Single-crystalline δ-Ni2Si nanowires with excellent physical properties

[[abstract]]In this article, we report the synthesis of single-crystalline nickel silicide nanowires (NWs) via chemical vapor deposition method using NiCl2·6H2O as a single-source precursor. Various morphologies of δ-Ni2Si NWs were successfully acquired by controlling the growth conditions. The growth mechanism of the δ-Ni2Si NWs was thoroughly discussed and identified with microscopy studies. Field emission measurements show a low turn-on field (4.12 V/μm), and magnetic property measurements show a classic ferromagnetic characteristic, which demonstrates promising potential applications for field emitters, magnetic storage, and biological cell separation.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子版[[booktype]]紙

Early determinants of food liking among 5y-old children: a longitudinal study from the EDEN mother-child cohort

International audienceAbstractBackgroundIdentifying the determinants of child’s liking for different foods may help to prevent future choices of unhealthy food.ObjectiveTo study early-life food-related characteristics associated with child’s liking for different foods at 5y with a longitudinal study.Design1142 5y- old children completed a liking test for “fruit and vegetables”, “meat, fish and eggs”, desserts and cheese. Data related to maternal food intake before pregnancy, infant feeding during the first year of life, maternal feeding practices at 2y, child’s food intake at 3y, and child’s food neophobia from 1 to 4y were collected prospectively from the mother. The associations between these factors and child‘s liking for each category of foods were analyzed using structural equation modelling.ResultsHigh food neophobia at 4 y was related to lower child’s liking for all food groups. Maternal feeding practices at 2y were associated with liking for dessert: negatively for the practices allowing child to control his/her own food intake, positively for restriction of child’s food intake for weight reasons. Moreover, child’s food intake at 3y was positively associated with child’s liking for “fruit and vegetables” as well as for cheese. Finally, adherence to the infant feeding pattern “long breastfeeding, later introduction of main meal components and use of home-made products” was positively associated with child’s liking for meat/fish/eggs.ConclusionsFor all food groups, food neophobia was a common determinant of child’s liking for food at 5y, whereas other factors were associated with food liking for specific food groups

Industry upgrading: recommendations of new products based on world trade network

GDP is a classic indicator of the extent of national economic development. Research based on the World Trade Network has found that a country’s GDP depends largely on the products it exports. In order to increase the competitiveness of a country and further increase its GDP, a crucial issue is finding the right direction to upgrade the industry so that the country can enhance its competitiveness. The proximity indicator measures the similarity between products and can be used to predict the probability that a country will develop a new industry. On the other hand, the Fitness–Complexity algorithm can help to find the important products and developing countries. In this paper, we find that the maximum of the proximity between a certain product and a country’s existing products is highly correlated with the probability that the country exports this new product in the next year. In addition, we find that the more products that are related to a certain product, the higher probability of the emergence of the new product. Finally, we combine the proximity indicator and the Fitness–Complexity algorithm and then attempt to provide a recommendation list of new products that can help developing countries to upgrade their industry. A few examples are given in the end

Effects of Chinese Formula Jueyin Granules on Psoriasis in an Animal Model

Although Traditional Chinese medicine (TCM) is known to be effective for psoriasis patients, the responsible mechanisms still remain poorly understood. In this study, we aimed to evaluate the effect of one formula, named Jueyin granules (JYG) in the mouse model of the vaginal epithelium and tail epidermis. Additionally, we also determined the anti-inflammatory effects of JYG in an imiquimod- (IMQ-) induced psoriasis-like skin mouse model. Our results show that JYG can attenuate the IMQ-induced psoriasis-like inflammation, accompanied with increased epidermal hyperplasia. We also measured estrogenic stage mitosis of vaginal epithelial cells and the formation of granular cell layers in male mouse tails per 100 scales, as well as the tissue nitric oxide (NO) and malondialdehyde (MDA) levels using the ELISA method. The results suggest that JYG significantly inhibited mitosis in mouse vaginal epithelial cells, promoted the formation of the squamous epidermal granular layer in mice tails, and reduced the levels of NO and MDA in an imiquimod-induced psoriasis-like skin mouse model after 14 d (P<0.05). These results demonstrate that JYG might be an effective clinical treatment for psoriasis and the effects may be related to inhibited keratinocytes proliferation, improved parakeratotic epidermal cells, and reduced expression of NO and MDA

Gas turbulence modulation in a two-fluid model for gas-solid flows

Recent rapid progress in the theoretical and experimental study of turbulence modulation has led to greater understanding of the physics of particle-gas turbulence interactions. A new two-fluid model incorporating these advances for relatively dilute gas-solid flows containing high-inertia particles is established. The effect of aerodynamic forces upon the particulate stresses is considered in this kinetic theory-based model, and the influence of the particles on the turbulent gas is addressed: the work associated with drag forces contributes to the gas turbulent energy, and the space occupied by particles restricts the turbulent length scale. The interparticle length scale, which is usually ignored, has been incorporated into a new model for determining the turbulent length scale. This model also considers the transport effect on the turbulent length scale. Simulation results for fully developed steady flows in vertical pipes are compared with a wide range of published experimental data and, generally, good agreement is shown. This comprehensive and validated model accounts for many of the interphase interactions that have been shown to be important

Tooth Position Determination by Automatic Cutting and Marking of Dental Panoramic X-ray Film in Medical Image Processing

This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, using the difference in pixel values to cut the image into several equal sections and then connecting each cavity feature point to extend a curve that completes the description of the separated jaw. The curve is shifted up and down to look for the gap between the teeth, to identify and address missing teeth and overlapping. Under FDI World Dental Federation notation, the left and right sides receive eight-code sequences to mark each tooth, which provides improved convenience in clinical use. According to the literature, X-ray film cannot be marked correctly when a tooth is missing. This paper utilizes artificial center positioning and sets the teeth gap feature points to have the same count. Then, the gap feature points are connected as a curve with the curve of the jaw to illustrate the dental segmentation. In addition, we incorporate different image-processing methods to sequentially strengthen the X-ray film. The proposed procedure had an 89.95% accuracy rate for tooth positioning. As for the tooth cutting, where the edge of the cutting box is used to determine the position of each tooth number, the accuracy of the tooth positioning method in this proposed study is 92.78%

A High-Accuracy Detection System: Based on Transfer Learning for Apical Lesions on Periapical Radiograph

Apical Lesions, one of the most common oral diseases, can be effectively detected in daily dental examinations by a periapical radiograph (PA). In the current popular endodontic treatment, most dentists spend a lot of time manually marking the lesion area. In order to reduce the burden on dentists, this paper proposes a convolutional neural network (CNN)-based regional analysis model for spical lesions for periapical radiographs. In this study, the database was provided by dentists with more than three years of practical experience, meeting the criteria for clinical practical application. The contributions of this work are (1) an advanced adaptive threshold preprocessing technique for image segmentation, which can achieve an accuracy rate of more than 96%; (2) a better and more intuitive apical lesions symptom enhancement technique; and (3) a model for apical lesions detection with an accuracy as high as 96.21%. Compared with existing state-of-the-art technology, the proposed model has improved the accuracy by more than 5%. The proposed model has successfully improved the automatic diagnosis of apical lesions. With the help of automation, dentists can focus more on technical and medical diagnoses, such as treatment, tooth cleaning, or medical communication. This proposal has been certified by the Institutional Review Board (IRB) with the certification number 202002030B0

Detection of Dental Apical Lesions Using CNNs on Periapical Radiograph

Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion

Associations of childcare arrangements with adiposity measures in a multi-ethnic Asian cohort : The gusto study

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Childcare arrangements shape behavioural patterns that influence the risk of childhood obesity. However, little is known of its influence on childhood obesity in Singapore. We aim to examine the associations between childcare arrangements at the age of 5 years and childhood adiposity at age 6 years. Children from the GUSTO study were grouped into three childcare arrangements at age 5: Full-time centre-based childcare (FC), partial centre-based with parental care (PCP), and partial centre-based with non-parents (grandparents and domestic helpers) as caregivers (PCN). Diet, physical activity and sedentary behaviour information were collected at age 5, while anthropometric measurements were collected at age 6. Associations were analysed using multivariable regression models. Among 540 children, those in PCN had higher BMI z-scores (β: 0.34; 95% CI: 0.01, 0.66), greater sum of skinfold thicknesses (mm) (β: 3.75; 95% CI: 0.53, 6.97) and were 3.55 times (95% CI: 1.78, 7.05) more likely to be overweight/obese than those in FC. Adiposity measures in PCP children did not differ from those in FC. PCN children were reported to have more screen time and greater fast-food intake. Children in PCN tended to have higher adiposity measures. Greater engagement of non-parental caregivers should be considered in interventions targeting child obesity.Peer reviewe