Construction of a Fusion Gene Carrying E10A and K5 with 2A Peptide-Linked by Using Overlap Extension PCR

E10A is a kind of replication-defective adenovirus which carries the human endostatin gene to inhibit the growth of tumors. Kringle 5(K5) has almost the same function as angiostatin to also inhibit the growth of tumors since they are all the byproduct of the proteolytic cleavage of plasminogen. Tumor size increasing can be suppressed because both of the endostatin and K5 can restrain the angiogenesis process. Therefore, in order to improve the treatment effect on tumor, 2A peptide is used to construct a fusion gene carrying both E10A and K5. Using 2A peptide is an ideal strategy when a fusion gene is expressed because it can avoid many problems during the expression of more than one kind of protein. The overlap extension PCR is also used to connect 2A peptide with E10A and K5. The final construction of fusion gene E10A-2A-K5 can provide a possible new method of the anti-angiogenesis treatment with a better expression performance.

Forecasting Stock Indexes Using Bayesian Additive Regression Tree

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Productivity Effect of Urea Deep Placement Technology: An Empirical Analysis from Irrigation Rice Farmers in the Northern Region of Ghana

This study examined the effect of Urea Deep Placement (UDP) technology on the output of irrigated rice farmers in the northern region of Ghana. Multi-stage sampling technique was used to select 142 rice farmers from the Golinga and Bontanga irrigation schemes, around Tamale. A treatment effect model was estimated at two stages; firstly, to determine the factors that influenced farmers’ decision to adopt the UDP technology and secondly, to determine the effect of the adoption of the UDP technology on the output of rice farmers. The significant variables that influenced rice farmers’ adoption of the UPD technology were sex of the farmer, land ownership, off-farm activity, extension service, farmer group participation and training. The results also revealed that farm size and the adoption of UDP technology significantly influenced the output of rice farmers in the northern region of Ghana. In addition to the potential of the technology to improve yields, it also presents an employment opportunity for women and youth, who are engaged in the deep placement of Urea Super Granules (USG), as well as in the transplantation of rice. It is recommended that the government of Ghana work closely with the IFDC to embed the UDP technology in the national agricultural programmes and policies. The study also recommends an effective collaboration between the government, through the Ministry of Food and Agriculture (MoFA) and the International Fertilizer Development Center (IFDC) to train agricultural extension agents on UDP technology in the rice producing areas of the country.

Comparison of the Effects of Continuous Flow Microwave Pre-treatment with Different Intensities on the Anaerobic Digestion of Sewage Sludge for Sustainable Energy Recovery from Sewage Treatment Plant

Anaerobic digestion is a well-known technique for sustainable energy recovery from sewage sludge. However, sewage sludge digestion is restricted due to certain factors. Pre-treatment methods have been established in various publications as a promising technique to improve the digestibility of the sewage sludge and to enhance the biogas generated which can be used for energy recovery. In this study, continuous flow microwave (MW) pre-treatment with different intensities were compared by using 5 L semi-continuous digesters at a hydraulic retention time of 27 days. We focused on the effects of MW at different intensities on the sludge solubilization, sludge digestibility, and biogas production of the untreated and MW pre-treated sludge. The MW pre-treatment demonstrated an increase in the ratio of soluble chemical oxygen demand to total chemical oxygen demand (sCOD/tCOD) and volatile fatty acid (VFA) concentration. Besides that, the total volatile solid (TVS) removal efficiency and tCOD removal efficiency also increased during the digestion of the MW pre-treated sewage sludge compared to the untreated sewage sludge. Furthermore, the biogas yield also subsequently increases due to the pre-treatment effect. A higher MW power level and irradiation time generally enhanced the biogas generation which has potential for sustainable energy recovery from sewage treatment plant. However, the net energy balance tabulation shows that the MW pre-treatment leads to negative net energy production.

On Pooling Different Levels of Data in Estimating Parameters of Continuous Meta-Analysis

A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combining the studies from different level have not been fully explored. This study aims to quantify the statistical benefits of including available IPD when conducting a conventional summary-level meta-analysis. Simulated meta-analysis were used to assess the influence of the levels of data on overall meta-analysis estimates based on IPD-only, AD-only and the combination of IPD and AD (mixed data, MD), under different study scenario. The percentage relative bias (PRB), root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. The results demonstrate that available IPD should always be included in a conventional meta-analysis using summary level data as they would significantly increased the accuracy of the estimates.On the other hand, if more than 80% of the available data are at IPD level, including the AD does not provide significant differences in terms of accuracy of the estimates. Additionally, combining the IPD and AD has moderating effects on the biasness of the estimates of the treatment effects as the IPD tends to overestimate the treatment effects, while the AD has the tendency to produce underestimated effect estimates. These results may provide some guide in deciding if significant benefit is gained by pooling the two levels of data when conducting meta-analysis.

A Simple Epidemiological Model for Typhoid with Saturated Incidence Rate and Treatment Effect

Typhoid fever is a communicable disease, found only in man and occurs due to systemic infection mainly by Salmonella typhi organism. The disease is endemic in many developing countries and remains a substantial public health problem despite recent progress in water and sanitation coverage. Globally, it is estimated that typhoid causes over 16 million cases of illness each year, resulting in over 600,000 deaths. A mathematical model for assessing the impact of educational campaigns on controlling the transmission dynamics of typhoid in the community, has been formulated and analyzed. The reproductive number has been computed. Stability of the model steady-states has been examined. The impact of educational campaigns on controlling the transmission dynamics of typhoid has been discussed through the basic reproductive number and numerical simulations. At its best the study suggests that targeted education campaigns, which are effective at stopping transmission of typhoid more than 40% of the time, will be highly effective at controlling the disease in the community. 

The Effect of Saturates on Rheological and Aging Characteristics of Bitumen

According to Rostler method (ASTM D 2006), saturates content of bitumen is determined based on its reactivity to sulphuric acid. While Corbett method (ASTM D 4124) based on its polarity level. This paper presents results from the study on the effect of saturates content determined by two different fractionation methods on the rheological and aging characteristics of bitumen. The result indicated that the increment of saturates content tended to reduce all the rheological characteristics concerned. Bitumen became less elastic, less viscous, and less resistant to plastic deformation, but became more resistant to fatigue cracking. After short and long term aging process, the treatment effect coefficients of saturates decreased, saturates became thicker due to aging process. This study concludes that saturates is not really stable or reactive in aging process. Therefore, the reactivity of saturates should be considered in bitumen aging index

Comparative Study of Transformed and Concealed Data in Experimental Designs and Analyses

This paper presents the comparative study of coded data methods for finding the benefit of concealing the natural data which is the mercantile secret. Influential parameters of the number of replicates (rep), treatment effects (τ) and standard deviation (σ) against the efficiency of each transformation method are investigated. The experimental data are generated via computer simulations under the specified condition of the process with the completely randomized design (CRD). Three ways of data transformation consist of Box-Cox, arcsine and logit methods. The difference values of F statistic between coded data and natural data (Fc-Fn) and hypothesis testing results were determined. The experimental results indicate that the Box-Cox results are significantly different from natural data in cases of smaller levels of replicates and seem to be improper when the parameter of minus lambda has been assigned. On the other hand, arcsine and logit transformations are more robust and obviously, provide more precise numerical results. In addition, the alternate ways to select the lambda in the power transformation are also offered to achieve much more appropriate outcomes.

Quantifying and Adjusting the Effects of Publication Bias in Continuous Meta-Analysis

This study uses simulated meta-analysis to assess the effects of publication bias on meta-analysis estimates and to evaluate the efficacy of the trim and fill method in adjusting for these biases. The estimated effect sizes and the standard error were evaluated in terms of the statistical bias and the coverage probability. The results demonstrate that if publication bias is not adjusted it could lead to up to 40% bias in the treatment effect estimates. Utilization of the trim and fill method could reduce the bias in the overall estimate by more than half. The method is optimum in presence of moderate underlying bias but has minimal effects in presence of low and severe publication bias. Additionally, the trim and fill method improves the coverage probability by more than half when subjected to the same level of publication bias as those of the unadjusted data. The method however tends to produce false positive results and will incorrectly adjust the data for publication bias up to 45 % of the time. Nonetheless, the bias introduced into the estimates due to this adjustment is minimal

Numerical Simulation of Wall Treatment Effects on the Micro-Scale Combustion

To understand working features of a micro combustor, a computer code has been developed to study combustion of hydrogen–air mixture in a series of chambers with same shape aspect ratio but various dimensions from millimeter to micrometer level. The prepared algorithm and the computer code are capable of modeling mixture effects in different fluid flows including chemical reactions, viscous and mass diffusion effects. The effect of various heat transfer conditions at chamber wall, e.g. adiabatic wall, with heat loss and heat conduction within the wall, on the combustion is analyzed. These thermal conditions have strong effects on the combustion especially when the chamber dimension goes smaller and the ratio of surface area to volume becomes larger. Both factors, such as larger heat loss through the chamber wall and smaller chamber dimension size, may lead to the thermal quenching of micro-scale combustion. Through such systematic numerical analysis, a proper operation space for the micro-combustor is suggested, which may be used as the guideline for microcombustor design. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the micro-combustor design, optimization and performance analysis.

The Effects of Feeding Raw Fiber Concentrate on Growth Performance and Blood Metabolites of Suckling Holstein Calves

Sixteen female Holstein calves allocated in three treatments including: 1: control, 2: fed raw fiber concentrate (RFC) for 45 days and 3: fed RFC for 90 days. RFC supplement (Vitacel® 200) was added to milk immediately before feeding (10 g/L milk). Withers height and body weights of calves were measured monthly. Individual dry matter intake was recorded daily. Blood samples were taken monthly. The result showed that calves consumed RFC had significantly greater weaning and final body weight. Treatment effect on dry matter intake was not significant (p>0.05). Calves fed RFC had better feed efficiency. Withers height of calves fed RFC were taller than the control group (p

Characterization for Post-treatment Effect of Bagasse Ash for Silica Extraction

Utilization of bagasse ash for silica sources is one of the most common application for agricultural wastes and valuable biomass byproducts in sugar milling. The high percentage silica content from bagasse ash was used as silica source for sodium silicate solution. Different heating temperature, time and acid treatment were studies for silica extraction. The silica was characterized using various techniques including X-ray fluorescence, X-ray diffraction, Scanning electron microscopy, and Fourier Transform Infrared Spectroscopy method,. The synthesis conditions were optimized to obtain the bagasse ash with the maximum silica content. The silica content of 91.57 percent was achieved from heating of bagasse ash at 600°C for 3 hours under oxygen feeding and HCl treatment. The result can be used as value added for bagasse ash utilization and minimize the environmental impact of disposal problems.

Kernel Matching versus Inverse Probability Weighting: A Comparative Study

Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.