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Background Examine the association of household financial indebtedness with depressive symptoms in old age, and investigate whether social network and support anticipation moderate the association. Methods Data were obtained from Sample Survey on Vulnerable Populations from Poor Families in Urban/Rural China (2018), with a sample of 5 934 older adults included. Center for Epidemiologic Studies Depression Scales was applied to measure depressive symptoms. Household indebtedness was measured in several ways, including whether the household was indebted, the amount of debts, and types of debts. We used the 6-item Lubben Social Network Scale to measure individual's social network. Socio-demographic, socioeconomic status and physical health variables were included as covariates. Results Household indebtedness, in form of being indebted and increased amount of debts, was associated with greater depressive symptoms in the Chinese elderly. The association of indebtedness and depressive symptoms may be driven by consumption and emergency debts. The moderating roles of social network and anticipation of support in the association of household indebtedness and depressive symptoms were found. Among those with household debts, older adults with larger size of social network and/or higher anticipation of being supported in the future reported with less symptoms of depressed. Limitations Due to a lack of information on the duration and debtor of household debt, we were not able to present a precise estimate for the exact impact of household indebtedness on mental health of elderly. Conclusion Familial financial strain was associated with aging mental well-being, increased social networks and social protections benefit aging health.

Benazir Income Support Program (BISP) is one of social protection programs providing unconditional financial assistance to poor women. The present study was conducted to explore the role of BISP in empowering women. This quantitative research was conducted in two districts of Punjab randomly selected out of 36 using face-to-face interviews with a sample size of 160 women beneficiaries of BISP. Research findings show that the majority of beneficiaries (78.8%) were married, with rural background (88%). A huge number (80%) of beneficiaries were illiterate. Similarly, overwhelming majority (81.9%) of respondents has labor as source of income. Most of the respondents were strongly agree (65%) and agree (95%) that the assistance should be more than Rs.5000/month or Rs.10000/month. Similarly, 69.4% and 71.3% of respondents agreed that female adults should take household decision and children should attend school regardless of gender. The government should provide appropriate assistance allowance for needy families especially for the empowerment of women. Moreover, the government should also launch massive programs to maximize girls' education with motive to empower women.

Cutting chatter is violent self-excited vibration between tool and work piece, which will seriously degrade the machining surface quality and health of machine tool. Online monitoring of chatter phenomenon can feed back the control system to adjust processing parameters dynamically for chatter suppression. In this article, a short-time difference spectrum analysis (STDSA) is proposed for early chatter identification, which can recognize chatter frequency and track its amplitude from low SNR vibration signal at early stage. The method is verified by both simulated vibration signals and machining vibration signals collected from an axle lathe. A comparison between classic variational mode decomposition (VMD) and STDSA is given to illustrate its performance. The results indicate that the method is robust to noise and has a little warning time delay, which makes it suitable for the online monitoring of cutting chatter in an industrial production environment.

Background Hearing loss is highly prevalent and associated with reduced well-being in older adults. But little is known about the role of social factors in the association of hearing difficulty and its health consequences. This study aims to examine the association between self-reported hearing loss and health-related quality of life (HRQoL, consisted of physical and mental component summary, PCS and MCS), and to investigate whether social engagement mediates this association. Method Data on 4035 older adults aged 60 years or above from a cross-sectional nationally representative database in China were obtained to address this study. HRQoL was measured by the Short Form 12 Health Survey (SF-12). Hearing loss was defined by a dichotomized measure of self-reported hearing difficulty, which has been proved to be sensitive and displayed moderate associations with audiometric assessment in elderly population. Social engagement was measured by the Index of Social Engagement Scale. Bootstrap test was applied to test for the significance of the mediating role of social engagement. Results Self-reported hearing loss was found negatively associated with HRQoL in older adults, and hearing loss was much more related to reduced mental well-being. Social engagement played a partial mediating role in the association of hearing loss and HRQoL. Social engagement account for 4.14% of the variance in the change of PCS scores and 13.72% for MCS, respectively. Conclusion The study lends support to the hypothesis that hearing loss is associated with aging well beings, and the use of hearing aid or proper social engagement intervention may improve the quality of life among the elderly.

Background Compression and expansion of morbidity are two critical hypotheses to analyze the relationship among morbidity, disability, and mortality. This study aims to analyze the global distribution of the compression and expansion of morbidity and to investigate its relationship with income inequality. Methods Data was from the Global Burden of Disease Study 2016 and Standardized World Income Inequality Database, version 8.2. Seven types of health changes were defined. Income inequality was measured with Gini coefficient index. Binary logistic regression was used to analyze the association of income inequality with the compression and expansion of morbidity. Results All the seven types of the compression and expansion of morbidity exist in the world, despite their uneven distribution. The relative expansion of morbidity with increased or constant life expectancy (Type 6) was the most popular type occurring to more than half of populations in the last quarter of century, which was followed by the relative compression of morbidity with increased or constant LE (Type 3, 30.71%). The income inequality was significantly associated with the health changes, which still held after controlling a variety of confounders and in robustness tests. Those societies with lower income inequality were more likely to incur Type 3. Conclusions It is necessary to distinguish the positive and negative changes in life expectancy when examing the compression and expansion of morbidity. The increasing popularity of Type 6 implies higher needs for health and social care. Measures to reduce income inequality or mitigate its negative influence on health changes might promote the occurrence of Type 3.

Background The inequity of healthcare utilization in rural China is serious, and the urban-rural segmentation of the medical insurance system intensifies this problem. To guarantee that the rural population enjoys the same medical insurance benefits, China began to establish Urban and Rural Resident Basic Medical Insurance (URRBMI) nationwide in 2016. Against this backdrop, this paper aims to compare the healthcare utilization inequity between URRBMI and New Cooperative Medical Schemes (NCMS) and to analyze whether the inequity is reduced under URRBMI in rural China. Methods Using the data from a national representative survey, the China Health and Retirement Longitudinal Study (CHARLS), which was conducted in 2015, a binary logistic regression model was applied to analyze the influence of income on healthcare utilization, and the decomposition of the concentration index was adopted to compare the Horizontal inequity index (HI index) of healthcare utilization among the individuals insured by URRBMI and NCMS. Results There is no statistically significant difference in healthcare utilization between URRBMI and NCMS, but in outpatient utilization, there are significant differences among different income groups in NCMS; high-income groups utilize more outpatient care. The Horizontal inequity indexes (HI indexes) in outpatient utilization for individuals insured by URRBMI and NCMS are 0.024 and 0.012, respectively, indicating a pro-rich inequity. Meanwhile, the HI indexes in inpatient utilization under the two groups are − 0.043 and − 0.028, respectively, meaning a pro-poor inequity. For both the outpatient and inpatient care, the inequity degree of URRBMI is larger than that of NCMS. Conclusions This paper shows that inequity still exists in rural areas after the integration of urban-rural medical insurance schemes, and there is still a certain gap between the actual and the expected goal of URRBMI. Specifically, compared to NCMS, the pro-rich inequity in outpatient care and the pro-poor inequity in inpatient care are more serious in URRBMI. More chronic diseases should be covered and moral hazard should be avoided in URRBMI. For the vulnerable groups, special policies such as reducing the deductible and covering these groups with catastrophic medical insurance could be considered.

In visual tracking, usually only a small number of samples are labeled, and most existing deep learning based trackers ignore abundant unlabeled samples that could provide additional information for deep trackers to boost their tracking performance. An intuitive way to explain unlabeled data is to incorporate manifold regularization into the common classification loss functions, but the high computational cost may prohibit those deep trackers from practical applications. To overcome this issue, we propose a two-stage approach to a deep tracker that takes into account both labeled and unlabeled samples. The annotation of unlabeled samples is propagated from its labeled neighbors first by exploring the manifold space that these samples are assumed to lie in. Then, we refine it by training a deep convolutional neural network using both labeled and unlabeled data in a supervised manner. Online visual tracking is further carried out under the framework of particle filters with the presented manifold regularized deep model being updated every few frames. Experimental results on different tracking datasets demonstrate that our tracker outperforms most existing tracking approaches. The source code and results are available at: https://github.com/shenjianbing/MRCNNTracking .

The study of aerated irrigation (AI) in conjunction with different irrigation levels on economic and environmental effects has important scientific significance for the selection of optimal irrigation and reasonable greenhouse management practices. In this paper, a two-year experiment was conducted to investigate tomato yield, water use efficiency (WUE), CO2, N2O, CH4 emissions, net global warming potential (NGWP), and carbon footprint (CF) differences for a greenhouse tomato system in Northwestern China in 2016 and 2017. Based on the amount of irrigation needed to provide an adequate water supply (W), 60%W, 80%W and 100%W were set as the three irrigation levels, with two aeration regimes (aeration and control), totaling six treatments. Compared to the control, AI significantly increased tomato yield by 32.0%, WUE by 32.0% and CF by 24.0% on average (p 0.05). With respect to the treatment of 100%W, 80%W over the two years had no obvious effect on tomato yield, WUE and CF (p>0.05), while 60%W reduced yield by 23.4% and CF by 32.6% but increased WUE by 35.1% significantly (p 0.05). The main inputs in this arid and semi-arid region were electricity for irrigation and fertilizers, contributing 87.9%–92.9% of the total impact. Overall, the treatment of aerated full irrigation was suitable for crop production, water saving and carbon sequestration with WUE of 24.05 (in 2016) and 19.95 kg m−3 (in 2017), a net greenhouse gas intensity of 0.103 (in 2016) and 0.086 (in 2017) t t−1, and with a carbon footprint per tomato yield of 0.350 (in 2016) and 0.426 (in 2017) kg CO2-eq kg−1.

This study evaluated the association between the special subsidy policy and the mental health of loss/disability-of-single-child parents (LCPs/DCPs) in China and found that accepting the special subsidy is inversely related to the mental health of LCPs and DCPs. In addition, accepting the subsidy is more inversely related to the mental health of LCPs than DCPs, of rural parents than urban parents, of male parents than female parents, and of loss/disability-of-single-son parents than loss/disability-of-single-daughter parents. According to taboo trade-off theory, we proposed several explanations for the finding and put forward some policy recommendations.

Neonatal cholestasis disease (NCD) is a complex and easily mis-diagnosed condition. We analyzed microbiota community structure in feces and measured short-chain fatty acids, bile acids (BAs) and liver function of 12 healthy, 13 NCD, and 13 treated infants after diagnosis. Based on 16S rRNA gene amplicon sequencing and gas-chromatographic-mass-spectrometric analysis of secondary BAs, we identified microbial genera and metabolites that associate with abnormal bile secretion. Streptococcus gallolyticus and Parabacteroides distasonis, and Lactobacillus gasseri had higher relative abundance in healthy and NCD infants respectively. Compared to NCD patients, healthy infants had higher LCA, CDCA and GCDCA fecal concentrations. The three microbial species and three secondary bile acids were selected as potential non-invasive combined biomarkers to diagnose NCD. We propose that microbiota-metabolite combined biomarkers could be used for diagnosis of NCD, and this may contribute to improved early clinical diagnosis of NCD in the future.

Angle beam wedge transducers are widely used in nonlinear Rayleigh wave experiments as they can generate Rayleigh wave easily and produce high intensity nonlinear waves for detection. When such a transducer is used, the spurious harmonics (source nonlinearity) and wave diffraction may occur and will affect the measurement results, so it is essential to fully understand its acoustic nature. This paper experimentally investigates the nonlinear Rayleigh wave beam fields generated and received by angle beam wedge transducers, in which the theoretical predictions are based on the acoustic model developed previously for angle beam wedge transducers [S. Zhang, et al., Wave Motion, 67, 141–159, (2016)]. The source of the spurious harmonics is fully characterized by scrutinizing the nonlinear Rayleigh wave behavior in various materials with different driving voltages. Furthermore, it is shown that the attenuation coefficients for both fundamental and second harmonic Rayleigh waves can be extracted by comparing the measurements with the predictions when the experiments are conducted at many locations along the propagation path. A technique is developed to evaluate the material nonlinearity by making appropriate corrections for source nonlinearity, diffraction and attenuation. The nonlinear parameters of three aluminum alloy specimens – Al 2024, Al 6061 and Al 7075 – are measured, and the results indicate that the measurement results can be significantly improved using the proposed method.

Coal slime, a low-calorific-value fuel, is a by-product during coal washing, which can be disposed in quantity and fully utilized in circulating fluidized bed (CFB) boiler. This research paid attention to the ignition and combustion behaviors of single coal slime particles, which affect the normal combustion, operation stability and burning efficiency in circulating fluidized bed boiler. The ignition and combustion behaviors including ignition mechanism, ignition delay, ignition temperature and combustion process of single coal slime particles in a vertical heating tube furnace in CO2/O2 atmosphere were researched under different operation condition parameters, for different gas temperatures (Tg = 923, 1073, and 1173 K), gas flow rates (V = 0–20 L/min), and oxygen mole concentrations (O2% = 5–80%). Coal slime particle had three ignition mechanisms in CO2/O2 atmosphere, namely, homogeneous ignition of volatiles at the windward and leeside of particle, heterogeneous ignition of char and heterogeneous ignition of coal. Only heterogeneous ignition of char and homogeneous ignition of volatiles at the windward of particle occurred in quiescent atmosphere. However, homogeneous ignition region decreased while heterogeneous ignition region increased gradually with the increasing flow rates in the oxygen concentration-gas temperature plane. Different ignition mechanisms were accompanied with various combustion processes. The combustion processes corresponding to heterogeneous ignition of char changed from flameless combustion to flaming combustion as oxygen concentration increased. Moreover, the critical oxygen concentration elevated from 30% to 50% with the increasing flow rate. The ignition temperatures and ignition delays decreased with the increasing gas temperature and oxygen concentration. As the flow rate increased, the trends became more obvious in medium-to-low oxygen concentrations. Compared with the ignition characteristics and combustion processes of coal slime particles in N2/O2 atmosphere, those in CO2/O2 atmosphere were suppressed due to the higher mole heat capacity and lower diffusion rate of oxygen molecule in CO2.

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

Two-dimensional (2D) hybrid perovskites exhibiting broadband light emission are attractive as down-converting phosphors in white light-emitting diodes (WLEDs). Despite active exploration of new members of this family of materials, fine-tuning of their emission through structural variation for realizing high color-rendering white light remains largely untapped. Here we report a series of (100)-oriented 2D perovskites whose structures are templated by the organic cations. By controlling the tilting of the inorganic octahedra, we were able to shift the broadband emission from blue to white. A photophysical study further suggests that the coexistence of self-trapped excitons and free excitons contributes to a double-peak broad emission, covering the entire visible spectrum. Using the broad-emitting perovskites as down-converting phosphors, we fabricated WLEDs with white-light emission having a correlated color temperature (CCT) of 6600 K and a high color rendering index (CRI, Ra) of 86. MOE (Min. of Education, S’pore)

In this work, three novel acene-based organic semiconductors, including 2,7-bis(trimethylstannyl)naphtho[2,1-b:6,5-b′]dithiophene (TPA-NADT-TPA), 4,4′-(anthracene-2,6-diyl)bis(N,N-bis(4-methoxyphenyl)aniline) (TPA-ANR-TPA) and N2,N2,N6,N6-tetrakis(4-methoxyphenyl)anthracene-2,6-diamine (DPA-ANR-DPA), are designed and synthesized for use in organic light-emitting diodes (OLEDs) and perovskite solar cells (PSCs). In OLEDs, devices based on TPA-NADT-TPA, TPA-ANR-TPA and DPA-ANR-DPA showed pure blue, blue green, and green emission, respectively. Also, the maximum brightness of the devices with a turn-on voltage of 3.8 V reached 8682 cd m−2 for TPA-NADT-TPA, 11 180 cd m−2 for TPA-ANR-TPA, and 18 600 cd m−2 for DPA-ANR-DPA. These new materials are also employed as hole transporting materials (HTMs) in inverted PSCs, where they were used without additives. The inverted devices based on these HTMs achieved an overall efficiency of 10.27% for TPA-NADT-TPA, 7.54% for TPA-ANR-TPA, and 6.05% for DPA-ANR-DPA under identical conditions (AM 1.5G and 100 mW cm−2). While the PSCs with TPA-NADT-TPA as the HTM achieved the highest efficiency, the DPA-ANR-DPA-based OLED devices showed the brightest emission and efficiency. Based on the obtained promising performance, it is clear that this molecular design presents a new research strategy to develop materials that can be used in multiple types of devices. MOE (Min. of Education, S’pore)

Solution-processed solar cells are promising as low-cost alternatives to the first-generation solar cells. Combining two solution-processed devices in a tandem structure can potentially achieve a high efficiency while maintaining a relatively low fabrication cost. Here we present a tandem combining solution-processed perovskite and CZTSSe solar cells in a reflective configuration. The perovskite cell with a large bandgap acts as a spectral filter reflecting the sub-bandgap photons to a low bandgap CZTSSe cell. A total efficiency of 16.1% has been obtained in a four-terminal measurement, higher than each of the sub-cells. These results show the potential of solution-processed tandem solar cell with perovskite and kesterite in achieving a high efficiency with a low fabrication cost.

An ultrasonic synthetic aperture focusing technique (SAFT) using a root mean square (RMS) velocity model is proposed for pulse-echo immersion testing to improve the computational efficiency. Considering the immersion ultrasonic testing of a steel block as an example, three kinds of imaging were studied (B-Scan, SAFT imaging based on ray tracing technology and RMS velocity). The experimental results show that two kinds of SAFT imaging have almost the same imaging performance, while the efficiency of RMS velocity SAFT imaging is almost 25 times greater than the SAFT based on Snell’s law.

A method based on the one-dimensional local binary pattern (1-D LBP) algorithm to extract features of ultrasonic defect signals and perform multi-class defect classification was proposed. The ultrasonic defect echo signals were first decomposed into wavelet coefficients by the wavelet packet decomposition. The 1-D LBP algorithm was employed to extract LBP features of components at low and high frequencies, respectively. Subsequently, these LBP statistical feature sets were regarded as feature vectors of defect classification. Weld defects were then classified automatically by using the radial basis function support vector machine. Defects of slag inclusion, porosity and incomplete penetration in a steel plate butt weld were used for experiments and feature extraction and defect classification were performed. The results show that the class separability of 1-D LBP features used for defect classification is superior to that of the traditional features. Moreover, the accuracy of defect classification...

The pulse-echo nonlinear acoustic wave fields generated by focused transducers are calculated numerically and verified experimentally. Simulation results show that in the reflection direction, phase differences between newly generated second harmonic and reflected waves are about π/2, regardless of the rigid and stress-free boundaries; thus, the total second harmonic wave will neither be strongly enhanced nor be cancelled. Experiments are conducted with a focused transducer working in pulse-echo mode and the measured amplitudes of nonlinear waves reflected after water-air and water-aluminum/steel interfaces agree with the simulated results. This work helps advance applications using pulse-echo nonlinear acoustics.

Tandem solar cells combining a wide bandgap, efficient perovskite absorber with a low bandgap photovoltaic module, such as a c-Si cell, can potentially achieve a high theoretical efficiency of over 30%. Instead of using the conventional parallel stacking tandem, we report here a reflective tandem configuration, with the perovskite solar cell acting as the spectral filter that absorbs high energy photons, while sub-bandgap photons are reflected to a Si sub-cell using a highly reflective back metal electrode. The perovskite solar cell exhibits a high reflectance of over 60% in the near infrared spectral region, which allows the subsequent silicon cell to absorb photons in this region, resulting in a high current density of 13.03 mA cm−2. In such a tandem configuration, we achieved a combined efficiency of 23.1% using a four-terminal measurement. This result demonstrates the promise of employing perovskite solar cells in a reflective tandem for a high efficiency solar energy conversion system, with an efficiency of up to 30%.

Background In 2016, the tiered healthcare model featuring “specialists + general practitioners + health managers” in Xiamen was recognized by the Medical Reform Office of State Council and was promoted as a model to replace hospital-centric care with community-based care. This study evaluated the impact of the Xiamen's tiered healthcare system reform on health outcomes and healthcare spending among chronic disease patients. Methods Data were derived from Xiamen's electronic health record (EHR) and medical claims systems. The sample included 154,651 individuals with hypertension and 50,722 individuals with diabetes from Xiamen between 2012 and 2016. The dependent variables included rates of disease under control and total treatment costs. Patients were grouped by the types of chronic disease management: precision management, regular management, or without management. Kaplan-Meier, Cox survival analysis and PSM + DID method (Propensity score matching and difference-in-difference method) were used to compare the management outcomes by group. Findings The precision management group showed better clinical quality performance than the regular management group. Under-control disease rates in the precision management group showed a continuous improvement trend, while the regular management group showed a ceiling effect after ten months. Under-control rates in the precision management group increased over 40% for hypertension and over 30% for diabetes, higher than that increases found in the regular management group. Reform was also associated with consistent reductions in annual per capita total treatment costs across groups. The cost-savings in the precision management group between 2014 and 2016 was 381 Chinese yuan (CNY) for hypertension and 1117 CNY for diabetes, compared with the group without management. Interpretation The results in this study demonstrated the associations between tiered healthcare system reform and better clinical quality performance and improved treatment cost-saving. Developing methods to promote the policy and increase implementation are also important aspects of healthcare reform.

PERC solar cell passivated on the backside with AlOx and SiNx was introduced to construct the perovskite/silicon four-terminal tandem solar cell, because of its outstanding spectral response at the long wavelength region and much lower cost than SHJ and IBC. Different from the vast majority of the related reports, which were focused on the improvement of perovskite top cell, the silicon bottom cell was optimized here to promote the tandem efficiency. The central wavelength of antireflection was adjusted to further reduce the reflectance and enhance the spectral response of PERC cell in long wavelengths, in order to make the most of long-wavelength light transmitted through the perovskite top cell. Along with the increase of central wavelength, the external quantum efficiency of PERC cell at near-infrared wavelengths increases resulting in better short circuit current density and photoelectric conversion efficiency when filtered by the perovskite cell. A tandem efficiency gain of 0.07% (abs.) has been achieved. This report provides a facile way to improve the efficiency of perovskite/silicon four-terminal tandem solar cell based on the optimization of long-wavelength spectral response.

Efficient and accurate nondestructive testing of surface or sub-surface flaws is essential for metal components. This study focuses on the high-quality image reconstruction of these flaws. An imaging detection method is introduced which combines the leaky Rayleigh waves testing and the synthetic aperture focusing technique (SAFT) with an immersion pulse-echo scanning. The principal component analysis (PCA) is used to reduce the noise of the leaky Rayleigh waves, and then the imaging is obtained using the SAFT algorithm. The experimental results show that the PCA-SAFT imaging method can reduce structural noise and imaging artifacts comparing with the B-scan imaging method. The lateral resolution of defects is improved and the mean error of defects sizing can be reduced by 48.81%. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the ultrasonic image are increased by 6.95 dB and 4.20 dB respectively. The proposed method can be a new choice for effective evaluating the surface quality of key components.

We propose a method that obtains a discriminative visual dictionary and a nonlinear classifier for visual tracking tasks in a sparse coding manner based on the globally linear approximation for a nonlinear learning theory. Traditional discriminative tracking methods based on sparse representation learn a dictionary in an unsupervised way and then train a classifier, which may not generate both descriptive and discriminative models for targets by treating dictionary learning and classifier learning separately. In contrast, the proposed tracking approach can construct a dictionary that fully reflects the intrinsic manifold structure of visual data and introduces more discriminative ability in a unified learning framework. Finally, an iterative optimization approach, which computes the optimal dictionary, the associated sparse coding, and a classifier, is introduced. Experiments on two benchmarks show that our tracker achieves a better performance compared with some popular tracking algorithms.

We describe a new approach for preparing organic-inorganic perovskite solar cells for electron beam-induced current (EBIC) measurements in plan-view geometry. This method substantially reduces sample preparation artefacts, provides good electrical contact and keeps the preparation steps as close as possible to those for real devices. Our EBIC images were acquired simultaneously with annular dark-field scanning transmission electron microscopy images using a home-made highly sensitive EBIC amplifier. High-angle annular dark-field images and energy dispersive X-ray maps were recorded from the same area immediately afterwards. This allowed the EBIC contrast to be correlated with regions containing N and a deficiency of O. The EBIC contrast was also found to be similar to secondary electron contrast recorded with a scanning electron microscope. By identifying the generation and absorption electron processes, we determine that EBIC cannot be separated from the secondary electron and absorbed currents. This means that careful analysis needs to be performed before conclusions can be made on the origin of the current measured across p-n or p-i-n junctions. Nanyang Technological University We are grateful to Thomas Duden for the fabrication and operation of the amplifier during the EBIC experiments. M.D. acknowledges fi- nancial support from Nanyang Technological University start-up grant M4081924

Background Despite decades of study, debates exist surrounding the relationship between education and functional health status transition among elderly populations. This study aims to add evidence to the debates using China as a case study. Specifically, this study analysed the association of education with functional health status transition and then the mechanism behind that association using the budget constraint relax hypothesis and the efficiency improvement hypothesis among elderly population in China. Methods Based on data from the Chinese Longitudinal Healthy Longevity Surveys from 2008 and 2011, this study focussed on adults aged 65 years and above, with a final sample size of 12,112. A generalised structural equation model was used to analyse the relationship between education and functional health status transition and the mechanism behind that association. Results During the three examined years, among elderly adults who were nondisabled at baseline, 53.1% stayed nondisabled, 14.6% became disabled, and 32.3% died; among those disabled in 2008, 8.1% recovered, 21.6% stayed disabled, and 70.3% died. Compared with older adults without any education, those who had attended primary schools had both lower mortality and disability, whereas those who had attended high schools and above only had a lower mortality rate. The budget constraint relax hypothesis and the efficiency improvement hypothesis explained the majority of the relationship between education and transition from non-disability to death, but hardly explained the transition from non-disability to disability. Furthermore, once a person was disabled, education had no significant relationship with functional ability recovery or mortality. Conclusions Attending primary school seems to provide the highest benefit to functional health status transition among older and nondisabled persons in China. Those who attended high schools and above are expected to live a longer life with disability. The mechanism between education and the onset of disability needs more discussion.

Sparse coding methods have achieved great success in visual tracking, and we present a strong classifier and structural local sparse descriptors for robust visual tracking. Since the summary features considering the sparse codes are sensitive to occlusion and other interfering factors, we extract local sparse descriptors from a fraction of all patches by performing a pooling operation. The collection of local sparse descriptors is combined into a boosting-based strong classifier for robust visual tracking using a discriminative appearance model. Furthermore, a structural reconstruction error based weight computation method is proposed to adjust the classification score of each candidate for more precise tracking results. To handle appearance changes during tracking, we present an occlusion-aware template update scheme. Comprehensive experimental comparisons with the state-of-the-art algorithms demonstrated the better performance of the proposed method.

An evaluation model based on the multi-scale ultrasonic attenuation coefficient was developed to control both systematic error and random error. AISI 304 stainless steel was used to validate the presented model. Wavelet transformation was used to obtain the variation of ultrasonic signal over time and scale. Particle swarm optimization was utilized to correlate the coefficient with grain sizes. The model shows the attenuation of all scales increased with the grain size, and ultrasound attenuates faster on smaller scales. Compared with the ultrasonic velocity method and the traditional attenuation method, the proposed method has less systematic error and random error.

This article explores the effects of SiO2/Al2O3 ratios (S/A) on sintering characteristics and provides guidance for alleviating ash depositions in a large-scale circulation fluidized bed. Five synthetic coal ash (SCA) samples with different S/As were treated in a muffle furnace for 12 h at different temperatures (from 773 K to 1373 K, in 100 K intervals). The morphological and chemical results of the volume shrinkage ratio (VSR), thermal deformation analysis by dilatometer (DIL), scanning electron microscope (SEM), X-ray photoelectron spectrometer (XPS), and X-ray diffraction (XRD) were combined to describe the sintering characteristics of different samples. The results showed that the sintering procedure mainly occurred in the third sintering stage when the temperature was over 1273 K, accompanied with significant decreases in the VSR curve. Excess SiO2 (S/A = 4.5) resulted in a porous structure while excess Al2O3 (S/A = 0.5) brought out large aggregations. The other three samples (S/A = 1.5, 2.5, 3.5) are made up of an amorphous compacted structure and are composed of low fusion temperature materials (e.g., augite and wadsleysite.). Sintering temperatures first dramatically decrease to a low level and then gradually rise to a high level as S/A increases, suggesting that Al2O3-enriched additives are more effective than SiO2enriched additives in alleviating depositions.

Surface roughness of a sample has a great effect on the calculated grain size when measurements are based on ultrasonic attenuation. Combining modified transmission and reflection coefficients at the rough interface with a Multi-Gaussian beam model of the transducer, a comprehensive correction scheme for the attenuation coefficient is developed. An approximate inverse model of the calculated attenuation, based on Weaver's diffuse scattering theory, is established to evaluate grain size in polycrystals. The experimental results showed that for samples with varying surface roughness and matching microstructures, the fluctuation of evaluated average grain size was ±1.17μm. For polished samples with different microstructures, the relative errors to optical microscopy were no more than ±3.61%. The presented method provides an effective nondestructive tool for evaluating the grain size in metals with rough surfaces.

Hydraulic turbine runner has a complex structure, and traditional location methods can't meet its requirement. This paper describes a source location of cracks in turbine blades by combining kernel independent component analysis (KICA) with wavelet neural network (WNN). The research shows that the location accuracy of WNN combined with KICA feature extraction is the best comparing with the results of WNN and back propagation neural network (BPNN). The method decreases the dimension of input parameters and improves the accuracy of location as well.

Porosity is an important characteristic of porous material, which affects mechanical and material properties. In order to solve the problem that the large distribution range of pore size of porous materials leads to the large detection errors of porosity, the non-linear ultrasonic testing technique is applied. A graphite composite was used as the experimental object in the study. As the accuracy of porosity is directly related with feature extraction, the dynamic wavelet fingerprint (DWFP) technology was utilized to extract the feature parameter of the ultrasonic signals. The effects of the wavelet function, scale factor, and white slice ratio on the extraction of the nonlinear feature are discussed. The SEM photos were conducted using gray value to identify the aperture. The relationship between pore diameter and detection accuracy was studied. Its results show that the DWFP technology could identify the second harmonic component well, and the extracted nonlinear feature could be used for the quantitative trait of porosity. The larger the proportion of the small diameter holes and the smaller the aperture distribution range was, the smaller the error was. This preliminary research aimed to improve the nondestructive testing accuracy of porosity and it is beneficial to the application of porous material in the manufacturing field.

Cu2ZnSnS4 (CZTS) can be potentially used as a counter electrode in dye-sensitized solar cells (DSSCs) because of its excellent catalytic performance. In this paper, stoichiometric CZTS was prepared and was applied in DSSCs. The DSSCs with CZTS counter electrodes showed relatively low photoelectric conversion efficiency (PCE) of 4.77%. However, the PCE was clearly enhanced by adding graphene to CZTS and a maximum PCE of 7.81% was achieved, which was superior to the value of 6.66% shown by the Pt counterpart. The influence of graphene that results in the improvement of the performance of the DSSCs is discussed in detail.

In discriminative tracking algorithms, the accuracy of classifier which relies heavily on the selection of training samples can directly influence the performance of visual tracking. Motivated by above, a tracking algorithm is presented based on regularized approximate residual weighted subsampling in the paper. Through the subsampling procedure, the corrupted samples which exert adverse impacts on the estimated classifier are ensured to be selected infrequently, thus making the classifier trained with the selected sample subset more robust to the noise caused by object appearance variations. Furthermore, an effective model updating strategy is adopted to enhance the flexibility of the tracker to the changes. Compared with some state-of-the-art trackers, our tracking algorithm performs better on a typical benchmark.

Feature pooling in a majority of sparse coding-based tracking algorithms computes final feature vectors only by low-order statistics or extreme responses of sparse codes. The high-order statistics and the correlations between responses to different dictionary items are neglected. We present a more generalized feature pooling method for visual tracking by utilizing the probabilistic function to model the statistical distribution of sparse codes. Since immediate matching between two distributions usually requires high computational costs, we introduce the Fisher vector to derive a more compact and discriminative representation for sparse codes of the visual target. We encode target patches by local coordinate coding, utilize Gaussian mixture model to compute Fisher vectors, and finally train semi-supervised linear kernel classifiers for visual tracking. In order to handle the drifting problem during the tracking process, these classifiers are updated online with current tracking results. The experimental results on two challenging tracking benchmarks demonstrate that the proposed approach achieves a better performance than the state-of-the-art tracking algorithms.

Due to unavoidable appearance variations caused by occlusion, deformation, and other factors, classifiers for visual tracking are nonlinear as a necessity. Building on the theory of globally linear approximations to nonlinear functions, we introduce an elegant method that jointly learns a nonlinear classifier and a visual dictionary for tracking objects in a semi-supervised sparse coding fashion. This establishes an obvious distinction from conventional sparse coding based discriminative tracking algorithms that usually maintain two-stage learning strategies, i.e., learning a dictionary in an unsupervised way then followed by training a classifier. However, the treating dictionary learning and classifier training as separate stages may not produce both descriptive and discriminative models for objects. By contrast, our method is capable of constructing a dictionary that not only fully reflects the intrinsic manifold structure of the data, but also possesses discriminative power. This paper presents an optimization method to obtain such an optimal dictionary, associated sparse coding, and a classifier in an iterative process. Our experiments on a benchmark show our tracker attains outstanding performance compared with the state-of-the-art algorithms.

Ultrasonic technique is very promising for non destructive inspection. In this paper, a method is presented on automatic ultrasonic inspection of defects in a propeller-blade without computer aided design (CAD) models. The 3D surface data are obtained by ultrasonic measurement, and then the inspection path is planned after the CAD model has been reconstructed. A C-scan image is obtained in real-time ultrasonic automatic inspection. Thereafter, defective area and sound area are separated through binarisation of the C-scan image, and an auxiliary table is used to segment defects in order that defects are disconnected to each other. Then, an algorithm based on edge element is proposed, simplifying the process of extracting edge. Finally, application of these procedures for inspecting a propeller-blade is demonstrated.

This paper develops an online algorithm based on sparse representation and boosting for robust object tracking. Local descriptors of a target object are represented by pooling some sparse codes of its local patches, and an Adaboost classifier is learned using the local descriptors to discriminate target from background. Meanwhile, the proposed algorithm assigns a weight value, calculated with the generative model, to each candidate object to adjust the classification result. In addition, a template update strategy, based on incremental principal component analysis and occlusion handing scheme, is presented to capture the appearance change of the target and to alleviate the visual drift problem. Comparison with the state-of-the-art trackers on the comprehensive benchmark shows effectiveness of the proposed method.

Kinship verification between aged parents and their children based on facial images is a challenging problem, due to aging factor which makes their facial similarities less distinct. In this paper, we propose to perform kinship verification in a transfer learning manner, which introduces photos of parents in their earlier ages as intermediate references to facilitate the verification. Child-young parent pairs are regarded as source domain and child-old parent ones are considered as target domain. The transfer learning scheme contains two phases. In the transfer metric learning phase, the extracted locality-constrained sparse features of images are projected into an optimized subspace where the intra-class distances are minimized and the inter-class ones are maximized. In the transfer classifier learning phase, a cross domain classifier is learned by a transfer SVM algorithm. Experimental results on UB KinFace dataset indicate that our method outperforms state-of-the-art methods.

As a light absorber in photovoltaic applications, hybrid organic-inorganic halide perovskites should have long and balanced diffusion lengths for both the separated electrons and holes before recombination, which necessitates high carrier mobility. In polar semiconductors, the room-temperature carrier mobility is often limited by the scattering between carriers and the lowest-frequency optical phonon modes. Using terahertz time-domain spectroscopy, we examine the temperature evolution of these phonon modes in CH3NH3PbBr3 and obtained high carrier mobility values using Feynman's polaron theory. This method allows us to estimate the upper limit of carrier mobilities without the need to create photogenerated free carriers, and can be applied to other heteropolar semiconductor systems with large polarons. MOE (Min. of Education, S’pore) Published version

Materials are often damaged during the process of detecting mass fractions by traditional methods. Acoustic emission (AE) technology combined with wavelet packet analysis is used to evaluate the mass fractions of microcrystalline graphite/polyvinyl alcohol (PVA) composites in this study. Attenuation characteristics of AE signals across the composites with different mass fractions are investigated. The AE signals are decomposed by wavelet packet technology to obtain the relationships between the energy and amplitude attenuation coefficients of feature wavelet packets and mass fractions as well. Furthermore, the relationship is validated by a sample. The larger proportion of microcrystalline graphite will correspond to the higher attenuation of energy and amplitude. The attenuation characteristics of feature wavelet packets with the frequency range from 125 kHz to 171.85 kHz are more suitable for the detection of mass fractions than those of the original AE signals. The error of the mass fraction of microcrystalline graphite calculated by the feature wavelet packet (1.8%) is lower than that of the original signal (3.9%). Therefore, AE detection base on wavelet packet analysis is an ideal NDT method for evaluate mass fractions of composite materials.

Economic reforms during the past few decades in China have been associated with migration of young Chinese from rural to urban centers. This migration as well as the one-child policy and increased longevity have affected the well-being of the elderly, who largely remain in rural residences. An erosion of the cultural tradition of filial piety has resulted and may adversely affect the mental health of a growing elderly population and increase the risk ofdeveloping depressive symptoms. We analyzed data from the China Health and Retirement Longitudinal Study that were collected in 2011. These data were from anationally representative and publicly available dataset, which provided comprehensive information about individuals aged ≥ 45 years in China. We evaluated the associations between 3 types of social support (family, community, and public) and depressive symptoms in the Chinese elderly (≥ 60 years) with a focus on age differentials and type of residential registration (urban or rural hukou). The results indicated that components of family, community, and public support were significantly and negatively associated with depressive symptoms. These components included living with a spouse, having frequent contact with children, having a senior center in the community, receiving a subsidy from the local agency, and receiving a pension. Also, the elderly living in a rural hukou had greater levels of depressive symptoms, and depressive symptoms in this population were most significantly and negatively affected by having a senior center in the community and receiving a local subsidy. Moreover, none of the three support mechanisms significantly affected the depressive symptoms of the oldest old. These results suggest that specific types of social support may negatively affect depressive symptomsand provide opportunities for targeted interventionsfrom community leaders and policy-makers that improve mental health and well-being among a growing elderly population in China.

Large break LOCA (LBLOCA) is one of the limit design basic accidents in nuclear power plant. The large flow water in the advanced accumulator is injected into primary loop in early short time. When the vessel pressure drops and reactor core is re-flooded, the advanced accumulator provides a small injection flow to keep the reactor core in flooded condition. Thus, the startup grace time of the low pressure safety injection pump is extended, and the core still stays in a long-term cooling state. By deducing the original accumulator model in RELAP5 accident analysis code, a new model combining the advanced and the traditional accumulator is obtained and coupled into RELAP5/ MOD 3.3. Simulation results show that there is a large flow in the advanced accumulator at the initial stage. When the accumulator water level is lower than the stand pipe, a vortex appears in the damper, resulting in a large pressure drop and small flow. The phenomenon meets the demand of the advanced accumulator design and the simulation of the advanced accumulator is accomplished successfully. Based on this, the primary coolant loop cold leg double-ended guillotine break LBLOCA in CPR1000 is analyzed with the modified RELAP5 code. When the double ended cold leg guillotine accident with 200s delayed startup of the low pressure safety injection occurs, maximum cladding temperature in the core with traditional accumulator is 1860K which seriously exceeded the safety temperature (1477K)[1] prescribed limits while the maximum cladding temperature with advanced accumulator has the security temperature-1277K. From this point of view, adopting passive advanced accumulator can strive a longer grace time for LPSI. Thus the reliability, security and economy of reactor system were improved.Copyright © 2013 by ASME

When visual tracking is performed by human, we typically pay attention to some salient regions or points of the target instead of the whole target. Inspired by this visual saliency property of human visual system, the paper proposes a novel salient regions extraction method to model target appearance. In order to capture the salient and spatial information within this model, the method extracts a set of local salient descriptors based on covariance features from the target. Afterwards, an optimization problem is constructed with respect to the features of these salient regions, and the optimal target state is obtained by solving this problem using a gradient descent algorithm. Experiments on several challenging video sequences demonstrate the good performance of the proposed method compared with four state-of-art tracking methods.

The ZnS thin films have been successfully fabricated on the surface of TiO2 nanoparticle electrodes via successive ionic layer adsorption and reaction method (SILAR). The thickness of ZnS coatings were controlled by varing the reaction cycles. The effect on the photovoltaic performance of the dye-sensitized solar cells (DSSCs) was systematically investigated. Electrical impedance spectroscopy (EIS) and intensity modulated photovoltaic spectroscopy were performed to analyze electronic processes. Results show that ZnS coatings have reduced the recombination rate during the electrons transportation and improved the fill factor of the DSSCs.

A novel method is proposed in this paper to model changes of object appearance for object contour tracking. Principal component analysis is utilized to learn eigenvectors from a set of the object appearance in our work, and then the current object appearance can be reconstructed by a linear combination of the eigenvectors. To extract the object contour, we perform covariance matching under the variational level set framework. The proposed method is tested on several sequences under large variations, and demonstrates that it outperforms current methods without updating the appearance template.

In this paper, we propose a visual tracking method based on local sparse covariance descriptor and matching pursuit. Covariance descriptor can model feature correlation of target templates effectively, and matching pursuit is employed to select the best target candidate which is reconstructed by target templates. The selection process is performed by solving a least square problem, and the candidate with the smallest projection error is taken as the tracking target. Experimental results on several video sequences demonstrate the good performance of proposed method compared with three existing tracking algorithms.