessing PEPs-induced disease risks. Whole-body inhalation of PEPs perturbed transcriptional activities associated with cardiovascular dysfunction, metabolic syndrome, and neural disorders at every observed time point in both rat lung and blood during the 21 days of exposure. Furthermore, the systematic analysis revealed PEPs-induced transcriptomic changes linking to other disease risks in rats, including diabetes, congenital defects, auto-recessive disorders, physical deformation, and carcinogenesis. The results were also confirmed with global metabolomics profiling in rat serum. Among the validated metabolites and lipids, linoleic acid, arachidonic acid, docosahexanoic acid, and histidine showed significant variation in PEPs-exposed rat serum. Overall, the identified PEPs-induced dysregulated genes, molecular pathways and functions, and miRNA-mediated transcriptional activities provide important insights into the disease mechanisms. The discovered important mRNAs, miRNAs, lipids and metabolites may serve as candidate biomarkers for future occupational and medical surveillance studies. To the best of our knowledge, this is the first study systematically integrating in vivo, transcriptomics, metabolomics, and lipidomics to assess PEPs inhalation exposure-induced disease risks using a rat model. [ABSTRACT FROM AUTHOR]