One-step hydrothermal synthesis of fluorescence carbon quantum dots with high product yield and quantum yield

A one-step hydrothermal synthesis of nitrogen and silicon co-doped fluorescence carbon quantum dots (N,Si-CQDs), from citric acid monohydrate and silane coupling agent KH-792 with a high product yield (PY) of 52.56% and high quantum yield (QY) of 97.32%, was developed. This greatly improves both the PY and QY of CQDs and provides a new approach for a large-scale production of high-quality CQDs. Furthermore, N,Si-CQDs were employed as phosphors without dispersants to fabricate white light-emitting diodes (WLEDs) with the color coordinates at (0.29, 0.32). It is suggested that N,Si-CQDs have great potential as promising fluorescent materials to be applied in WLEDs.Peer reviewe

The Construction of a Clinical Decision Support System Based on Knowledge Base

Part 7: e-Health, the New Frontier of Service Science InnovationInternational audienceBased on a review of domestic and foreign research, application status, classification, composition, and the main problem of a clinical decision support system, this paper proposed a CDSS mode based on a knowledge base. On KB-CDSS mode, this paper discussed the architecture, principle, process, construction of the knowledge base, system design, and application value, then introduced the application WanFang Data Clinical Diagnosis and Treatment Knowledge Base

CNN-based Prediction of Network Robustness With Missing Edges

Connectivity and controllability of a complex network are two important issues that guarantee a networked system to function. Robustness of connectivity and controllability guarantees the system to function properly and stably under various malicious attacks. Evaluating network robustness using attack simulations is time consuming, while the convolutional neural network (CNN)-based prediction approach provides a cost-efficient method to approximate the network robustness. In this paper, we investigate the performance of CNN-based approaches for connectivity and controllability robustness prediction, when partial network information is missing, namely the adjacency matrix is incomplete. Extensive experimental studies are carried out. A threshold is explored that if a total amount of more than 7.29\% information is lost, the performance of CNN-based prediction will be significantly degenerated for all cases in the experiments. Two scenarios of missing edge representations are compared, 1) a missing edge is marked `no edge' in the input for prediction, and 2) a missing edge is denoted using a special marker of `unknown'. Experimental results reveal that the first representation is misleading to the CNN-based predictors.Comment: In Proceedings of the IEEE 2022 International Joint Conference on Neural Networks (IJCNN

Analysis of contributions of herpes simplex virus type 1 UL43 protein to induction of cell-cell fusion

Purpose: To investigate whether UL43 protein, which is highly conserved in alpha- and gamma herpes viruses, and a non-glycosylated transmembrane protein, is involved in virus entry and virus-induced cell fusion.Methods: Mutagenesis was accomplished by a markerless two-step Red  recombination mutagenesis system implemented on the Herpes simplex virus 1 (HSV-1) bacterial artificial chromosome (BAC). Growth properties of HSV-1 UL43 mutants were analyzed using plaque morphology and one-step growth kinetics. SDS-PAGE and Western blot was employed to assay the synthesis of the viral glycoproteins. Virus-penetration was assayed to determine if UL43 protein is required for efficient virus entry.Results: Lack of UL43 expression resulted in significantly reduced plaque sizes of syncytial mutant viruses and inhibited cell fusion induced by gBΔ28 or gKsyn20 (p < 0.05). Deletion of UL43 did not affect overall expression levels of viral  glycoproteins gB, gC, gD, and gH on HSV-1(F) BAC infected cell surfaces.  Moreover, mutant viruses lacking UL43 gene exhibited slower kinetics of entry into Vero cells than the parental HSV-1(F) BAC.Conclusion: Thus, these results suggest an important role for UL43 protein in  mediating virus-induced membrane fusion and efficient entry of virion into target cells.Keywords: Herpes simplex virus type 1, UL43 protein, Membrane fusion, Mutant viruses, Virion, Mutagenesi

catena-Poly[[nickel(II)-μ3-1,1-dicyano­ethene-2,2-dithiol­ato-κ4 S,S′:N:N′-bis­[(15-crown-5)magnesium(II)]-μ3-1,1-dicyano­ethene-2,2-dithiol­ato-κ4 N:N′:S,S′] dichloride]

The reaction of MgCl2, NiCl2, and Na2(i-mnt) (i-mnt is 1,1-dicyano­thene-2,2-dithiol­ate) with 15-crown-5 (15-C-5) leads to an infinite chain polymer, {[NiMg2(C4N2S2)2(C10H20O5)2]Cl2}n or {[Mg(15-C-5)]2[Ni(i-mnt)2]Cl2}n, which consists of two [Mg(15-C-5)]2+ complex cations, one [Ni(i-mnt)2]2− complex anion and two Cl− ions per formula unit. In the [Ni(i-mnt)2]2− complex anion, Ni2+ is located on a crystallographic mirror plane with a slightly distorted square-planar coordination by four S atoms. In the [Mg(15-C-5)]2+ complex cations, the Mg and one O atom of the crown lie on mirror planes and the Mg atoms are in sevenfold coordination environments of five O atoms from the crown and two N atoms from two i-mnt anions. The bridging of the two complexes via the Mg—N bonds leads to the formation of one-dimensional chains along the a axis

Efficient Monaural Speech Enhancement using Spectrum Attention Fusion

Speech enhancement is a demanding task in automated speech processing pipelines, focusing on separating clean speech from noisy channels. Transformer based models have recently bested RNN and CNN models in speech enhancement, however at the same time they are much more computationally expensive and require much more high quality training data, which is always hard to come by. In this paper, we present an improvement for speech enhancement models that maintains the expressiveness of self-attention while significantly reducing model complexity, which we have termed Spectrum Attention Fusion. We carefully construct a convolutional module to replace several self-attention layers in a speech Transformer, allowing the model to more efficiently fuse spectral features. Our proposed model is able to achieve comparable or better results against SOTA models but with significantly smaller parameters (0.58M) on the Voice Bank + DEMAND dataset

Factor Analysis Of The Market Environment For Artisanal Dimension Stone In Nairobi, Kenya

Artisanal dimension stone (i.e., blocks cut and shaped from natural rock using hand tools) has attracted scholarly attention as part of the informal sector of the construction industry and as part of the productive enterprise of artisans. One of the areas that intrigue scholars in this respect is the market environment of the subject product. In Nairobi, for instance, researchers have adopted a qualitative approach to the study of the market environment of artisanal dimension stone. We build on the outcomes of previous studies to present a quantitative approach to the factors influencing the market environment of artisanal dimension stone in Kenya by developing the factors identified in the past studies into 24 measurable variables that are then subjected to factor analysis to identify and gauge the principal components. The analysis identifies five principal components that influence the market environment: a difficult marketing terrain, a general lack of specification by building professionals and formal developers, occasional specification by building professionals, a cumbersome stone procurement system, and advantages provided by the use of artisanal dimension stone in building. These include both negative and positive factors, although the negative forces tend to dominate, resulting in an inhibitive rather than a facilitative environment. Recommendations are made to address this situation, including recommendations for an association with a mining advocacy organisation such as Communities and Small-Scale Mining (CASM) or similar institution and the formation of a marketing cooperative by the producing units to help in the formalisation of their transactions

Risk factors predicting a higher grade of subarachnoid haemorrhage in small ruptured intracranial aneurysm (< 5 mm)

Aim. To identify the risk factors for clinical and radiographic grades of subarachnoid haemorrhage (SAH) in small (&lt; 5 mm) intracranial aneurysms (SIAs). Material and methods. We retrospectively analysed patients with SIAs treated in our centre between February 2009 and June 2018. The clinical status was graded using the Hunt and Hess (H&amp;H) score and the radiological severity of SAH was graded by Fisher grades (FG). The risk factors were determined using multivariate logistic regression analysis. Results. A total of 160 patients with ruptured SIAs (&lt; 5 mm) were included. In univariate analysis, smoking (P = 0.007), alcohol use (P = 0.048), aspirin use (P = 0.001), and higher size ratio (SR) (P = 0.001) were significantly associated with a higher H&amp;H grade (3–5) in SIAs; and smoking (P = 0.019), aspirin use (P = 0.031), inflow angle &lt; 90 degrees (P = 0.011), and aneurysm size (P = 0.039) were significantly associated with a higher FG score (3–4). In the adjusted multivariate analysis, previous SAH (OR, 12.245, 95% CI, 2.261–66.334, P = 0.004), aspirin use (OR, 4.677, 95% CI, 1.392–15.718, P = 0.013), alcohol use (OR, 3.392, 95% CI, 1.146–10.045, P = 0.027), inflow angle &lt; 90 (OR, 3.881, 95% CI, 1.273–11.831, P = 0.017), and higher SR (OR, 6.611, 95% CI, 2.235–19.560, P = 0.001) were independent risk factors for a higher H&amp;H grade in ruptured SIAs; smoking (OR, 2.157, 95% CI, 1.061–4.384, P = 0.034), and inflow angle &lt; 90 degrees (OR, 2.603, 95% CI, 1.324–5.115, P = 0.006) were independent risk factors for a higher FG (3–4). Conclusions. This study revealed that inflow angle &lt; 90 degrees and size ratio, but not absolute size, may highly predict poorer grade of SAH in SRA. Aspirin use, previous SAH, and alcohol use were significantly associated with a higher H&amp;H grade in ruptured SIAs, and smoking was a significant predictor of poorer FG