Indigenous cellulolytic and hemicellulolytic bacteria enhanced rapid co-composting of lignocellulose oil palm empty fruit bunch with palm oil mill effluent anaerobic sludge.

The composting of lignocellulosic oil palm empty fruit bunch (OPEFB) with continuous addition of palm oil mill (POME) anaerobic sludge which contained nutrients and indigenous microbes was studied. In comparison to the conventional OPEFB composting which took 60-90. days, the rapid composting in this study can be completed in 40. days with final C/N ratio of 12.4 and nitrogen (2.5%), phosphorus (1.4%), and potassium (2.8%), respectively. Twenty-seven cellulolytic bacterial strains of which 23 strains were closely related to Bacillus subtilis, Bacillus firmus, Thermobifida fusca, Thermomonospora spp., Cellulomonas sp., Ureibacillus thermosphaericus, Paenibacillus barengoltzii, Paenibacillus campinasensis, Geobacillus thermodenitrificans, Pseudoxanthomonas byssovorax which were known as lignocellulose degrading bacteria and commonly involved in lignocellulose degradation. Four isolated strains related to Exiguobacterium acetylicum and Rhizobium sp., with cellulolytic and hemicellulolytic activities. The rapid composting period achieved in this study can thus be attributed to the naturally occurring cellulolytic and hemicellulolytic strains identified

Feature selection algorithms for Malaysian dengue outbreak detection model

Dengue fever is considered as one of the most common mosquito borne diseases worldwide. Dengue outbreak detection can be very useful in terms of practical efforts to overcome the rapid spread of the disease by providing the knowledge to predict the next outbreak occurrence. Many studies have been conducted to model and predict dengue outbreak using different data mining techniques. This research aimed to identify the best features that lead to better predictive accuracy of dengue outbreaks using three different feature selection algorithms; particle swarm optimization (PSO), genetic algorithm (GA) and rank search (RS). Based on the selected features, three predictive modeling techniques (J48, DTNB and Naive Bayes) were applied for dengue outbreak detection. The dataset used in this research was obtained from the Public Health Department, Seremban, Negeri Sembilan, Malaysia. The experimental results showed that the predictive accuracy was improved by applying feature selection process before the predictive modeling process. The study also showed the set of features to represent dengue outbreak detection for Malaysian health agencies

"I employed my own strategy": Exploring primary headteachers' organisational and professional socialisations

Purpose - The main purpose of this study was to explore primary headteachers' perceptions of their professional and organisational socialisation within their novice years as school leaders. There is a lack of studies exploring primary headteachers' socialisation within the Malaysian primary education context. Methodology - A total of nine primary headteachers from three states were purposely selected and interviewed to obtain their perceptions on the professional socialisation they received before and after their appointment and the strategies that they employed within their organisational socialisation process. Findings - The study revealed that the primary headteachers employed their own organisational socialisation strategies in order to be accepted as a new member of the school. These were relatively diverse but accorded with their school's values and culture. However, in terms of their professional socialisation, there were various findings: some mentioned the lack of support programs while others acknowledged receiving quite helpful programmes within their initial years of headship. The findings and the implications for the improvement of primary headteachers' socialisation are discussed. Significance - This study provides supplementary literature that explores primary headteachers' organisational and professional socialisation within the Malaysian schooling context. This study notes some practical and theoretical implications for improving the prospective headteachers' training and their leadership development which aim to enhance the leadership qualities of future primary school leaders

Periodic addition of anaerobic sludge enhanced the lignocellulosic degradation rate during co-composting of oil palm biomass

The main objective of this work was to investigate the effects of the controlled periodic addition of anaerobic sludge during composting to increase amount of microbial DNA, which appears to be correlated to soluble sugar content which may relate to rate of lignocellulosic degradation. In this study, the composting of pressed-shredded oil palm empty fruit bunch with the periodic addition of palm oil mill effluent anaerobic sludge for moisture control in a newly designed in-vessel type composter was carried out. A control experiment was also conducted over the same period but with the periodic addition of water for moisture control instead of the anaerobic sludge. The lignocellulosic composition and the reducing sugar content were determined via fibre analysis and the spectrophotometric method respectively. The bacterial profile throughout the composting process was quantified by using qPCR. The growth of bacteria reached its peak at 48°C and the degradation of lignocellulose was highest during the thermophilic stage. The highest content of reducing sugar coincided with the highest degradation rate of lignocellulose and the highest DNA copy number during the thermophilic stage. Under the controlled experimental condition of increasing the microbial community, the composting was accelerated to 2.07% OM degradation per day compared to the water addition control at 0.60% OM per day

Enhanced biogas production from palm oil mill effluent supplemented with untreated oil palm empty fruit bunch biomass with a change in the microbial community

The biogas and biomethane production in a 50 litre closed stirred tank anaerobic bioreactor treating palm oil mill effluent (POME) supplemented with oil palm biomass in the form of oil palm empty fruit bunch (OPEFB) under mesophilic condition was evaluated. With OPEFB supplementation, the biogas and biomethane generation increased by 63% and 52%, respectively. During this process, we found changes in the OPEFB morphology and microbial community through microbiota analysis using 16S rRNA gene clone library method, after OPEFB was added, suggesting that the increased biogas and biomethane production would be due to enhanced lignocellulosic biomass degradation

Analysis of ANN and Fuzzy Logic Dynamic Modelling to Control the Wrist Exoskeleton

Human intention has long been a primary emphasis in the field of electromyography (EMG) research. This being considered, the movement of the exoskeleton hand can be accurately predicted based on the user's preferences. The EMG is a nonlinear signal formed by muscle contractions as the human hand moves and easily captured noise signal from its surroundings. Due to this fact, this study aims to estimate wrist desired velocity based on EMG signals using ANN and FL mapping methods. The output was derived using EMG signals and wrist position were directly proportional to control wrist desired velocity. Ten male subjects, ranging in age from 21 to 40, supplied EMG signal data set used for estimating the output in single and double muscles experiments. To validate the performance, a physical model of an exoskeleton hand was created using Sim-mechanics program tool. The ANN used Levenberg training method with 1 hidden layer and 10 neurons, while FL used a triangular membership function to represent muscles contraction signals amplitude at different MVC levels for each wrist position. As a result, PID was substituted to compensate fluctuation of mapping outputs, resulting in a smoother signal reading while improving the estimation of wrist desired velocity performance. As a conclusion, ANN compensates for complex nonlinear input to estimate output, but it works best with large data sets. FL allowed designers to design rules based on their knowledge, but the system will struggle due to the large number of inputs. Based on the results achieved, FL was able to show a distinct separation of wrist desired velocity hand movement when compared to ANN for similar testing datasets due to the decision making based on rules setting setup by the designer

Optimizing processing parameters and fiber size for kenaf fiber reinforced thermoplastic polyurethane composite

In this study, composite of Themoplastic polyurethane (TPU) reinforced with short fiber (Hibiscus Cannabinus) kenaf (KF) were prepared via melt blending method using Haake Polydrive R600 internal mixer. Effect of various processing temperatures, times and speeds on tensile strength was studied, together with effect of various fiber sizes on tensile, flexural properties and impact strength. Optimum blending parameters were 190°C, 11 min, and 40 rpm for temperature, time and speed, respectively. Using the optimum processing parameters TPU-KF composites with different fiber sizes were prepared. Composite sheets were prepared by hot press machine at 190 °C for 10 min. Five samples were cut from the composite sheet. Mean value was taken for each composite according to ASTM standards. Tensile and flexural strength were best for fibers between 125-300 micron. Impact strength showed an increasing trend with increasing fiber size

Utilization of glucose recovered by phase separation system from acid-hydrolysed oil palm empty fruit bunch for bioethanol production

Oil palm empty fruit bunch (OPEFB) is one the most abundant lignocellulosic wastes produced throughoutthe year in the palm oil industry. A new process of separating lignocellulose components after acid hydrolysis(known as phase separation system) has been previously developed, by which lignin and carbohydrate can becompletely and rapidly separated in 60 minutes between 25 and 30°C. In this process, cellulose is completelyhydrolyzed to oligosaccharides and remains in the acid phase. The maximum glucose yield of 53.8% wasobtained by hydrolysis, with 4% acid after autoclaving at 121°C for 5 minutes. This work focused on theseparation of monosaccharide (glucose) from cellulose fraction, which was subsequently used as a substratefor ethanol production. For this purpose, different types of nitrogen sources were evaluated, with yeast extractas the best nitrogen source (93% of theoretical yield) as compared to palm oil mill effluent (POME) andsludge powder for the growth of acid tolerant Saccharomyces cerevisiae ATCC 26602. Batch and repeatedbatch fermentation of S. cerevisiae ATCC 26602 using OPEFB hydrolysate gave 0.46 g glucose g ethanol-1,representing 87% of theoretical yield with a productivity of about 0.82 g-1 l-1 h-1 and 0.48 g glucose g ethanol-1,representing 89% of theoretical yield with productivity of about 2.79 g-1 l-1 h-1, respectively

Fatigue life for type 316L stainless steel under cyclic loading

The paper presents the determination of fatigue life of 316L stainless steel at room temperature. Plenty of steel in the world has been investigated for a lot of application in the science and technology market. The mechanisms of fatigue of 316L stainless steels were studied and investigated. Fatigue tests of specimens were performed in accordance with ASTM E466-96. The fatigue tests were performed in constant load amplitude, constant frequency of 5 Hz with load ratio R=0.1. Fracture surface of specimens were examined by using Scanning Electron Microscope (SEM). The results showed that the endurance fatigue limit of 316L stainless steel was 146.45 MPa