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IntroductionAttentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings.MethodsThirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording.ResultsSelf-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls.ConclusionsThe study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.

Excessive pressure drop within the internal flow channel of the water hydraulic throttle valve will generate severe noise. In order to reduce the noise of the throttle valve, in this paper, the model of the throttle valve was established, and the flow characteristics and acoustic characteristics of the valve were simulated. The simulation results showed that the parameters of the throat structure, such as the half angle, throat inlet angle and throat length, have a significant effect on the noise of the valve. Then, the three main structural parameters were used as optimization variables, and radial basis function (RBF) neural networks and multi-island genetic algorithms (MIGA) were used to reduce the noise of the valve. The approximate model of the relationship between the structural parameters of the valve and noise was established by RBF neural networks, and MIGA was used to optimize the approximate model. Finally, the optimal valve model was established based on the obtained optimal parameters, and its noise was analyzed through simulation and experiment. The research results indicated that the optimization method, which combines RBF Neural Network and MIGA, can effectively reduce the noise of hydraulic throttle valves.

The rational synthesis of zeolites with designed morphology is a highly challenging task. In this study, we propose 1,5-bis(methylpiperidine)pentylammonium hydroxide (BMPPAOH) as an organic structure-directing agent (OSDA) based on theoretical calculations. The morphology of zeolite samples is characterized by XRD, SEM, TEM, N2 sorption isotherms, and UV Raman spectroscopy. This simple bis-quaternary ammonium salt favored the formation of spiral morphology in Beta zeolite spheres (S-Beta). The crystallization of zeolite in the presence of BMMPAOH is a two-stage process, where nanoparticles agglomerate into spheres in the early stages followed by the emergence of S-Beta crystals with spiral morphology. The synthesized Pt-S-Beta catalysts show higher catalytic activity in VOC abatement compared with other Pt-Beta samples.

Abstract Background Aneuploidies are the most common chromosomal abnormality and the main genetic cause of adverse pregnancy outcomes. Since numerous studies have focused on common trisomies, relatively little is known about the association between phenotypic findings and rare autosomal aneuploidies (RAAs). We conducted a retrospective study of 48,904 cases for chromosomal microarray analysis in a large tertiary referral center and reported the overall frequencies, clinical manifestations, and outcomes of prenatal RAAs. Results A total of 90 RAAs were detected, of which 83 cases were mosaic trisomies and 7 were non-mosaic trisomies. Chromosomes 16, 22, and 9 were identified as the major chromosomes involving RAAs. The four predominant indications for prenatal diagnosis in our RAA cases were RAA-positive in noninvasive prenatal screening, advanced maternal age, ultrasound abnormalities, and high-risk for serum prenatal screening. Cardiovascular defects were the most frequently observed structural abnormalities, followed by musculoskeletal anomalies. Increased nuchal translucency and persistent left superior vena cava, the major soft marker abnormalities involved, were also observed in our RAA cases. Clinical outcomes were available for all RAAs, with 63 induced abortions and 27 live births recorded. Conclusions Variable phenotypes and outcomes were observed, which were highly heterogeneous in cases of prenatal RAAs. Thus, a cautious and comprehensive strategy should be implemented during prenatal counseling for RAAs.

In order to investigate the vibration characteristics of nuclear centrifugal pumps at low flow rates, the simulation prototype of centrifugal pump was built by mean of ANSYA CFD software, and the mechanism of reverse flow and rotating stall at low flow rates was analyzed. The type HAZ50-250 centrifugal pump was selected as prototype and the vibration was tested via Enpac2500 analytical instrument, it was shown that vibration frequency was concentrated in the low frequency range from 0.23 times rotation frequency to 0.25 times rotation frequency. Because at low flow rates, the pumps blade frequency is very sensitive to hydraulic disturbance, the vibration frequency including rotation frequency and two times rotation frequency will be accompanied as well. With the vibration frequency characteristic which was researched, the root cause of nuclear centrifugal pumps hydraulic vibration was analyzed, the improvement and optimization suggestions was forwarded, relative conclusion and method which could be regarded as an important reference for vibration analysis and pumps design.

ObjectiveTo develop an accurate and automatic segmentation model based on convolution neural network to segment the prostate and its lesion regions.MethodsOf all 180 subjects, 122 healthy individuals and 58 patients with prostate cancer were included. For each subject, all slices of the prostate were comprised in the DWIs. A novel DCNN is proposed to automatically segment the prostate and its lesion regions. This model is inspired by the U-Net model with the encoding-decoding path as the backbone, importing dense block, attention mechanism techniques, and group norm-Atrous Spatial Pyramidal Pooling. Data augmentation was used to avoid overfitting in training. In the experimental phase, the data set was randomly divided into a training (70%), testing set (30%). four-fold cross-validation methods were used to obtain results for each metric.ResultsThe proposed model achieved in terms of Iou, Dice score, accuracy, sensitivity, 95% Hausdorff Distance, 86.82%,93.90%, 94.11%, 93.8%,7.84 for the prostate, 79.2%, 89.51%, 88.43%,89.31%,8.39 for lesion region in segmentation. Compared to the state-of-the-art models, FCN, U-Net, U-Net++, and ResU-Net, the segmentation model achieved more promising results.ConclusionThe proposed model yielded excellent performance in accurate and automatic segmentation of the prostate and lesion regions, revealing that the novel deep convolutional neural network could be used in clinical disease treatment and diagnosis.

ObjectiveRecent knowledge concerning the significance of long non-coding RNA (lncRNA)-mediated ceRNA networks provides new insight into their possible roles as specific biomarkers for the treatment of osteosarcoma (OS). Thus, this study aims to clarify the functional relevance and mechanistic actions of lncRNA LBX2-AS1 in OS.MethodsDifferential analysis was performed by integrating the TCGA and GTEx databases. Cox regression analysis was then employed to assess the prognostic value of the model. The expression of lncRNA LBX2-AS1 and miR-597-3p was quantified in OS cell lines by qRT-PCR. The proliferation, migration, invasion, and apoptosis of OS cell lines in response to manipulated lncRNA LBX2-AS1 were evaluated by MTT, colony formation, transwell, Western blot, and flow cytometry assays. Luciferase activity was assayed to validate the reciprocal regulation between lncRNA LBX2-AS1 and miR-597-3p. The protein levels of BRD4 and EMT-related factors were examined by Western blot assay. Finally, tumor growth in response to LBX2-AS1 knockdown was evaluated in xenograft-bearing nude mice.ResultsBy integrating the GTEx and TCGA databases, we identified 153 differentially expressed lncRNAs. Among them, 5 lncRNAs, RP11-535M15.1, AC002398.12, RP3-355L5.4, LBX2-AS1, and RP11.47A8.5, were selected to establish a model, which predicted the prognosis of OS. Higher lncRNA LBX2-AS1 expression was noted in OS tissues relative to that in normal tissues. Silencing lncRNA LBX2-AS1 facilitated apoptosis and curtailed proliferative, migratory, and invasive capacities of OS cells. Mechanistically, lncRNA LBX2-AS1 could elevate the expression of BRD4, an oncogene, by competitively binding to miR-597-3p. More importantly, knockdown of lncRNA LBX2-AS1 increased the sensitivity of OS cells to the BRD4 inhibitor JQ-1. Finally, the tumor growth of OS cell xenografts was constrained in vivo in the presence of lncRNA LBX2-AS1 knockdown.ConclusionIn conclusion, lncRNA LBX2-AS1 promotes the growth of OS and represses the sensitivity to JQ-1 by sponging miR-597-3p to elevate the expression of BRD4.

Torreya grandis meal has a high protein content and an appropriate amino acid ratio, making it an excellent protein source for producing ACE inhibitory peptides. To promote its application in food, medicine, and other fields, an alkaline protease hydrolysate of Torreya grandis was used in this study to isolate and identify a novel angiotensin-converting enzyme inhibitory peptide, VNDYLNW (VW-7), using ultrafiltration, gel chromatography purification, LC-MS/MS, and in silico prediction. The results show that the IC50 value of VW-7 was 205.98 µM. The Lineweaver–Burk plot showed that VW-7 had a mixed-type inhibitory effect on ACE. Meanwhile, according to the results of molecular docking, VW-7 demonstrated a strong affinity for ACE (binding energy −10 kcal/mol). VW-7 was bound to ACE through multiple binding sites. In addition, VW-7 could remain active during gastrointestinal digestion in vitro. Nitric oxide (NO) generation in human endothelial cells could rise after receiving a pretreatment with VW-7. These results indicated that Torreya grandis meal protein can be developed into products with antihypertensive function, and VW-7 has broad application prospects in the field of antihypertensive.

Abstract The prediction of production volumes from shale gas wells is important in reservoir development. The physical parameters of a reservoir are uncertain and complex, and therefore, it is very difficult to predict the production capability of a shale gas well. An improved GM(1, N) model for shale gas well productivity prediction, focused upon the causes of prediction errors from the existing traditional GM(1, N) method, was established. By processing a data series related to the predicted data, the improved GM(1, N) model takes into account the fluctuations of the original production data, reflects the trend of the original data under the influence of relevant factors, and hence predicts more accurately the fluctuation amplitude and direction of the original data. Additionally, the proposed method has higher accuracy than the conventional GM(1, N), GM(1, 1), and MEP models. The prediction accuracy increases gradually and the relative error decreases gradually from bottom data (casing pressure at well start-up, etc.) to top data (shale gas production). Accordingly, a step-by-step prediction method could be effective in improving prediction accuracy and reflects the typical fluctuation characteristics of shale gas production.

This paper proposes an extension of numerical P (NP) systems, called stochastic numerical P (StNP) systems. In StNP systems, a novel stochastic production function-repartition protocol is developed to evolve the variables. Compared with usual production function-repartition protocol in NP systems, there are two differences in stochastic production function-repartition protocol: (i) some stochastic/randomized factors are introduced in production function and/or repartition protocol; (ii) data updating way is relaxed and can be flexibly used. An StNP system has a nested structure and contains some variables and a group of programs. The programs consist of stochastic production function-repartition protocols and/or usual production function-repartition protocols. Therefore, StNP systems are a class of distributed parallel computing models with stochastic and dynamic characteristics. Data clustering problems are used as an application to demonstrate the availability and effectiveness of StNP systems. Based on StNP systems, a novel partition clustering algorithm is presented. Experimental results demonstrate advantage of StNP systems for data clustering problems.

Abstract Background The identification of cell-free fetal DNA (cffDNA) facilitated non-invasive prenatal screening (NIPS) through analysis of cffDNA in maternal plasma. However, challenges regarding its clinical implementation become apparent. Factors affecting fetal fraction should be clarified to guide its clinical application. Results A total of 13,661 pregnant subjects with singleton pregnancies who undertook NIPS were included in the study. Relationship of gestational age, maternal BMI, and maternal age with the cffDNA fetal fraction in maternal plasmas for NIPS was investigated. Compared with 13 weeks (12.74%) and 14–18 weeks group (12.73%), the fetal fraction in gestational ages of 19–23 weeks, 24–28 weeks, and more than 29 weeks groups significantly increased to 13.11%, 16.14%, and 21.17%, respectively (P

Effect of the diamond nanoparticle on the friction property of the sliding friction pair is investigated using the molecular dynamics simulation. A molecular dynamics simulation model without the diamond nanoparticle is also set up. The simulation is conducted at an external load of 60 nN. The results confirm that adding diamond nanoparticle can improve the friction property. With increasing the diameter, the angular velocity, and the indentation depth decrease inversely. Also, when the diameter varies from 32.13 Å to 49.98 Å, the friction force, and the contact area are both inversely proportional to 3.6 power of the diameter. The relationship between friction force and contact area shows a linear increase law, which indicates that friction force is affected by the contact area.

Objectives The study aim was to determine the effect of an occupational blood-borne pathogen exposure (OBE) management program based on the PRECEDE-PROCEED model on knowledge, attitude and behaviour regarding OBE prevention among operating room nurses. Methods This was a one-group pre-test post-test experimental study. The PRECEDE-PROCEED model was used to design and evaluate the effect of an OBE management program on 87 operating room nurses from February to July 2018. The study included pre-intervention assessment; risk factor analysis; interventions targeted to predisposing, reinforcing and enabling factors and focusing on areas of low scoring; and a post-intervention assessment. Attitudes, knowledge and behaviour compliance regarding OBE were measured before and after the 6-month program using a self-developed questionnaire. Descriptive epidemiological analysis and t-tests were used for data analysis. Results Low-scoring items for OBE knowledge, attitudes and behaviour were identified in the baseline assessment. Six months post-intervention, there were significant improvements in attitudes toward OBE prevention, in knowledge about OBE safety precautions and in behaviour compliance with standard precautions. Conclusions The findings indicate the effectiveness of an OBE management program based on the PRECEDE-PROCEED model for improving knowledge, attitudes and behaviour adherence to OBE prevention among operating room nurses.

Given the numerous industrial applications of zeolites as adsorbents, catalysts, and ion-exchangers, the development of new zeolite structures is highly desired to expand their practical applications. Currently, a general route to develop new zeolite structures is to use interlayer expansion agents to connect layered silicates. In this review, we briefly summarize the novel zeolite structures constructed from the lamellar precursor zeolites MWW, RUB-36, PREFER, Nu-6(1), COK-5, and PLS-1 via interlayer expansion. The contents of the summary contain detailed experiments, physicochemical characterizations, possible expansion mechanisms, and catalytic properties. In addition, the insertion of metal heteroatoms (such as Ti, Fe, Sn) into the layered zeolite precursor through interlayer expansion, which could be helpful to modify the catalytic function, is discussed.

Intensive longitudinal data has been widely used to examine reciprocal or causal relations between variables. However, these variables may not be temporally aligned. This study examined the consequences and solutions of the problem of temporal misalignment in intensive longitudinal data based on dynamic structural equation models. First the impact of temporal misalignment on parameter estimation were investigated in a simulation study, which showed that temporal misalignment led to incomparable cross-lagged effects between variables. Then, two solutions, model adjustment and data interpolation, were proposed, and their performance was compared with those of the naive estimation which blindly treating temporally misaligned data as aligned. The simulation results supported the effectiveness of the model adjustment method over the other two methods. Finally, all three methods were applied to two empirical data collected by daily diaries and empirical sampling method, and recommendations were made for collecting and analyzing intensive longitudinal data.

The crystal structures and microwave dielectric properties of (Na1/2Nd1/2)TiO₃ (NNT) ceramics with x wt. % CeO₂ dopants (x = 0, 0.15, 0.3, 0.45) were investigated in this paper. X-ray diffraction (XRD) results showed that all the samples fitted well with a single perovskite structure phase in a Pm-3m space group. The lattice parameters increased because of the replacement of Ce4+ at the B-site. The change of dielectric constant (εr) was similar to that of ionic polarizabilities. The temperature coefficient of resonant frequency (τf) value of samples displayed a decreasing tendency with increasing x. The quality factor (Qxf) was found to have a maximum value of 8287 GHz at x = 0.3. As a result, when x = 0.3, the (Na1/2Nd1/2)TiO₃ ceramics sintered at 1300 °C for 2 h has good microwave dielectric properties of εr = 105.36, high Qxf = 8287 GHz, and τf = 246.3 ppm/ °C.

The continuous spontaneous localization (CSL) model predicts a tiny break of energy conservation via a weak stochastic force acting on physical systems, which triggers the collapse of the wave function. Mechanical oscillators are a natural way to test such a force; in particular, a levitated micromechanical oscillator has been recently proposed to be an ideal system. We report a proof-of-principle experiment with a micro-oscillator generated by a microsphere diamagnetically levitated in a magnetogravitational trap under high vacuum. Due to the ultralow mechanical dissipation, the oscillator provides a new upper bound on the CSL collapse rate, which gives an improvement of two orders of magnitude over the previous bounds in the same frequency range, and partially reaches the enhanced collapse rate suggested by Adler. Although being performed at room temperature, our experiment has already exhibited advantages over those operating at low temperatures. Our results experimentally show the potential for a magnetogravitational levitated mechanical oscillator as a promising method for testing the collapse model. Further improvements in cryogenic experiments are discussed.

Photocatalytic degradation of triclosan is one of the most promising way to eliminate triclosan pollution in water, yet it presents profound challenges to develop efficient photocatalysts to meet the demand of application. Herein, we demonstrate a facile hydrothermal-precipitation method to prepare amorphous Nb _2 O _5 catalysts by using niobium(V) oxalate hydrate and ammonium carbonate. A series of amorphous Nb _2 O _5 catalysts were obtained and analyzed by detail characterizations (XRD, XPS, BET and SEM). By optimizing synthesis conditions, it was found that 180/12-Nb _2 O _5 -(1:5) catalyst exhibited the optimal photocatalytic activity for triclosan degradation. Furthermore, the pseudo-first-order kinetic equations for triclosan degradation over 180/12-Nb _2 O _5 -(1:5) catalyst were investigated under conditions with different pH value. Among them, the triclosan degradation rate over 180/12-Nb _2 O _5 -(1:5) catalyst gave the highest reaction constant k (0.5 min ^−1 ) and shortest half-period (t _1/2 = 0.17 min ^−1 ) at pH of 8. The presence of ionic state triclosan in base condition should be responsible for the improved degradation rate from acid to base reaction condition. Compared with molecular triclosan, ionic state triclosan exhibits very high reaction rate with radicals due to its strong electrophilic property. The high photocatalytic activity of 180/12-Nb _2 O _5 -(1:5) catalyst should be related to the presence of amorphous structure compared with calcined 180/12-Nb _2 O _5 -(1:5) catalyst with highly crystalline structure. The existence of N species doping and nano-sheet structure in catalyst is also thought to promote the catalytic reaction.

P systems are a class of distributed parallel computing models; this paper presents a novel clustering algorithm, which is inspired from mechanism of a tissue-like P system with a loop structure of cells, called membrane clustering algorithm. The objects of the cells express the candidate centers of clusters and are evolved by the evolution rules. Based on the loop membrane structure, the communication rules realize a local neighborhood topology, which helps the coevolution of the objects and improves the diversity of objects in the system. The tissue-like P system can effectively search for the optimal partitioning with the help of its parallel computing advantage. The proposed clustering algorithm is evaluated on four artificial data sets and six real-life data sets. Experimental results show that the proposed clustering algorithm is superior or competitive to k-means algorithm and several evolutionary clustering algorithms recently reported in the literature.

This paper aims to extend the extant (primarily Western) organizational culture literature to emerging economies by explicitly incorporating two key contextual variables-ownership type and firm size into organizational culture model. Based on the theoretical model developed by Denison and his colleagues, we examined the impact of ownership type and firm size on organizational culture, as well as the moderating effect of the two contextual variables on the linkage between organizational culture and firm effectiveness. Using survey data from foreign-invested and state-owned firms in China, we find that ownership type and firm size have significant influence on organizational culture. We also find that different ownership type and firm size result in different organizational cultural effect on performance.

In vitro hypoxic preconditioning (HP) of mesenchymal stem cells (MSCs) could ameliorate their viability and tissue repair capabilities after transplantation into the injured tissue through yet undefined mechanisms. There is also experimental evidence that HP enhances the expression of both stromal-derived factor-1 (SDF-1) receptors, CXCR4 and CXCR7, which are involved in migration and survival of MSCs in vitro, but little is known about their role in the in vivo therapeutic effectiveness of MSCs in renal ischemia/reperfusion (I/R) injury. Here, we evaluated the role of SDF-1-CXCR4/CXCR7 pathway in regulating chemotaxis, viability and paracrine actions of HP-MSCs in vitro and in vivo. Compared with normoxic preconditioning (NP), HP not only improved MSC chemotaxis and viability but also stimulated secretion of proangiogenic and mitogenic factors. Importantly, both CXCR4 and CXCR7 were required for the production of paracrine factors by HP-MSCs though the former was only responsible for chemotaxis while the latter was for viability. SDF-1α expression was upregulated in postischemic kidneys. After 24 h systemical administration following I/R, HP-MSCs but not NP-MSCs were selectively recruited to ischemic kidneys and this improved recruitment was abolished by neutralization of CXCR4, but not CXCR7. Furthermore, the increased recruitment of HP-MSCs was associated with enhanced functional recovery, accelerated mitogenic response, and reduced apoptotic cell death. In addition, neutralization of either CXCR4 or CXCR7 impaired the improved therapeutic potential of HP-MSCs. These results advance our knowledge about SDF-1-CXCR4/CXCR7 axis as an attractive target pathway for improving the beneficial effects of MSC-based therapies for renal I/R.