Pre-feasibility study of applying a biomass-powered district energy system in Marathon, Ontario

With the energy price fluctuation the nation is currently experiencing, more and more people are now looking into biomass as a substitute energy resource. Northwestern Ontario, with a history of forestry operations and management for over a hundred years and a substantial net annual growth of wood, has the potential to produce enough biomass to support the energy demand of the local communities as well as take a portion of the national or international market. There have been several previous studies within the region of Northwestern Ontario to assess the possibility of applying biomass heating in remote communities to reduce the cost as well as add energy supply stability. In this article, we examined the feasibility of applying a biomass-powered district energy system (DES) in Marathon, ON. A biomass-powered DES is proposed to be constructed in the town center to supply the surrounding public buildings with heat. The cost of the DES is $14,405,095. We concluded that a volume of 26,061 m3 of wood chips is needed to supply the DES annually. A total volume of 30,638 m3 of wood pellets will be needed to supply all the private dwellings in Marathon with individual biomass boilers or furnaces. There is a total volume of over 9 million cubic meters of wood that could be potentially used for biomass production in the surrounding forest units, within a 10-years management period, which could sufficiently supply the proposed project. The proposed DES will bring a potential annual saving of$2,075,249 on fuel, which will make the return period of the initial investment 8.737 years. The DES will also bring a GHG reduction of 3,712 tons annually

An Empirical Investigation of IPO Underpricing in Japanese Stock Market

In general, IPO underpricing is much lower in developed countries than developing countries. However, Japan is developed country with mature stock market, which has a high level of IPO underpricing. This is abnormal. Hence, this dissertation tries to investigate the driving factors in Japanese IPO underpricing by using a data sample of all 1561 IPOs issued in Japanese IPO market from 1997 to 2009. The initial return of new issues is used to measure the level of underpricing. Based on previous literatures and characteristics of Japanese IPO market, a multiple linear regression model is created with ten independent variables, consisting of offer size, offer price, frim age, underwriters’ reputation, offer price position, percent width of offer price range, high-tech industry, bull market, bear market and secondary offering percentage. Through analysing the descriptive statistics for key variables and the regression results, the six variables of frim age, offer price position, high-tech industry, bull market, bear market and secondary offering percentage are considered as significant determinants affecting the IPO underpricing in Japan

A Low Complexity Navigation Data Estimation Algorithm for Weak GNSS Signal Tracking

The computation load of traditional navigation data estimation algorithms for weak GNSS signal tracking increases exponentially with respect to the number of data bits needed to be estimated. To solve this problem, by adopting the dynamic programming philosophy, a navigation data bits estimation algorithm is proposed. The proposed algorithm uses the partial sum of correlation values as data bit combination searching branches. It can predict and exclude searching branches of data bit combination which have small coherent accumulated energy as soon as possible by angle quantification, thus reducing its computation load to be linearly related to the number of data bits needed to be estimated. Simulation results show that for signal of 500bps navigation data rate, the carrier track loop with a frequency discriminator implementing 0.12s coherent accumulation by navigation data estimation improves the tracking sensitivity up to 7 dB compared with traditional frequency discriminator under the same track accuracy constraint

Analysis of Spatial-Temporal Variation of Agricultural Drought and Its Response to ENSO over the Past 30 Years in the Huang-Huai-Hai Region, China

This study constructed a time series of the seasonal Temperature Vegetation Dryness Index (TVDI) based on a remotely sensed dataset from the National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Earth Observing System/Moderate Resolution Imaging Spectroradiometer (EOS/MODIS). We examined the spatiotemporal variation in drought in the Huang-Huai-Hai region of China during the period from 1981 to 2011. Combined with the El Niño and southern oscillation (ENSO) indicator (i.e., the Sea Surface Temperature Anomaly, SSTA of the El Niño 3.4 area), the spatial and temporal relationship of agricultural drought in this region and ENSO was analyzed. The results showed that drought demonstrated a significant downward trend (95% confidence level) which covered 38.01 ~ 55.13% of the farmland in this region. In addition, the largest area of drought reducing appeared in winter. The significant decreasing tendency of agricultural drought started from the late 20th and early 21st centuries, whose variation cycles were mainly between 2.5 to 5 a (year). TVDI series were closely correlated to the ENSO index sequences at the 2.5 to 7 a cycle, and there was a delay from 0.16 to 1.40 a between them. However, the correlation between TVDI and ENSO index series was less. These findings show that there is a relationship between the spatiotemporal changes of agricultural drought in the Huang-Huai-Hai region of China and ENSO events over the recent 30 years

Identification of diagnostic hub genes related to neutrophils and infiltrating immune cell alterations in idiopathic pulmonary fibrosis

BackgroundThere is still a lack of specific indicators to diagnose idiopathic pulmonary fibrosis (IPF). And the role of immune responses in IPF is elusive. In this study, we aimed to identify hub genes for diagnosing IPF and to explore the immune microenvironment in IPF.MethodsWe identified differentially expressed genes (DEGs) between IPF and control lung samples using the GEO database. Combining LASSO regression and SVM-RFE machine learning algorithms, we identified hub genes. Their differential expression were further validated in bleomycin-induced pulmonary fibrosis model mice and a meta-GEO cohort consisting of five merged GEO datasets. Then, we used the hub genes to construct a diagnostic model. All GEO datasets met the inclusion criteria, and verification methods, including ROC curve analysis, calibration curve (CC) analysis, decision curve analysis (DCA) and clinical impact curve (CIC) analysis, were performed to validate the reliability of the model. Through the Cell Type Identification by Estimating Relative Subsets of RNA Transcripts algorithm (CIBERSORT), we analyzed the correlations between infiltrating immune cells and hub genes and the changes in diverse infiltrating immune cells in IPF.ResultsA total of 412 DEGs were identified between IPF and healthy control samples, of which 283 were upregulated and 129 were downregulated. Through machine learning, three hub genes (ASPN, SFRP2, SLCO4A1) were screened. We confirmed their differential expression using pulmonary fibrosis model mice evaluated by qPCR, western blotting and immunofluorescence staining and analysis of the meta-GEO cohort. There was a strong correlation between the expression of the three hub genes and neutrophils. Then, we constructed a diagnostic model for diagnosing IPF. The areas under the curve were 1.000 and 0.962 for the training and validation cohorts, respectively. The analysis of other external validation cohorts, as well as the CC analysis, DCA, and CIC analysis, also demonstrated strong agreement. There was also a significant correlation between IPF and infiltrating immune cells. The frequencies of most infiltrating immune cells involved in activating adaptive immune responses were increased in IPF, and a majority of innate immune cells showed reduced frequencies.ConclusionOur study demonstrated that three hub genes (ASPN, SFRP2, SLCO4A1) were associated with neutrophils, and the model constructed with these genes showed good diagnostic value in IPF. There was a significant correlation between IPF and infiltrating immune cells, indicating the potential role of immune regulation in the pathological process of IPF

Distillation of liquid fuels by thermogravimetry

In this paper, design and operation of a custom-built thermogravimetric apparatus for the distillation of liquid fuels are reported. Using a sensitive balance with scale of 0.001 g and ASTM distillation glassware, several petroleum and petroleum-derived samples have been analyzed by the thermogravimetric distillation method. When the ASTM distillation glassware is replaced by a micro-scale unit, sample size could be reduced from 100 g to 5-10 g. A computer program has been developed to transfer the data into a distillation plot, e.g. Weight Percent Distilled vs. Boiling Point. It also generates a report on the characteristic distillation parameters, such as, IBP (Initial Boiling Point), FBP (Final Boiling Point), and boiling point at 50 wt% distilled. Comparison of the boiling point distributions determined by TG (thermogravimetry) with those by SimDis GC (Simulated-Distillation Gas Chromatography) on two liquid fuel samples (i.e. a decanted oil and a filtered crude oil) are also discussed in this paper

Applications of the thermogravimetric analysis in the study of fossil fuels

Thermogravimetric analysis (TGA) of coal and resid liquids and coal and resid solid residues, produced in coal liquefaction and coal- derived resid hydroprocessing in SCTBR (short contact time batch reactor), provides a sensitive, rapid, reproducible means of studying kinetics and mechanisms of fossil fuel conversion processes. SimDis TGA and custom built TGA system for distillation provide unique means to characterize liquid fuels for boiling point distribution. TGA provides information about various weight loss processes that can be a reflection of physical and chemical structure of fossil fuel samples. This technique can also yield TG scanning parameters, such as volatile matter, fixed carbon, ash, etc., for monitoring the conversion processes. One example is onset and rate of retrograde reactions during coal liquefaction

A novel smoothing routine for the data processing in thermogravimetric analysis

For a certain short interval of a TG scan, the correlation between mass and time is linear. A smoothing and filtering routine based on use of linear regression and error analysis was developed and successfully applied in the TG data processing. This method provides a filter to smooth the noise fluctuations and, at the same time, to introduce no distortions into the TGA experimental data. The computer program required is quite simple and effective. The method used in the program promises auto-convergence