Manufacturing Of Robust Natural Fiber Preforms Utilizing Bacterial Cellulose as Binder

We present a novel method of manufacturing rigid and robust short natural fiber preforms using a papermaking process. Bacterial cellulose acts simultaneously as the binder for the loose fibers and provides rigidity to the fiber preforms. These preforms can be infused with a resin to produce truly green hierarchical composites

Biostabilised icosahedral gold nanoparticles: synthesis, cyclic voltammetric studies and catalytic activity towards 4-nitrophenol reduction

A green and cost-effective biosynthetic approach for the preparation of icosahedral gold nanoparticles (AuNPs) using an aqueous leaf extract of Polygonum minus as reducing and stabilising factor is described. The reduction of Au3+ ions to elemental Au rapidly occurred and is completed within 20 minutes at room temperature. The size of the nanoparticles is highly sensitive to the AuCl4 −/leaf extract concentration ratio and pH. Transmission electron microscopy and X-ray diffraction data indicated that the nanoparticles were in a crystalline shape (face-centred cubic), mostly icosahedral and nearly monodispersed with an average size of 23 nm. Cyclic voltammetric studies suggested that flavonoids, such as quercetin and myricetin present in the leaf extract had a tendency to donate electrons to Au3+ ions and the formation of elemental Au was possible due to the transfer of electrons from these flavonoids to Au3+ ions. Infrared absorption of the AuNPs and the leaf extract revealed that the oxidised (quinone) form of quercetin and myricetin were presumably the main stabilising agents in the formation of stable nanoparticles. The present biosynthesis of AuNPs was simple, rapid, cost-effective and environmentally friendly. The newly prepared biostabilised icosahedral AuNPs show good catalytic activity in the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP)

Virtual Collaborative R&D Teams in Malaysia Manufacturing SMEs

This paper presents the results of empirical research conducted during March to September 2009. The study focused on the influence of virtual research and development (R&D) teams within Malaysian manufacturing small and medium sized enterprises (SMEs). The specific objective of the study is better understanding of the application of collaborative technologies in business, to find the effective factors to assist SMEs to remain competitive in the future. The paper stresses to find an answer for a question “Is there any relationship between company size, Internet connection facility and virtuality?”. The survey data shows SMEs are now technologically capable of performing the virtual collaborative team, but the infrastructure usage is less. SMEs now have the necessary technology to begin the implementation process of collaboration tools to reduce research and development (R&D) time, costs and increase productivity. So, the manager of R&D should take the potentials of virtual teams into account

Embedded Scale United Moment Invariant for Identification of Handwriting Individuality

Past few years, a lot of research on moment functions have been explored in pattern recognition. Several new techniques have been investigated to improve conventional regular moment by proposing the scaling factor of geometrical function. In this paper, integrated scaling formulations of Aspect Invariant Moment and Higher Order Scaling Invariant with United Moment Invariant are presented in Writer Identification to seek the invarianceness of authorship or individuality of handwriting perseverance. Mathematical proving and results of computer simulations are included to verify the validity of the proposed technique in identifying eccentricity of the author in Writer Identification

DISCRETIZATION OF INTEGRATED MOMENT INVARIANTS FOR WRITER IDENTIFICATION

Conservative regular moments have been proven to exhibit some shortcomings in the original formulations of moment functions in terms of scaling factor. Hence, an incorporated scaling factor of geometric functions into United Moment Invariant function is proposed for mining the feature of unconstrained words. Subsequently, the discrete proposed features undertake discretization procedure prior to classification for better feature representation and splendid classification accuracy. Collectively, discrete values are finite intervals in a continuous spectrum of values and well known to play important roles in data mining and knowledge discovery. Many induction algorithms found in the literature requires that training data contains only discrete features and some works better on discretized data; in particular rule based approaches like rough sets. Hence, in this study, an integrated scaling formulation of Aspect Scaling Invariant is presented in Writer Identification to hunt for the individuality perseverance. Successive exploration is executed to investigate for the suitability of discretization techniques in probing the issues of writer authorship. Mathematical proving and results of computer simulations are embraced to attest the feasibility of the proposed technique in Writer Identification. The results disclose that the proposed discretized invariants reveal 99% accuracy of classification by using 3520 training data and 880 testing data

Embedded Scale United Moment Invariant for Identification of Handwriting Individuality

Past few years, a lot of research on moment functions have been explored in pattern recognition. Several new techniques have been investigated to improve conventional regular moment by proposing the scaling factor of geometrical function. In this paper, integrated scaling formulations of Aspect Invariant Moment and Higher Order Scaling Invariant with United Moment Invariant are presented in Writer Identification to seek the invarianceness of authorship or individuality of handwriting perseverance. Mathematical proving and results of computer simulations are included to verify the validity of the proposed technique in identifying eccentricity of the author in Writer Identification

Rhizobacteria as bioenhancer and biofertilizer for growth and yield of banana (Musa spp. cv. ‘Berangan’)

Banana, an important fruit crop, requires high amounts of fertilizers for commercial cultivation, which is costly and can be hazardous to the environment when used excessively. Inoculations of plant growth promoting rhizobacteria (PGPR) have been shown to produce beneficial effects through growth stimulation in legumes and cereals, and an attempt has been made to use rhizobacteria in bananas. Three experiments were conducted to observe the effects of plant growth promoting rhizobacteria (PGPR) inoculation on root stimulation and colonization, nutrient absorption, growth and yield of bananas (Musa spp. cv. ‘Berangan’, AA type). The results showed that inoculation together with 33% N improved the bioenhancing activity by increasing root and shoot growth, and photosynthetic rate. The PGPR inoculation with 33% N-fertilizer also increased the Ca uptake capacity resulting in higher Ca concentration in root, corm and pulp but increased the Mg concentration in the root only. In addition, the total accumulation of nutrients was heavily influenced by PGPR inoculation due to enhanced root proliferation. The PGPR inoculation greatly increased the bunch yield (35–51%). The strains Sp7 and UPMB10 were evaluated for their N2 fixing capacities in association with banana roots by 15N isotopic dilution technique and acetylene reduction assay (ARA). The results conclusively showed that roots of PGPR-inoculated plants fixed N2 and produced higher ARA values and inoculated plants together with the least N-fertilizer supply showed the highest amount of nitrogen derived from atmosphere (Ndfa). The findings from the above studies demonstrated that PGPR strains (Sp7 and UPMB 10) inoculation with minimal N-fertilizer supply are effective as a bioenhancer for increasing plant growth, nutrient uptake and yield of bananas

Selection of classification models from repository of model for water quality dataset

This paper proposes a new technique, Model Selection Technique (MST) for selection andranking of models from the repository of models by combining three performance measures(Acc, TPR and TNR). This technique provides weightage to each performance measure to findthe most suitable model from the repository of models. A number of classification modelshave been generated to classify water quality using the most significant features andclassifiers such as J48, JRip and BayesNet. To validate this technique proposed, the waterquality dataset of Kinta River was used in this research. The results demonstrate that theFunction classifier is the optimal model with the most outstanding accuracy of 97.02%, TPR =0.96 and TNR = 0.98. In conclusion, MST is able to find the most relevant model from therepository of models by using weights in classifying the water quality dataset.Keywords: selection of models; water quality; classification model; models repository

Voluntary Fasting to Control Post-Ramadan Weight Gain among Overweight and Obese Women

Objectives: This study aimed to examine the effectiveness of an Islamic voluntary fasting intervention to control post-Ramadan weight gain. Methods: This study was conducted between July and November 2011. Two weight loss intervention programmes were developed and implemented among groups of overweight or obese Malay women living in the Malaysian cities of Putrajaya and Seremban: a standard programme promoting control of food intake according to national dietary guidelines (group B) and a faith-based programme promoting voluntary fasting in addition to the standard programme (group A). Participants’ dietary practices (i.e., voluntary fasting practices, frequency of fruit/vegetable consumption per week and quantity of carbohydrates/protein consumed per day), body mass index (BMI), blood pressure, fasting blood high-density lipoprotein cholesterol (HDL-C) and total cholesterol (TC):HDL-C ratio were assessed before Ramadan and three months post-Ramadan. Results: Voluntary fasting practices increased only in group A (P <0.01). Additionally, the quantity of protein/carbohydrates consumed per day, mean diastolic pressure and TC:HDL-C ratio decreased only in group A (P <0.01, 0.05, 0.02 and <0.01, respectively). Frequency of fruit/vegetable consumption per week, as well as HDL-C levels, increased only in group A (P = 0.03 and <0.01, respectively). Although changes in BMI between the groups was not significant (P = 0.08), BMI decrease among participants in group A was significant (P <0.01). Conclusion: Control of post-Ramadan weight gain was more evident in the faith-based intervention group. Healthcare providers should consider faith-based interventions to encourage weight loss during Ramadan and to prevent post-Ramadan weight gain among patients

Study of heterosis in Bangladeshi chilli (Capsicum annuum L.) landraces

Chilli is an important cash crop in Bangladesh but average yield is very low (0.89 t ha-1) and genetic potentiality of Bangladeshi chilli landraces for hybrid variety development has not been evaluated. The objective of this study was to find out heterotic behavior following Gardner and Eberhart model (1966) II. Six different homozygous divergent parents CCA 2, CCA 5, BARI Morich 1, CCA 11, CCA 15 and CCA 19 were used to estimate heterosis. A significant amount of heterosis was present in yield and yield contributing traits. Estimate of variety heterosis for yield per plant was significantly positive in CCA 5 and BARI Morich 1. In BARI Morich 1, the significant and positive variety heterosis for yield per plant was associated with significant and positive estimates of heterosis for number of fruits per plant and number of seeds per fruit, suggesting that these yield traits contributed to the final heterosis manifested through yield. Indigenous×exotic crosses showed significant amount of heterosis. It is possible to emphasize indigenous×exotic crosses for good fruit yield, particularly to be used as commercial hybrids. Hybrids of BARI Morich 1×CCA 19 and CCA 5×BARI Morich 1 showed better performance