Growth method for chalcongenide phase-change nanostructures

A method for growth of an alloy for use in a nanostructure, to provide a resulting nanostructure compound including at least one of Ge.sub.xTe.sub.y, In.sub.xSb.sub.y, In.sub.xSe.sub.y, Sb.sub.xTe.sub.y, Ga.sub.xSb.sub.y, Ge.sub.xSb.sub.y,Te.sub.z, In.sub.xSb.sub.yTe.sub.z, Ga.sub.xSe.sub.yTe.sub.z, Sn.sub.xSb.sub.yTe.sub.z, In.sub.xSb.sub.yGe.sub.z, Ge.sub.wSn.sub.xSb.sub.yTe.sub.z, Ge.sub.wSb.sub.xSe.sub.yTe.sub.z, and Te.sub.wGe.sub.xSb.sub.yS.sub.z, where w, x, y and z are numbers consistent with oxidization states (2, 3, 4, 5, 6) of the corresponding elements. The melt temperatures for some of the resulting compounds are in a range 330-420.degree. C., or even lower with some compounds

Extraction of contact resistance in carbon nanofiber via interconnects with varying lengths

A method to extract the contact resistance and bulk resistivity of vertically grown carbon nanofibers (CNFs) or similar one-dimensional nanostructures is described. Using a silicon-compatible process to fabricate a terrace test structure needed for the CNF length variation, the contact resistance is extracted by measuring in situ the resistances of individual CNFs with different lengths and within a small range of diameters using a nanoprober inside a scanning electron microscope. Accurate determination of contact resistances for various combinations of catalysts and underlayer metals can lead to eventual optimization of materials’ growth and device fabrication processes for CNF via interconnects

Study of Phonon Modes in Germanium Nanowires

The observation of pure phonon confinement effect in germanium nanowires is limited due to the illumination sensitivity of Raman spectra. In this paper we measured Raman spectra for different size germanium nanowires with different excitation laser powers and wavelengths. By eliminating the local heating effect, the phonon confinement effect for small size nanowires was clearly identified. We have also fitted the Raman feature changes to estimate the size distribution of nanowires for the first time.Comment: 11 pages,15 figure

Q-YOLO: Efficient Inference for Real-time Object Detection

Real-time object detection plays a vital role in various computer vision applications. However, deploying real-time object detectors on resource-constrained platforms poses challenges due to high computational and memory requirements. This paper describes a low-bit quantization method to build a highly efficient one-stage detector, dubbed as Q-YOLO, which can effectively address the performance degradation problem caused by activation distribution imbalance in traditional quantized YOLO models. Q-YOLO introduces a fully end-to-end Post-Training Quantization (PTQ) pipeline with a well-designed Unilateral Histogram-based (UH) activation quantization scheme, which determines the maximum truncation values through histogram analysis by minimizing the Mean Squared Error (MSE) quantization errors. Extensive experiments on the COCO dataset demonstrate the effectiveness of Q-YOLO, outperforming other PTQ methods while achieving a more favorable balance between accuracy and computational cost. This research contributes to advancing the efficient deployment of object detection models on resource-limited edge devices, enabling real-time detection with reduced computational and memory overhead

Identifying Users' Gender via Social Representations

Gender prediction has evoked great research interests due to its potential applications like targeted advertisement and personalized search. Most of existing studies rely on the content texts. However, the text information is hard to access. This makes it difficult to extract text features. In this paper, we propose a novel framework which only involves the users' ids for gender prediction. The key idea is to represent users in the embedding connection space. We present two strategies to modify the word embedding technique for user embedding. The first is to sequentialize users' ids to get the order of social context. The second is to embed users into a large-sized sliding window of contexts. We conduct extensive experiments on two real data sets from Sina Weibo. Results show that our method is significantly better than the state-of-the-art graph embedding baselines. Its accuracy also outperforms that of the content based approaches

Inequality of Opportunity in Health Care in China: Suggestion on the Construction of the Urban-Rural Integrated Medical Insurance System

This paper investigates the urban-rural inequality of opportunity in health care in China based on the theory of the EOp of Roemer (1998). Following the compensation principle proposed by Fleurbaey and Schokkaert (2011), this paper decomposes the fairness gap in the urban-rural health care utilization. The results shows that the ratios of the fairness gap to are 1.167 during 1997-2000 and 1.744 during 2004-2006. It implies that the degree of the essential inequity is underestimated. Meanwhile, upgrading the urban-rural reimbursement ratios is probably not sufficient to eliminate the inequality of opportunity in health care utilization between urban and rural residents. Under background of urban-rural dualistic social structure and the widening of urban-rural income gap, the pro-disadvantage policies will be more effective to promote the equality of opportunity in health car

Will Low-Income Populations Love Spicy Foods More? Accounting for Tastes

Based on the Theory of Rational Addiction (TORA), this paper identifies the correlation between income and the preference for spicy foods by analysing the China Health and Nutrition Survey (CHNS) data. The results show that compare with high-income residents of same area, the low-income residents prefer to spicy foods in China. The regression results of IV and Lewbel IV all support it. According to the result, the channel of health behaviours and health awareness are possible causal channels for the negative correlation between income and the preference for spicy foods, rather than health capital stock and food selection

Will Low-Income Populations Love Spicy Foods More? Accounting for Tastes

Based on the Theory of Rational Addiction (TORA), this paper identifies the correlation between income and the preference for spicy foods by analysing the China Health and Nutrition Survey (CHNS) data. The results show that compare with high-income residents of same area, the low-income residents prefer to spicy foods in China. The regression results of IV and Lewbel IV all support it. According to the result, the channel of health behaviours and health awareness are possible causal channels for the negative correlation between income and the preference for spicy foods, rather than health capital stock and food selection