Testing the assumption that more anthropomorphic (human-like) computer representations elicit more social responses from people, a between-participants experiment (
N
=
168) manipulated 12 computer ...agents to represent four levels of anthropomorphism: low, medium, high, and real human images. Social responses were assessed with users’ social judgment and homophily perception of the agents, conformity in a choice dilemma task, and competency and trustworthiness ratings of the agents. Linear polynomial trend analyses revealed significant linear trends for almost all the measures. As the agent became more anthropomorphic to being human, it received more social responses from users.
Wind speed forecasting is critical for wind energy conversion systems since it greatly influences the issues such as the scheduling of a power system, and the dynamic control of the wind turbine. In ...this paper, we present a comprehensive comparison study on the application of different artificial neural networks in 1-h-ahead wind speed forecasting. Three types of typical neural networks, namely, adaptive linear element, back propagation, and radial basis function, are investigated. The wind data used are the hourly mean wind speed collected at two observation sites in North Dakota. The performance is evaluated based on three metrics, namely, mean absolute error, root mean square error, and mean absolute percentage error. The results show that even for the same wind dataset, no single neural network model outperforms others universally in terms of all evaluation metrics. Moreover, the selection of the type of neural networks for best performance is also dependent upon the data sources. Among the optimal models obtained, the relative difference in terms of one particular evaluation metric can be as much as 20%. This indicates the need of generating a single robust and reliable forecast by applying a post-processing method.
Polydimethylsiloxanes (PDMS) foam as one of next‐generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. ...Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self‐adhesive PDMS foam materials are reported with worm‐like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip‐coating strategy followed by silane surface modification. Interestingly, such self‐adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano‐coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super‐hydrophobicity (water contact angle of ≈159o), tunable electrical conductivity (from 10−8 to 10 S m−1), stable compressive cyclic reliability in both wide‐temperature range (from −20 to 200 oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire‐safe thermal insulation.
Polydimethylsiloxanes (PDMS) foam usually exhibits poor surface adhesion and limited functionality, restricting the potential applications. Here, self‐adhesive PDMS foams with worm‐like rough structure and reactive groups are fabricated by a facile silicone foaming approach. Decorating with MXene/cellulose nanofiber interconnected network and using silane modification, exceptional multifunctionalities PDMS nanocomposites are prepared, showing versatile applications in thermal insulating and smart sensing fields.
•The QDFrHT is proposed to generalize the discrete fractional Hartley transform into quaternion transform domain.•A large-capacity image compression and encryption scheme based on QDFrHT and an ...improved adaptive pixel diffusion is developed.•The storage and transmission of the keys are more convenient due to small key consumption.•Secret keys utilized in the proposed scheme are independent to original images.•An improved adaptive pixel diffusion operation makes the proposed cryptosystem immune to the known-plaintext attack and the chosen-plaintext attack.
A new multi-image encryption scheme based on quaternion discrete fractional Hartley transform (QDFrHT) and an improved pixel adaptive diffusion is proposed, which can simultaneously increase the encryption capacity and reduce the consumption of keys. In the proposed scheme, the QDFrHT is proposed to generalize the discrete fractional Hartley transform to quaternion transform domain and then applied to multi-image encryption. The original images are compressed into four fusion images by discrete cosine transform (DCT) and Zigzag operations and then the resulting four images are represented as quaternion algebra. Afterward, the quaternion signal is processed with the proposed QDFrHT and the double random phase encoding technique. To enhance the security of the algorithm, the plaintext-related pixel adaptive diffusion and the pixel scrambling operation based on chaotic systems are followed to obtain the final encryption image. Different from the traditional cryptosystem whose secret keys are dependent on the plaintext, the designed cryptosystem ensures the sensitivity of the cryptosystem to plaintext while the selection of the secret keys is independent on plaintext by introducing an improved diffusion mechanism. Numerical experiments verify the feasibility and the efficiency of the proposed multi-image compression and encryption scheme.
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•Graphene oxide nanoribbons functionalized by two types of silane molecules were successfully synthesized.•The functionalized graphene nanoribbon based sponges were prepared via a ...facile dip-coating process.•The modified sponges possessed excellent mechanical elasticity/durability and good electrical conductivity.•Two silane-modified sponges showed different super-hydrophobicity and oleophilicity/oleophobicity.•The super-hydrophobic sponges exhibited efficient oil/water separation at both static and dynamic states.
Graphene oxide nanoribbons (GONRs) were synthesized and functionalized by silane molecules with different hydrophobic end-groups, and silane functionalized reduced GONR (silane-f-rGONR) coated polyurethane (PU) sponge composites were fabricated via a facile dip-coating process. Fourier-transform infrared, Raman spectrum, X-ray photoelectron spectroscopy and scanning electron microscopy demonstrated that silane molecules were successfully grafted onto GONR sheets, thus producing the ability to tune surface and physical properties of PU sponge from insulating and hydrophobic to conductive and super-hydrophobic. Cyclic compression and strain-induced electrical resistance change tests indicated that the porous silane-f-rGONR coated PU (silane-f-rGONR@PU) sponge composites exhibited excellent mechanical elasticity and durability and high sensitivity of resistance change. Furthermore, the two types of silane modified sponges showed different super-hydrophobicity and tunable oleophilicity/oleophobicity. Compared to the rGONR@PU composite with poor oil/water separation at dynamic state, these porous silane-f-rGONR@PU composites not only possessed excellent oil/solvent absorption capacity and selective oil/water separation at static state, but also showed good continuous oil/solvent pumping collection with high recyclability (>97% after 10 cycles) and outstanding oil/water separation efficiency at the dynamic shaking state. This work provides a new strategy for fabricating the super-hydrophobic, electrically conductive and mechanically flexible porous rGONR based composites, showing promising application in strain sensor and oil pollution remediation fields at different environmental conditions.
The integrated functions of diagnostics and therapeutics make theranostics great potential for personalized medicine. Stimulus-responsive therapy allows spatial control of therapeutic effect only in ...the site of interest, and offers promising opportunities for imaging-guided precision therapy. However, the imaging strategies in previous stimulus-responsive therapies are 'always on' or irreversible 'turn on' modality, resulting in poor signal-to-noise ratios or even 'false positive' results. Here we show the design of dual-stimuli-responsive and reversibly activatable nanoprobe for precision tumour-targeting and fluorescence-guided photothermal therapy. We fabricate the nanoprobe from asymmetric cyanine and glycosyl-functionalized gold nanorods (AuNRs) with matrix metalloproteinases (MMPs)-specific peptide as a linker to achieve MMPs/pH synergistic and pH reversible activation. The unique activation and glycosyl targetibility makes the nanoprobe bright only in tumour sites with negligible background, while AuNRs and asymmetric cyanine give synergistic photothermal effect. This work paves the way to designing efficient nanoprobes for precision theranostics.
The distant metastasis of cancer cells is a risk factor for tumor lethality and poor prognosis in non-small-cell lung carcinoma (NSCLC). Increased SOX9 expression has been associated with clinical ...stage and poor prognosis in NSCLC, but the molecular mechanisms by which SOX9 promotes metastasis in NSCLC are still unknown.
The relationship between SOX9 expression and T, N, M classification was assessed using the χ
test and Spearman's analysis in 142 immunohistochemically diagnosed specimens of NSCLC. We also generated SOX9-overexpression and SOX9-knockdown cells lines and their corresponding control cell lines by transfection with lentiviral constructs. In vivo assay, SOX9-overexpressing and SOX9-knockdown NSCLC cells were injected in zebrafish to examine distance metastasis. Gene set enrichment analysis (GSEA) was applied to analysis the correlation between SOX9 overexpression and Wnt/β-catenin pathway. Luciferase assay was used to check transcriptional activity of TCF/LEF and western blot and immunofluorescence was employed to detect β-catenin translocation in SOX9-overexpression, SOX9-knockdown and their corresponding control cell lines.
We found that SOX9 overexpression correlates with the T, N and M stage significantly (p = 0.03, 0.000, and 0.032 respectively) in 142 immunohistochemically diagnosed specimens of NSCLC. SOX9 overexpression was found to decrease the expression of the epithelial cell markers E-cadherin and γ-catenin and increase the expression of the mesenchymal cell markers N-cadherin and vimentin. An in vivo assay showed distant metastasis of the SOX9-overexpressing cells, which was not observed in the SOX9-knockdown cells. These findings indicate that SOX9 promotes distant metastasis by promoting EMT in NSCLC cells. GSEA showed that SOX9 overexpression was significantly correlated with the Wnt/β-catenin pathway which was corroborated by the expression of EMT-associated proteins in this pathway and its downstream target genes. SOX9 overexpression was also found to enhance the transcriptional activity of TCF/LEF, promote the nuclear translocation of β-catenin and increase the phosphorylation of GSK3β at Ser9. Further, inhibition of β-catenin suppressed the metastasis-promoting effects of SOX9 overexpression.
This study is the first to report that SOX9 is associated with clinical TNM stage and indicates that SOX9 promotes migration, invasion and the EMT process through the Wnt/β-catenin pathway.
Background
The usefulness of 3D deep learning‐based classification of breast cancer and malignancy localization from MRI has been reported. This work can potentially be very useful in the clinical ...domain and aid radiologists in breast cancer diagnosis.
Purpose
To evaluate the efficacy of 3D deep convolutional neural network (CNN) for diagnosing breast cancer and localizing the lesions at dynamic contrast enhanced (DCE) MRI data in a weakly supervised manner.
Study Type
Retrospective study.
Subjects
A total of 1537 female study cases (mean age 47.5 years ±11.8) were collected from March 2013 to December 2016. All the cases had labels of the pathology results as well as BI‐RADS categories assessed by radiologists.
Field Strength/Sequence
1.5 T dynamic contrast‐enhanced MRI.
Assessment
Deep 3D densely connected networks were trained under image‐level supervision to automatically classify the images and localize the lesions. The dataset was randomly divided into training (1073), validation (157), and testing (307) subsets.
Statistical Tests
Accuracy, sensitivity, specificity, area under receiver operating characteristic curve (ROC), and the McNemar test for breast cancer classification. Dice similarity for breast cancer localization.
Results
The final algorithm performance for breast cancer diagnosis showed 83.7% (257 out of 307) accuracy (95% confidence interval CI: 79.1%, 87.4%), 90.8% (187 out of 206) sensitivity (95% CI: 80.6%, 94.1%), 69.3% (70 out of 101) specificity (95% CI: 59.7%, 77.5%), with the area under the curve ROC of 0.859. The weakly supervised cancer detection showed an overall Dice distance of 0.501 ± 0.274.
Data Conclusion
3D CNNs demonstrated high accuracy for diagnosing breast cancer. The weakly supervised learning method showed promise for localizing lesions in volumetric radiology images with only image‐level labels.
Level of Evidence: 4
Technical Efficacy: Stage 1
J. Magn. Reson. Imaging 2019;50:1144–1151.
A practical method through sunlight mediated annulation of α,β‐unsaturated hydrazones has been developed for the synthesis of pyrazole. Based on the analysis of UV‐Vis absorption of the substrate, ...the reaction was designed to avoid the use of external photocatalysis and proceeds via direct irradiation of N‐centred anion by sunlight. The key features of this reaction include operational simplicity, readily available reagents, and amenability to gram‐scale synthesis.
Several studies have found that primary sclerosing cholangitis (PSC) and inflammatory bowel disease (IBD) are closely associated. However, the direction and causality of their interactions remain ...unclear. Thus, this study employs Mendelian Randomization to explore whether there are causal associations of genetically predicted PSC with IBD.
Genetic variants associated with the genome-wide association study (GWAS) of PSC were used as instrumental variables. The statistics for IBD, including ulcerative colitis (UC), and Crohn's disease (CD) were derived from GWAS. Then, five methods were used to estimate the effects of genetically predicted PSC on IBD, including MR Egger, Weighted median (WM), Inverse variance weighted (IVW), Simple mode, and Weighted mode. Last, we also evaluated the pleiotropic effects, heterogeneity, and a leave-one-out sensitivity analysis that drives causal associations to confirm the validity of the analysis.
Genetically predicted PSC was significantly associated with an increased risk of UC, according to the study (odds ratio OR IVW= 1.0014, P<0.05). However, none of the MR methods found significant causal evidence of genetically predicted PSC in CD (All P>0.05). The sensitivity analysis results showed that the causal effect estimations of genetically predicted PSC on IBD were robust, and there was no horizontal pleiotropy or statistical heterogeneity.
Our study corroborated a causal association between genetically predicted PSC and UC but did not between genetically predicted PSC and CD. Then, we identification of shared SNPs for PSC and UC, including rs3184504, rs9858213, rs725613, rs10909839, and rs4147359. More animal experiments and clinical observational studies are required to further clarify the underlying mechanisms of PSC and IBD.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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