Quality assurance plan for China collection 2.0 aerosol datasets

The inversion of atmospheric aerosol optical depth (AOD) using satellite data has always been a challenge topic in atmospheric research. In order to solve the aerosol retrieval problem over bright land surface, the Synergetic Retrieval of Aerosol Properties (SRAP) algorithm has been developed based on the synergetic using of the MODIS data of TERRA and AQUA satellites [1, 2]. In this paper we describe, in details, the quality assessment or quality assurance (QA) plan for AOD products derived using the SRAP algorithm. The pixel-based QA plan is to give a QA flag to every step of the process in the AOD retrieval. The quality assessment procedures include three common aspects: 1) input data resource flags, 2) retrieval processing flags, 3) product quality flags [3]. Besides, all AOD products are assigned a QA ‘confidence’ flag (QAC) that represents the aggregation of all the individual QA flags. This QAC value ranges from 3 to 0, with QA = 3 indicating the retrievals of highest confidence and QA = 2/QA = 1 progressively lower confidence [4], and 0 means ‘bad’ quality. These QA (QAC) flags indicate how the particular retrieval process should be considered. It is also used as a filter for expected quantitative value of the retrieval, or to provide weighting for aggregating/averaging computations [5]. All of the QA flags are stored as a “bit flag” scientific dataset array in which QA flags of each step are stored in particular bit positions

Post calibration of channel 1 of NOAA-14 AVHRR: Implications on aerosol optical depth retrieval

In order to produce long-term aerosol optical depth (AOD) dataset over land from the Advanced Very High Resolution Radiometer (AVHRR), AVHRR data quality in terms of radiometric calibration must be maintained. A vicarious calibration method have been developed by incorporating well calibrated Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) radiance data over several pseudo-invariant targets to inter-calibrate the channel 1 of AVHRR based on Bidirectional Reflectance Distribution Functions (BRDFs) and spectral band adjustment factor (SBAF) models for different targets. Comparison of our calibration coefficients with those of Pathfinder Atmospheres Extended (PATMOS-x) indicate the calibration accuracy to be within 2.5%. The operational L1B and recalibrated AVHRR radiance are applied to derive AOD maps over East America (dark surface) and West Africa (bright surface) using the land aerosol and bidirectional reflectance inversion by times series technique (LABITS) algorithm. Preliminary comparisons show that significant difference in the retrieved AOD from the two different calibration is expected, while the spatial distribution of AOD difference is complicated due to different surface brightness and deficiencies of numeric solutions

Information and Control ICIC International c ⃝2011 ISSN

Abstract. The statistical process control (SPC) chart is effective in detecting proces

Hybrid Soft Computing Schemes for the Prediction of Import Demand of Crude Oil in Taiwan

Crude oil is the most important nonrenewable energy resource and the most key element for the world. In contrast to typical forecasts of oil price, this study aims at forecasting the demand of imported crude oil (ICO). This study proposes different single stage and two-stage hybrid stages of forecasting models for prediction of ICO in Taiwan. The single stage forecasting modeling includes multiple linear regression (MLR), support vector regression (SVR), artificial neural networks (ANN), and extreme learning machine (ELM) approaches. While the first step of the two-stage modeling is to select the fewer but more significant explanatory variables, the second step is to generate predictions by using these significant explanatory variables. The proposed two-stage hybrid models consist of integration of different modeling components. Mean absolute percentage error, root mean square error, and mean absolute difference are utilized as the performance measures. Real data set of crude oil in Taiwan for the period of 1993–2010 and twenty-three associated explanatory variables are sampled and investigated. The forecasting results reveal that the proposed two-stage hybrid modeling is able to accurately predict the demand of crude oil in Taiwan

Omics approach for generating a high-yield CHO cell line producing monoclonal antibodies

Chinese hamster ovary (CHO) cells are extensively used for the industrial manufacture of therapeutic antibodies. Generating high producing cell lines for secretory protein production requires knowing the bottleneck in the cellular machinery for protein expression. Integration site of gene of interest (GOI) is one of the important factors that influence the protein productivity. Even though screening of cells randomly integrated GOI can select high producing cells, the selected cell might not stable due to the chromosome instability. Here, we would like to look for host integration sites where GOI is high yield and stable by screening a single copy integration system. We developed several methods to identify integration sites including PCR based, whole genome sequencing based, and a platform to integrate a single copy of GOI into host genome. By determining the integration sites of the high producing clones, we can elucidate the major high yield sites for target gene expression. We have also employed the genome-editing tool, TALEN and CRISPR/cas9 to specifically integrate the vector with an antibody gene into two integration sites of CHO genome. Our data showed, IS1 and IS2 integration sites can be actively edited and specifically integrated an antibody expression vector of 15kb by either TALEN or CRISPR/Cas9. We successfully established site specifically integrated cell pools and expanded the FACS-sorted single cell into a cell line. Each single cell derived cell lines was confirmed by junction-PCR and sequence analysis. Furthermore, these single cells derived CHO cell lines are shown to express antibody gene with high titer. With the combination of omics knowledge and toolbox, including CHO genomics, transcriptomics and CHO specific microarray, GOI can be stably and highly produced

The flow back tracing and DDoS defense mechanism of the TWAREN defender cloud

The TWAREN Defender Cloud is a distributed filter platform on thenetwork backbone to help defending our connecting institutions against maliciousnetwork attacks. By combining the security reports from participating schools, thissystem can block the incoming threats from the entry points, thus it helps protectingall connecting institutions in the most economic and effective way. This paper aimedat explaining the analyzer design, its mechanism to back trace DDoS attack flows totheir entry points and the defense mechanism it provides to block the threats

Neuroprotective Effect of Ginkgolide B on Bupivacaine-Induced Apoptosis in SH-SY5Y Cells

Local anesthetics are used routinely and effectively. However, many are also known to activate neurotoxic pathways. We tested the neuroprotective efficacy of ginkgolide B (GB), an active component of Ginkgo biloba, against ROS-mediated neurotoxicity caused by the local anesthetic bupivacaine. SH-SY5Y cells were treated with different concentrations of bupivacaine alone or following preincubation with GB. Pretreatment with GB increased SH-SY5Y cell viability and attenuated intracellular ROS accumulation, apoptosis, mitochondrial dysfunction, and ER stress. GB suppressed bupivacaine-induced mitochondrial depolarization and mitochondria complex I and III inhibition and increased cleaved caspase-3 and Htra2 expression, which was strongly indicative of activation of mitochondria-dependent apoptosis with concomitantly enhanced expressions of Grp78, caspase-12 mRNA, protein, and ER stress. GB also improved ultrastructural changes indicative of mitochondrial and ER damage induced by bupivacaine. These results implicate bupivacaine-induced ROS-dependent mitochondria, ER dysfunction, and apoptosis, which can be attenuated by GB through its antioxidant property

SERPINE2, an inhibitor of plasminogen activators, is highly expressed in the human endometrium during the secretory phase

<p>Abstract</p> <p>Background</p> <p>SERPINE2, also known as protease nexin-1, belongs to the serine protease inhibitor (SERPIN) superfamily. It is one of the potent SERPINs that modulates the activity of plasminogen activators (PAs). PAs and their SERPIN inhibitors, such as SERPINB2 and SERPINE1, were expressed in the human endometrium and were implicated in implantation. However, expression data about SERPINE2 in the human endometrium is still unknown. Thus, we conducted an investigation to reveal the spatiotemporal and cellular expression of SERPINE2 in the human uterus during the menstrual cycle.</p> <p>Methods</p> <p>Seven patients who underwent a hysterectomy and samples of 120 archived patients' endometrial curettage or parts of the uterus that were formalin-fixed and embedded in paraffin. Western blotting was performed to evaluate the specificity and sensitivity of the antibody. Immunohistochemistry was conducted to localize the SERPINE2 expression site. Quantitative analysis was conducted to evaluate expression levels of SERPINE2 in various sub-phases of the menstrual cycle.</p> <p>Results</p> <p>The SERPINE2 protein was primarily detected in the uterine fluid during the mid- and late-secretory phases of the menstrual cycle. It was predominantly expressed in the luminal and glandular epithelium, less in the myometrium, and only dispersedly in certain stromal cells throughout the menstrual cycle. A quantitative analysis of expression levels of SERPINE2 in the glandular epithelium revealed that it was highly expressed in the endometrium during the secretory phase compared to the proliferative phase.</p> <p>Conclusions</p> <p>The SERPINE2 protein is highly expressed in the endometrium during the secretory phase, indicating that it may participate in tissue remodeling involved in implantation.</p