Colchicine induced polyploidy in coriander (Coriandrum sativum L.)

The aim of this study was to find a suitable treatment combination that would effectively induce polyploidy in Coriander. In this study, colchicine concentrations and treatment durations were examined for improving the induction of polyploidy. The combinations of three colchicine concentrations such as 0.1%, 0.2% and 0.3% for 3 hrs per day for two to three days were tested in coriander. Three tetraploids were obtained in 0.2% colchicine treated population. The treatment of colchicine (cotton swab method) seedling with 0.2% for 3 days was suitable for induction of chromosome doubling. The control plant showed eleven bivalents (2n=2x=22) and polyploid plant showed twenty two bivalents (2n=4x=44) at diakinesis/metaphase-I in most of the PMCs. Anaphase-I distribution of chromosomes was normal (11:11) in control and in tetraploids distribution of chromosomes was (22:22) at each poles. In contrast with the normal plants, those treated by colchicine treatment often showed changes in height and width, in thickness of branches, in size, shape, texture of leaves, flowers, size of fruits and seed setting

Mannerisms of Millennials: Why are they different?

Differences in attitudes and mannerisms of the millennials and the older generation could result in intergenerational conflicts. This study aims to determine the definitions of good mannerisms as perceived by the two different generations and to identify the factors that contribute to the mannerisms and characteristics of the millennials. Using a non-experimental design, a questionnaire was distributed to 400 respondents. The responses by the millennials differed in some aspects from the older generation. Nevertheless, both groups agreed that the lack of a good upbringing and social media influences were the primary reasons for the lack of good mannerisms among millennials. Keywords: Millennials, Mannerism, Values, Characteristics eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians), and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i21.369

Gaussian process methodology for multi-frequency marine controlled-source electromagnetic profile estimation in isotropic medium

The marine controlled-source electromagnetic (CSEM) technique is an application of electromagnetic (EM) waves to image the electrical resistivity of the subsurface underneath the seabed. The modeling of marine CSEM is a crucial and time-consuming task due to the complexity of its mathematical equations. Hence, high computational cost is incurred to solve the linear systems, especially for high-dimensional models. Addressing these problems, we propose Gaussian process (GP) calibrated with computer experiment outputs to estimate multi-frequency marine CSEM profiles at various hydrocarbon depths. This methodology utilizes prior information to provide beneficial EM profiles with uncertainty quantification in terms of variance (95% confidence interval). In this paper, prior marine CSEM information was generated through Computer Simulation Technology (CST) software at various observed hydrocarbon depths (250–2750 m with an increment of 250 m each) and different transmission frequencies (0.125, 0.25, and 0.5 Hz). A two-dimensional (2D) forward GP model was developed for every frequency by utilizing the marine CSEM information. From the results, the uncertainty measurement showed that the estimates were close to the mean. For model validation, the calculated root mean square error (RMSE) and coefficient of variation (CV) proved in good agreement between the computer output and the estimated EM profile at unobserved hydrocarbon depths

Advancement in biomarker based effective diagnosis of neonatal sepsis

Neonatal sepsis is considered as alarming medical emergency and becomes the common global reason of neonatal mortality. Non-specific symptoms and limitations of conventional diagnostic methods for neonatal sepsis mandate fast and reliable method to diagnose disease for point of care application. Recently, disease specific biomarkers have gained interest for rapid diagnosis that led to the development of electrochemical biosensor with enhanced specificity, sensitivity, cost-effectiveness and user-friendliness. Other than conventional biomarker C-reactive protein to diagnose neonatal sepsis, several potential biomarkers including Procalcitonin (PCT), Serum amyloid A (SAA) and other candidates are extensively investigated. The present review provides insights on advancements and diagnostic abilities of protein and nucleotide based biomarkers with their incorporation in developing electrochemical biosensors by employing novel fabrication strategies. This review provides an overview of most promising biomarker and its capability for neonatal sepsis diagnosis to fulfil future demand to develop electrochemical biosensor for point-of-care applications.</p

The arithmetic mean iterative method for solving 2D Helmholtz equation

In this paper, application of the Arithmetic Mean (AM) iterative method is extended by solving second order finite difference algebraic equations. The performance of AM method in solving second order finite difference algebraic equations is comparatively studied by their application on two-dimensional Helmholtz equation. Numerical results of AM method in solving two test problems are included and compared with the standard Gauss-Seidel (GS) method. Based on the numerical results obtained, the results show that AM method is better than GS method in the sense of number of iterations and CPU time

Numerical solutions of linear Fredholm Integral Equations using half-sweep arithmetic mean method

In this paper, performance of the 2-Point Half-Sweep Explicit Group (2-HSEG) iterative method with first order composite closed Newton-Cotes quadrature scheme for solving second kind linear Fredholm integral equations is investigated. The formulation and implementation of the method are described. Furthermore, numerical results of test problems are also presented to verify the performance of the method compared to 2-Point Full-Sweep Explicit Group (2-FSEG) method. From the numerical results obtained, it is noticeable that the 2-HSEG method is superior to 2-FSEG method, especially in terms of computational time

Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I) and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βt and a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4.7% each day with a decreased capacity of 40%. For 7-day and 14-day projections, the modified SIR model accurately predicted I total, I and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19