Controllable 3D display system based on frontal projection lenticular screen

A novel auto-stereoscopic three-dimensional (3D) projection display system based on the frontal projection lenticular screen is demonstrated. It can provide high real 3D experiences and the freedom of interaction. In the demonstrated system, the content can be changed and the dense of viewing points can be freely adjusted according to the viewers’ demand. The high dense viewing points can provide smooth motion parallax and larger image depth without blurry. The basic principle of stereoscopic display is described firstly. Then, design architectures including hardware and software are demonstrated. The system consists of a frontal projection lenticular screen, an optimally designed projector-array and a set of multi-channel image processors. The parameters of the frontal projection lenticular screen are based on the demand of viewing such as the viewing distance and the width of view zones. Each projector is arranged on an adjustable platform. The set of multi-channel image processors are made up of six PCs. One of them is used as the main controller, the other five client PCs can process 30 channel signals and transmit them to the projector-array. Then a natural 3D scene will be perceived based on the frontal projection lenticular screen with more than 1.5 m image depth in real time. The control section is presented in detail, including parallax adjustment, system synchronization, distortion correction, etc. Experimental results demonstrate the effectiveness of this novel controllable 3D display system

Neural progenitor cells generate motoneuron-like cells to form functional connections with target muscles after transplantation into the musculocutaneous nerve

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Serum Amyloid A in Stable COPD Patients is Associated with the Frequent Exacerbator Phenotype

Background: We sought to determine whether circulating inflammatory biomarkers were associated with the frequent exacerbator phenotype in stable COPD patients ie, those with two or more exacerbations in the previous year. Methods: Eighty-eight stable, severe, COPD patients (4 females) were assessed for exacerbation frequency, pulmonary function, fraction of expired nitric oxide (FENO); inflammatory variables were measured in venous blood. Logistic regression assessed associations between the frequent exacerbator phenotype and systemic inflammation. Results: Compared with infrequent exacerbators, frequent exacerbators (n=10; 11.4%) had greater serum concentration (median (25th-75th quartile)) of serum amyloid A (SAA; 134 (84– 178) vs 71 (38– 116) ng/mL; P=0.024), surfactant protein D (SP-D; 15.6 (9.0– 19.3) vs 8.5 (3.6– 14.9) ng/mL; P=0.049) and interleukin-4 (IL-4; 0.12 (0.08– 1.44) vs 0.03 (0.01– 0.10) pg/mL; P=0.001). SAA, SP-D and IL-4 were not significantly correlated with FEV1%predicted or FVC %predicted. After adjusting for sex, age, BMI, FEV1/FVC and smoking pack-years, only SAA remained independently associated with the frequent exacerbator phenotype (OR 1.49[1.09– 2.04]; P=0.012). The odds of being a frequent exacerbator was 18-times greater in the highest SAA quartile (≥ 124.1 ng/mL) than the lowest SAA quartile (≤ 44.1 ng/mL) (OR 18.34[1.30– 258.81]; P=0.031), and there was a significant positive trend of increasing OR with increasing SAA quartile (P=0.008). For SAA, the area under the receiver operating characteristic curve was 0.721 for identification of frequent exacerbators; an SAA cut-off of 87.0 ng/mL yielded an 80% sensitivity and 61.5% specificity. Conclusion: In stable COPD patients, SAA was independently associated with the frequent exacerbator phenotype, suggesting that SAA may be a useful serum biomarker to inform progression or management in COPD

The driver of dengue fever incidence in two high-risk areas of China: A comparative study.

In China, the knowledge of the underlying causes of heterogeneous distribution pattern of dengue fever in different high-risk areas is limited. A comparative study will help us understand the influencing factors of dengue in different high-risk areas. In the study, we compared the effects of climate, mosquito density and imported cases on dengue fever in two high-risk areas using Generalized Additive Model (GAM), random forests and Structural Equation Model (SEM). GAM analysis identified a similar positive correlation between imported cases, density of Aedes larvae, climate variables and dengue fever occurrence in the studied high-risk areas of both Guangdong and Yunnan provinces. Random forests showed that the most important factors affecting dengue fever occurrence were the number of imported cases, BI and the monthly average minimum temperature in Guangdong province; whereas the imported cases, the monthly average temperature and monthly relative humidity in Yunnan province. We found the rainfall had the indirect effect on dengue fever occurrence in both areas mediated by mosquito density; while the direct effect in high-risk areas of Guangdong was dominated by temperature and no obvious effect in Yunnan province by SEM. In total, climate factors and mosquito density are the key drivers on dengue fever incidence in different high-risk areas of China. These findings could provide scientific evidence for early warning and the scientific control of dengue fever in high-risk areas

Electrospinning for healthcare: recent advancements

Electrospinning is a simple route to generate polymer-based fibres with diameters on the nano- to micron-scale. It has been very widely explored in biomedical science for applications including drug delivery systems, diagnostic imaging, theranostics, and tissue engineering. This extensive literature reveals that a diverse range of functional components including small molecule drugs, biologics, and nanoparticles can be incorporated into electrospun fibres, and it is possible to prepare materials with complex compartmentalised architectures. This perspective article briefly introduces the electrospinning technique before considering its potential applications in biomedicine. Particular attention is paid to the translation of electrospinning to the clinic, including the need to produce materials at large scale and the requirement to do so under Good Manufacturing Practice conditions. We finish with a summary of the key current challenges and future perspectives

Computational Model for Urban Growth Using Socioeconomic Latent Parameters

Land use land cover changes (LULCC) are generally modeled using multi-scale spatio-temporal variables. Recently, Markov Chain (MC) has been used to model LULCC. However, the model is derived from the proportion of LULCC observed over a given period and it does not account for temporal factors such as macro-economic, socio-economic, etc. In this paper, we present a richer model based on Hidden Markov Model (HMM), grounded in the common knowledge that economic, social and LULCC processes are tightly coupled. We propose a HMM where LULCC classes represent hidden states and temporal fac-tors represent emissions that are conditioned on the hidden states. To our knowledge, HMM has not been used in LULCC models in the past. We further demonstrate its integration with other spatio-temporal models such as Logistic Regression. The integrated model is applied on the LULCC data of Pune district in the state of Maharashtra (India) to predict and visualize urban LULCC over the past 14 years. We observe that the HMM integrated model has improved prediction accuracy as compared to the corresponding MC integrated modelComment: 12 page

Pan-genome analysis highlights the role of structural variation in the evolution and environmental adaptation of Asian honeybees.

The Asian honeybee, Apis cerana, is an ecologically and economically important pollinator. Mapping its genetic variation is key to understanding population-level health, histories and potential capacities to respond to environmental changes. However, most efforts to date were focused on single nucleotide polymorphisms (SNPs) based on a single reference genome, thereby ignoring larger scale genomic variation. We employed long-read sequencing technologies to generate a chromosome-scale reference genome for the ancestral group of A. cerana. Integrating this with 525 resequencing data sets, we constructed the first pan-genome of A. cerana, encompassing almost the entire gene content. We found that 31.32% of genes in the pan-genome were variably present across populations, providing a broad gene pool for environmental adaptation. We identified and characterized structural variations (SVs) and found that they were not closely linked with SNP distributions; however, the formation of SVs was closely associated with transposable elements. Furthermore, phylogenetic analysis using SVs revealed a novel A. cerana ecological group not recoverable from the SNP data. Performing environmental association analysis identified a total of 44 SVs likely to be associated with environmental adaptation. Verification and analysis of one of these, a 330 bp deletion in the Atpalpha gene, indicated that this SV may promote the cold adaptation of A. cerana by altering gene expression. Taken together, our study demonstrates the feasibility and utility of applying pan-genome approaches to map and explore genetic feature variations of honeybee populations, and in particular to examine the role of SVs in the evolution and environmental adaptation of A. cerana