Evaluation of positioning error-induced pixel shifts on satellite linear push-broom imagery

Georeferencing is one of the major tasks of satellite-borne remote sensing. Compared to traditional indirect methods, direct georeferencing through a Global Positioning System/inertial navigation system requires fewer and simpler steps to obtain exterior orientation parameters of remotely sensed images. However, the pixel shift caused by geographic positioning error, which is generally derived from boresight angle as well as terrain topography variation, can have a great impact on the precision of georeferencing. The distribution of pixel shifts introduced by the positioning error on a satellite linear push-broom image is quantitatively analyzed. We use the variation of the object space coordinate to simulate different kinds of positioning errors and terrain topography. Then a total differential method was applied to establish a rigorous sensor model in order to mathematically obtain the relationship between pixel shift and positioning error. Finally, two simulation experiments are conducted using the imaging parameters of Chang’ E-1 satellite to evaluate two different kinds of positioning errors. The experimental results have shown that with the experimental parameters, the maximum pixel shift could reach 1.74 pixels. The proposed approach can be extended to a generic application for imaging error modeling in remote sensing with terrain variation

Prompting Fab Yeast Surface Display Efficiency by ER Retention and Molecular Chaperon Co-expression.

For antibody discovery and engineering, yeast surface display (YSD) of antigen-binding fragments (Fabs) and coupled fluorescence activated cell sorting (FACS) provide intact paratopic conformations and quantitative analysis at the monoclonal level, and thus holding great promises for numerous applications. Using anti-TNFα mAbs Infliximab, Adalimumab, and its variants as model Fabs, this study systematically characterized complementary approaches for the optimization of Fab YSD. Results suggested that by using divergent promoter GAL1-GAL10 and endoplasmic reticulum (ER) signal peptides for co-expression of light chain and heavy chain-Aga2 fusion, assembled Fabs were functionally displayed on yeast cell surface with sigmoidal binding responses toward TNFα. Co-expression of a Hsp70 family molecular chaperone Kar2p and/or protein-disulfide isomerase (Pdi1p) significantly improved efficiency of functional display (defined as the ratio of cells displaying functional Fab over cells displaying assembled Fab). Moreover, fusing ER retention sequences (ERSs) with light chain also enhanced Fab display quality at the expense of display quantity, and the degree of improvements was correlated with the strength of ERSs and was more significant for Infliximab than Adalimumab. The feasibility of affinity maturation was further demonstrated by isolating a high affinity Fab clone from 1:103 or 1:105 spiked libraries

Using Non-Additive Measure for Optimization-Based Nonlinear Classification

Over the past few decades, numerous optimization-based methods have been proposed for solving the classification problem in data mining. Classic optimization-based methods do not consider attribute interactions toward classification. Thus, a novel learning machine is needed to provide a better understanding on the nature of classification when the interaction among contributions from various attributes cannot be ignored. The interactions can be described by a non-additive measure while the Choquet integral can serve as the mathematical tool to aggregate the values of attributes and the corresponding values of a non-additive measure. As a main part of this research, a new nonlinear classification method with non-additive measures is proposed. Experimental results show that applying non-additive measures on the classic optimization-based models improves the classification robustness and accuracy compared with some popular classification methods. In addition, motivated by well-known Support Vector Machine approach, we transform the primal optimization-based nonlinear classification model with the signed non-additive measure into its dual form by applying Lagrangian optimization theory and Wolfes dual programming theory. As a result, 2 – 1 parameters of the signed non-additive measure can now be approximated with m (number of records) Lagrangian multipliers by applying necessary conditions of the primal classification problem to be optimal. This method of parameter approximation is a breakthrough for solving a non-additive measure practically when there are a relatively small number of training cases available (). Furthermore, the kernel-based learning method engages the nonlinear classifiers to achieve better classification accuracy. The research produces practically deliverable nonlinear models with the non-additive measure for classification problem in data mining when interactions among attributes are considered

Brzo otkrivanje uzročnika virusnog proljeva goveda u mlijeku iz spremnika pomoću kombinacije metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu

Bovine viral diarrhea virus (BVDV) is one of the most prevalent and economically important pathogens of ruminants, and leads to significant financial losses to the livestock industry worldwide. Development of rapid and accurate diagnostic methods is of great importance for the control and eradication of BVDV infection. The aim of this study was to develop a novel isothermal recombinase polymerase amplification (RPA) method combined with a lateral flow dipstick (LFD), for rapid detection of BVDV. RPA primers and a probe targeting the specific conserved 5′-UTR of BVDV genome were designed. The RPA amplification could be finished at a constant temperature of 38 0000C for 15 min, and the amplification product was easily visualized on a simple LFD within 5 min. The detection limit of this assay was 20 copies per reaction, and there was no cross-reactivity with other bovine infectious viruses, such as infectious bovine rhinotracheitis virus (IBRV), bovine enterovirus (BEV), bovine coronavirus (BcoV), bovine parainfluenza virus type 3 (BPIV-3), bovine ephemeral fever virus (BEFV) and bovine respiratory syncytial virus (BRSV). The assay performance on bulk tank milk was also evaluated, and the sensitivity and accuracy of BVDV LFD RPA was compared with real-time RT-PCR. Of 284 pool or bulk tank milk samples, 51 were found to be positive by RPA assay, whereas 52 were positive by real-time RT-PCR. The coincidence rate between LFD RPA and real-time RT-PCR was 97.54% (277/284).Uzročnik virusnog proljeva goveda (BVDV) jedan je od najčešćih i ekonomski važnih patogena preživača koji uzrokuje znatne financijske gubitke u stočarskoj industriji širom svijeta. Razvoj brzih i točnih dijagnostičkih metoda iznimno je važan za kontrolu i iskorjenjivanje zaraze BVDV-om. Cilj ovog istraživanja bio je razviti novu metodu za brzo otkrivanje BVDV-a baziranu na kombinaciji metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu. Oblikovane su početnice i probe za umnažanje rekombinazne polimeraze usmjerene na specifični konzervirani 5’-UTR u genomu BVDV-a. Umnažanje se moglo završiti pri konstantnoj temperaturi od 38 °C tijekom 15 minuta i produkt umnažanja je lako vizualiziran na jednostavnoj test-traci za „lateral flow“ analizu unutar 5 minuta. Test je ograničen na 20 kopija po reakciji, pri čemu nije bilo križne reaktivnosti s drugim goveđim zaraznim virusima kao što su infektivni rinotraheitis virusa goveda (IBRV), goveđi enterovirus (BEV), goveđi koronavirus (BcoV), virus goveđe parainfluence tipa 3 (BPIV-3), virus gljivične ephemeralne groznice (BEFV) i goveđi respiratorni sincicijski virus (BRSV). Učinkovitost kombinacije navedenih metoda istražena je i s obzirom na usporedbu osjetljivosti odnosno točnosti koja se dobiva uporabom RT-PCR metode. Od 284 skupna uzorka mlijeka iz spremnika, kombinacijom metoda umnožene rekombinazne polimeraze i test-traka za „lateral flow“ analizu utvrđen je 51 pozitivan uzorak, a RT-PCR 52 pozitivna uzorka. Stopa podudarnosti između navedenih metoda bila je 97,54 % (277/284)

Bone Mineral Density Reference Standards for Chinese Children Aged 3-18: Cross-Sectional Results of the 2013-2015 China Child and Adolescent Cardiovascular Health (CCACH) Study

Objectives: No nationwide paediatric reference standards for bone mineral density (BMD) are available in China. We aimed to provide sex-specific BMD reference values for Chinese children and adolescents (3-18 years). Methods: Data (10 818 participants aged 3-18 years) were obtained from cross-sectional surveys of the China Child and Adolescent Cardiovascular Health in 2015, which included four municipality cities and three provinces. BMD was measured using Hologic Discovery Dual Energy X-ray Absorptiometry (DXA) scanner. The DXA measures were modelled against age, with height as an independent variable. The LMS statistical method using a curve fitting procedure was used to construct reference smooth cross-sectional centile curves for dependent versus independent variables. Results: Children residing in Northeast China had the highest total body less head (TBLH) BMD while children residing in Shandong Province had the lowest values. Among children, TBLH BMD was higher for boys as compared with girls; but, it increased with age and height in both sexes. Furthermore, TBLH BMD was higher among US children as compared with Chinese children. There was a large difference in BMD for height among children from these two countries. US children had a much higher BMD at each percentile (P) than Chinese children; the largest observed difference was at P50 and P3 and the smallest difference was at P97. Conclusions: This is the first study to present a sex-specific reference dataset for Chinese children aged 3-18 years. The data can help clinicians improve interpretation, assessment and monitoring of densitometry results

Green Light-Emitting Devices Based on Perovskite CsPbBr3 Quantum Dots

In this paper, high quality green-emitting CsPbBr3 quantum dots (QDs) are successfully synthesized by hot-injection method. Different injection temperatures are tested to optimize the synthesis conditions. High brightness with the photoluminescence (PL) quantum yields (QYs) up to 90% and narrow size-distribution with the full width at half-maximum (FWHM) of 18.5 nm are obtained under the optimized conditions. Green light emitting diodes (LEDs) based on the CsPbBr3 QDs are successfully demonstrated by combining solution method with vapor deposition method. Composite films of poly[9,9-dioctylfluorene-co- N-[4-(3-methylpropyl)]-diphenylamine] (TFB) and bathocuproine (BCP) layers are chosen as the hole-transporting and the electron-transporting layers, respectively. The highly bright green QD-based light-emitting devices (QLEDs) showing maximum luminance up to 46,000 cd/m2 with a low turn on voltage of 2.3 V, and peak external quantum efficiency (EQE) of 5.7%, corresponding to 19.9 cd/A in luminance efficiency. These devices also show high color purity for electroluminescence (EL) with FWHM <20 nm, and no redshift and broadening with increasing voltage as well as a spectral match between PL and EL

Intracytoplasmic sperm injection (ICSI) versus conventional in vitro fertilisation (IVF) in couples with non-severe male infertility (NSMI-ICSI) : protocol for a multicentre randomised controlled trial

Funding This study was supported by National Key Research and Development Program of China (2016YFC1000201; 2018YFC1002104) and the National Science Foundation of China (81730038). The study funders had no rule in the study design, implementation, analysis, manuscript, preparation or decision to submit this article for publication.Peer reviewedPublisher PD

Evaluation of association tests for rare variants using simulated data sets in the Genetic Analysis Workshop 17 data

We evaluate four association tests for rare variants—the combined multivariate and collapsing (CMC) method, two weighted-sum methods, and a variable threshold method—by applying them to the simulated data sets of unrelated individuals in the Genetic Analysis Workshop 17 (GAW17) data. The family-wise error rate (FWER) and average power are used as criteria for evaluation. Our results show that when all nonsynonymous SNPs (rare variants and common variants) in a gene are jointly analyzed, the CMC method fails to control the FWER; when only rare variants (single-nucleotide polymorphisms with minor allele frequency less than 0.05) are analyzed, all four methods can control FWER well. All four methods have comparable power, which is low for the analysis of the GAW17 data sets. Three of the methods (not including the CMC method) involve estimation of p-values using permutation procedures that either can be computationally intensive or generate inflated FWERs. We adapt a fast permutation procedure into these three methods. The results show that using the fast permutation procedure can produce FWERs and average powers close to the values obtained from the standard permutation procedure on the GAW17 data sets. The standard permutation procedure is computationally intensive