Environmental parameters and incidence of white spot disease in Penaeus monodon (Fab.) farming

An investigation was carried out to monitor management practices and to find out whether there is any relationship with occurrence of deadly white spot disease and environmental parameters. Three semi-intensive and a improved traditional shrimp farms were selected in which mass mortality of shrimp (Penaeus monodon) by white spot disease occurred previously. The farms were situated at two different geographical locations. Two ponds from each farm at random were selected for the study. Out of eight investigated ponds, 6 ponds in three farms were affected by the disease during investigation period. The non-affected ponds had relatively lower stocking density, lightly different management practice and were located at different geographical area. There was no significant variation in water quality parameters among the affected and non-affected ponds. No significant variations were recorded in pond preparation, source of Post Larvae (PL), water and feed management among the affected and non-affected ponds. The observation indicated that pond micro-organisms in a farm may not the only cause of the disease but some external factors also might be responsible for the outbreak of this disease

Identifying Unnatural Variation in Precision Rotational Part Manufacturing

In the manufacturing industry, it is well known that in-process variation is a major contributor to poor quality products. In order to fabricate a precise part, the source of unnatural variation (UV) needed to be properly identified, monitored and controlled while the process is running. In relation to this issue, this study aims to identify the error root causes of UV in bivariate process associated with statistical process control (SPC) chart patterns. In research methodology, in-process variation in manufacturing roller head component was discussed systematically based on real product of roller head, computer aided design (CAD) and statistical process control (SPC) chart patterns. Initially, the CAD software was used to model a precise rotational part, and to analyse the cause of UV. Then, the programming software was used to generate the artificial SPC data streams based on an established mathematical model. Data generation also involved linear correlation between two dependent variables (bivariate). The outcome of this study would be helpful for industrial practitioners as a database when applying SPC for monitoring bivariate process

Effect of decapsulation on viability and hatching performance of Artemia cysts at different salinity levels

Artemia cysts were produced from the traditional solar salt works of Bangladesh through different fertilization treatments were tested for viability and hatching performance in different forms, such as processed and preserved, processed and decapsulated and unprocessed and undecapsulated. Decapsulated cysts performed maximum hatching (86.0%) in 20ppt salinity during 48 hours of incubation. The hatching percentage by the unprocessed and undecapsulated cysts were very low (12.0- 18.7%) in all the tested salinity grades

Thermal Radiation and Thermal Diffusion for Soret and Dufour’s Effects on MHD Flow over Rotating Infinite Disk

In general, the thermal radiation and thermal diffusion effects over an electrically conducting, Newtonian fluid in a steady laminar magnetohydrodynamic convective flow over a porous rotating infinite disk with the consideration of heat and mass transfer in the presence of Soret and Dufour’s diffusion effects have been obtained and studied numerically. The governing continuity, momentum, energy and concentration equations are converted into a system of non-linear ordinary differential equations by means of similarity transformation. The resulting system of coupled non-linear ordinary differential equations is solved numerically. In this chapter, numerical results were presented for velocity (radial, axial and tangential), temperature, concentration and pressure profiles for different parameters of the problem Also, the effects of the pertinent parameters on the radial and tangential skin friction, the rate of heat and mass transfer are obtained and discussed numerically and illustrated graphically

Virtual Chemical Sensor For Classification Of Herb � Orthosiphon Stamineus According To Its Geographical Origin.

Herbal medicine is an important part of health care to a majority of the world's population

Heat Transfer and Thermal Radiation at a General Three-Dimensional in a Nanofluid through a Porous Medium

In this chapter, the magnetohydrodynamic effects on heat transfer and thermal radiation at a stagnation point flowing in a nanofluid containing different types of nanoparticles namely, copper (Cu), alumina (Al2O3) and titania (TiO2) through a porous medium have been investigated numerically. By using appropriate transformation for velocity and temperature into a set of non-linear coupled ordinary differential equations which are solved numerically. Numerical results are presented for velocity and temperature profiles for different parameters of the problem. Also, the effects of the pertinent parameters on the skin friction and the heat fluxes are obtained and discussed numerically and illustrated graphically

Control Chart Pattern Recognition Using Small Window Size for Identifying Bivariate Process Mean Shifts

There are many traits in the manufacturing technology to assure the quality of products. One of the current practices aims for monitoring the in-process quality of small-lot production using Statistical Process Control (SPC), which requires small samples or small window sizes. In this study, the recognition performance of bivariate SPC pattern recognition scheme was investigated when dealing with small window sizes (less than 24). The framework of the scheme was constructed using an artificial neural network recognizer. The simulated SPC samples in different window sizes (8 ~ 24) and different change points (fixed and varies) were generated to study the recognition performance of the scheme based on mean square error (MSE) and classification accuracy (CA) measures. Two main findings have been suggested: (i) the scheme was superior when recognizing shift patterns with various change points compared to the shift patterns with fixed change point, with lower MSE and higher CA results, (ii) the scheme was more difficult to recognize smaller window size patterns with increasing MSE and decreasing CA trends, since these patterns provided insufficient information of unnatural variation. The outcome of this study would be helpful for industrial practitioners towards applying SPC for small-lot-production. &nbsp

Control Chart Pattern Recognition Using Small Window Size for Identifying Bivariate Process Mean Shifts

There are many traits in the manufacturing technology to assure the quality of products. One of the current practices aims for monitoring the in-process quality of small-lot production using Statistical Process Control (SPC), which requires small samples or small window sizes. In this study, the recognition performance of bivariate SPC pattern recognition scheme was investigated when dealing with small window sizes (less than 24). The framework of the scheme was constructed using an artificial neural network recognizer. The simulated SPC samples in different window sizes (8 ~ 24) and different change points (fixed and varies) were generated to study the recognition performance of the scheme based on mean square error (MSE) and classification accuracy (CA) measures. Two main findings have been suggested: (i) the scheme was superior when recognizing shift patterns with various change points compared to the shift patterns with fixed change point, with lower MSE and higher CA results, (ii) the scheme was more difficult to recognize smaller window size patterns with increasing MSE and decreasing CA trends, since these patterns provided insufficient information of unnatural variation. The outcome of this study would be helpful for industrial practitioners towards applying SPC for small-lot-production. &nbsp

Twenty-five years of global research publications trends of novel coronavirus: A scientometrics assessment

The study aimed to identify the trends and characteristics of the publication on the novel coronavirus. A total of 2661 publications from Scopus downloaded in the bib.text andCVSformat for 25 years to analyze by using scientometrics analysis software, namely Bibliometrix and Vosviewer. The results show that there is very little research conducted before 2002, but exponentially increased after 2003 and 2020 shows the highest number of publications (779). The result reveals that the 1806 publication is in the form of research articles, i.e., 68%. University Of Hong Kong has produced the highest publication, i.e., 362. The Journal of Virology (JIF = 4.324) has ranked1 interms of the number of total publications (173), total citation (9618), g index (90), and h index (57) respectively. Yuen KY found as the prolific author (75) and has more collaborative publication (62) as well. The author\u27s keyword coronavirus considered the more reliable keyword. The most cited (TC = 2194) article is A Novel Coronavirus Associated with Severe Acute Respiratory Syndrome by Ksiazek TG (2003). The study is beneficial for researchers who are currently doing or planning research on coronavirus

Oxalate and silica contents of seven varieties of Napier grass (Pennisetum purpureum)

Oxalate and silica are considered antinutrients. Large quantities of oxalate and silica in plants can interfere with the uptake of essential minerals in ruminants. Therefore, the aim of this study was to compare the total silica and oxalate contents of seven varieties of Napier grass to find out which is best for cultivation. Taiwan, Zanzibar, Pakchong, Purple, Kobe, Indian, and Dwarf Napier grass were grown in a completely randomized design with three replications to determine their soluble oxalate, total oxalate, and silica contents. Plants were harvested at two months of plant maturity. Whole plant of the Dwarf Napier grass contained significantly higher soluble oxalate content than tall varieties. Total oxalate content in whole plant differed significantly among varieties. Dwarf showed the highest total oxalate content (3.23% dry matter (DM)) followed by Kobe (2.61%), Zanzibar (2.60%), Purple (2.44%), Taiwan (2.43%), Indian (2.15%), and Pakchong (1.95%). Regardless of variety, leaf tissue contained significantly higher soluble oxalate and total oxalate than stem tissue. There were no differences in silica content among them. In conclusion, the tall varieties could produce lower levels of soluble oxalate than the Dwarf variety, whereas silica content might not vary among them.Keywords: botanical fractions, mineral bioavailability, ruminan