DFT and G4 results reveal that cations display the following trends in imparting its positive charge to acrylonitrile; H⁺ > Li⁺ > Na⁺ > K⁺ for group I and Be²⁺ > Mg²⁺ > Ca²⁺ for group II. Solvation by water molecules and interaction with cation make the cyano bond more polarized and exhibits ketene-imine character. Bond order in nitrile-cation complexes has been predicted based on the s character of the covalent bond orbitals. Mulliken, CHELPG, and NPA charges are in good agreement in predicting positive charge buildup and GIAO nuclear deshileding on C1. G4 enthalpies show that Mg²⁺ is more strongly bound to acrylonitrile than to acetonitrile by 3 kcal mol⁻¹, and the proton affinity of the former is higher by 0.8 kcal mol⁻¹. G4 enthalpies of reductions support prior experimental observation that metalated conjugated nitriles show enhanced reactivity toward weak nucleophiles to afford Michael addition products.
OBJECTIVE: Asians are known to have different tear characteristics compared to Caucasians that may affect contact lens wear. There are scanty research studies that have evaluated tears during continuous wear contact lens in Asia. The present study aims to evaluate changes in tears in subjects wearing continuous wear rigid gas permeable contact lens (CWRGP) for 6 months.
MATERIALS AND METHODS: Thirty five neophyte subjects (21 females, 14 females) were recruited for this study. Subjects were fitted with CWRGP lenses with Dk of 163 on both eyes. Tear was evaluated using Phenol red thread test (PRT), tear break up time (TBUT) test and tear meniscus height (TMH) measurement. Non parametric and parametric analyses were used to compare the parameters.
RESULTS: Values at baseline (BL) and six months (6M) were as follow: PRT, BL=19.10 ± 3.86 mm, 6M= 21.02 ± 4.27 mm, TBUT, BL= 8.58 ± 4.90 sec, 6M=8.08 ± 5.32 sec, TMH, BL= 0.38 ± 0.12 mm, 6M= 0.34 ± 0.07 mm. Statistical analysis showed significant difference in tear volume for PRT only at 6 months (p=0.007).
CONCLUSION: Our analysis showed minimal change in the tear characteristics after six months of CWRGP lens wear, which indicated low impact of CWRGP contact lens on tears characteristics of Asian eyes. However, careful monitoring is required to prevent development of adverse events during contact lens wear.
A gas sensor array was developed in a 10 × 10 mm(2) space using Screen Printing and Pulse Laser Ablation Deposition (PLAD) techniques. Heater, electrode, and an insulator interlayer were printed using the screen printing method on an alumina substrate, while tin oxide and platinum films, as sensing and catalyst layers, were deposited on the electrode at room temperature using the PLAD method, respectively. To ablate SnO(2) and Pt targets, depositions were achieved by using a 1,064 nm Nd-YAG laser, with a power of 0.7 J/s, at different deposition times of 2, 5 and 10 min, in an atmosphere containing 0.04 mbar (4 kPa) of O(2). A range of spectroscopic diffraction and real space imaging techniques, SEM, EDX, XRD, and AFM were used in order to characterize the surface morphology, structure, and composition of the films. Measurement on the array shows sensitivity to some solvent and wood smoke can be achieved with short response and recovery times.
In order to reduce the negative impact of coal utilization for energy generation, the pollutants present in the flue gas of coal combustion such as sulfur dioxide (SO(2)) and nitrogen oxide (NO) must be effectively removed before releasing to the atmosphere. Thus in this study, sorbent prepared from rice husk ash that is impregnated with copper is tested for simultaneous removal of SO(2) and NO from simulated flue gas. The effect of various sorbent preparation parameters; copper loading, RHA/CaO ratio, hydration period and NaOH concentration on the sorbent desulfurization/denitrification capacity was studied using Design-Expert Version 6.0.6 software. Specifically, Central Composite Design (CCD) coupled with Response Surface Method (RSM) was used. Significant individual parameters that affect the sorbent capacity are copper loading and NaOH concentration. Apart from that, interaction between the following parameters was also found to have significant effect; copper loading, RHA/CaO ratio and NaOH concentration. The optimum sorbent preparation condition for this study was found to be 3.06% CuO loading, RHA/CaO ratio of 1.41, 8.05 h of hydration period and NaOH concentration of 0.80 M. Sorbent characterization using SEM, XRD and surface area analysis were used to describe the effect of sorbent preparation parameters on the desulfurization/denitrification activity.
Produced water is the largest waste stream generated in oil and gas industries. It is a mixture of different organic and inorganic compounds. Due to the increasing volume of waste all over the world in the current decade, the outcome and effect of discharging produced water on the environment has lately become a significant issue of environmental concern. Produced water is conventionally treated through different physical, chemical, and biological methods. In offshore platforms because of space constraints, compact physical and chemical systems are used. However, current technologies cannot remove small-suspended oil particles and dissolved elements. Besides, many chemical treatments, whose initial and/or running cost are high and produce hazardous sludge. In onshore facilities, biological pretreatment of oily wastewater can be a cost-effective and environmental friendly method. As high salt concentration and variations of influent characteristics have direct influence on the turbidity of the effluent, it is appropriate to incorporate a physical treatment, e.g., membrane to refine the final effluent. For these reasons, major research efforts in the future could focus on the optimization of current technologies and use of combined physico-chemical and/or biological treatment of produced water in order to comply with reuse and discharge limits.
A series of polyetherimide (PEI) hollow fiber membranes with various polymer concentrations (13-16 wt.%) for CO2 stripping process in membrane contactor application was fabricated via wet phase inversion method. The PEI membranes were characterized in terms of liquid entry pressure, contact angle, gas permeation and morphology analysis. CO2 stripping performance was investigated via membrane contactor system in a stainless steel module with aqueous diethanolamine as liquid absorbent. The hollow fiber membranes showed decreasing patterns in gas permeation, contact angle, mean pore size and effective surface porosity with increasing polymer concentration. On the contrary, wetting pressure of PEI membranes has enhanced significantly with polymer concentration. Various polymer concentrations have different effects on the CO2 stripping flux in which membrane with 14 wt.% polymer concentration showed the highest stripping flux of 2.7 × 10(-2)mol/m(2)s. From the performance comparison with other commercial membrane, it is anticipated that the PEI membrane has a good prospect in CO2 stripping via membrane contactor.
High performance sorbents for flue gas desulfurization can be synthesized by hydration of coal fly ash, calcium sulfate, and calcium oxide. In general, higher desulfurization activity correlates with higher sorbent surface area. Consequently, a major aim in sorbent synthesis is to maximize the sorbent surface area by optimizing the hydration conditions. This work presents an integrated modeling and optimization approach to sorbent synthesis based on statistical experimental design and two artificial intelligence techniques: neural network and genetic algorithm. In the first step of the approach, the main and interactive effects of three hydration variables on sorbent surface area were evaluated using a full factorial design. The hydration variables of interest to this study were hydration time, amount of coal fly ash, and amount of calcium sulfate and the levels investigated were 4-32 h, 5-15 g, and 0-12 g, respectively. In the second step, a neural network was used to model the relationship between the three hydration variables and the sorbent surface area. A genetic algorithm was used in the last step to optimize the input space of the resulting neural network model. According to this integrated modeling and optimization approach, an optimum sorbent surface area of 62.2m(2)g(-1) could be obtained by mixing 13.1g of coal fly ash and 5.5 g of calcium sulfate in a hydration process containing 100ml of water and 5 g of calcium oxide for a fixed hydration time of 10 h.
Carbon monoxide (CO) is a ubiquitous, an indoor and outdoor air pollutant. It is not a significant greenhouse gas as it absorbs little infrared radiation from the Earth. It is produced by the incomplete combustion of fossil fuels, and biomass burning. The CO data are obtained from Atmospheric Infrared Sounder (AIRS) onboard NASA’s Aqua satellite. The AIRS provides information for several greenhouse gases, CO2, CH4, CO, and O3 as a one goal of the AIRS instrument (included on the EOS Aqua satellite launched, May 4, 2002) as well as to improve weather prediction of the water and energy cycle. The results of the analysis of the retrieved CO total column amount (CO_total_column_A) as well as effective of the CO volume mixing ratio (CO_VMR_eff_A), Level-3 monthly (AIR*3STM) 1º*1º spatial resolution, ascending are used to study the CO distribution over the East and West Malaysia for the year 2003. The CO maps over the study area were generated by using Kriging Interpolation technique and analyzed by using Photoshop CS. Variations in the biomass burning and the CO emissions where noted, while the highest CO occurred at late dry season in the region which has experienced extensive biomass burning and greater draw down of CO occurred in the pristine continental environment (East Malaysia). In all cases, the CO concentration at West Malaysia is higher than East Malaysia. The southeastern Sarawak (lat. 3.5˚ - long. 115.5˚) is less polluted regions and less the CO in most of times in the year. Examining satellite measurements revealed that the enhanced CO emission correlates with occasions of less rainfall during the dry season.
Employment of edible oils as alternative green fuel for vehicles had raised debates on the sustainability of food supply especially in the third-world countries. The non-edible oil obtained from the abundantly available rubber seeds could mitigate this issue and at the same time reduce the environmental impact. Therefore, this paper investigates the catalytic cracking reaction of a model compound named linoleic acid that is enormously present in the rubber seed oil. Batch-scale experiments were conducted using 8.8 mL Inconel batch reactor having a cyclic horizontal swing span of 2 cm with a frequency of 60 cycles per minute at 450 °C under atmospheric condition for 90 min. The performance of HZSM-5, HBeta, HFerrierite, HMordenite and HY catalysts was tested for their efficiency in favouring gasoline range hydrocarbons. The compounds present in the organic liquid product were then analysed using GC-MS and classified based on PIONA which stands for paraffin, isoparaffin, olefin, naphthenes and aromatics respectively. The results obtained show that HZSM-5 catalyst favoured gasoline range hydrocarbons that were rich in aromatics compounds and promoted the production of desired isoparaffin. It also gave a higher cracking activity; however, large gaseous as by-products were produced at the same time.
In this work, the removal of SO(2) and NO from simulated flue gas from combustion process was investigated in a fixed-bed reactor using rice husk ash (RHA)/CaO-based sorbent. Various metal precursors were used in order to select the best metal impregnated over RHA/CaO sorbents. The results showed that RHA/CaO sorbents impregnated with CeO(2) had the highest sorption capacity among other impregnated metal oxides for the simultaneous removal of SO(2) and NO. Infrared spectroscopic results indicated the formation of both sulfate (SO(4)(2-)) and nitrate (NO(3)(-)) species due to the catalytic role played by CeO(2). Apart from that, the catalytic activity of the RHA/CaO/CeO(2) sorbent was found to be closely related to its physical properties (specific surface area, total pore volume and average pore diameter).
The clastogenic and mutagenic effects of the insecticide Dimethoate (Cygon-2E), herbicides Atrazine, Simazine (Princep), Dicamba (Banvel D) and Picloram (Tordon) were studied using the Tradescantia-micronucleus (Trad-MCN) and Tradescantia-stamen hair mutation (Trad-SHM) assays. In clone 4430, dimethoate fumes both significantly increased the pink mutation events and reduced the number of stamen hairs per filament with increasing dosages. The pink mutation events were elevated by the liquid treatment with Picloram at 100 ppm concentration. The result of Trad-MCN test on Dimethoate fumes was not significantly different between the control and treated groups. The herbicide Atrazine showed positive effects at 10-50 ppm dose (liquid) and signs of overdose at 100 and 500 ppm concentrations. Simazine was mildly positive in elevating the MCN frequencies in the dose range of 5 to 200 ppm (liquid doses). Both Dicamba and Picloram induced a dosage-related increase in MCN frequencies in the Trad-MCN tests using Tradescantia clone 03. However, in higher dosages (200 ppm or higher), there were signs of overdose, reduction of MCN frequencies and physical damage of the leaves and buds of plant cuttings.
Native Lantang and commercial Duroc pigs were used as animal models to evaluate the differences existing in dietary fiber utilization ability between breeds. Animals were fed the same diet from weaning (4 weeks) to 4 months of age. Neutral detergent fiber (NDF) from wheat bran (as substrate) and fecal samples from the two breeds (as inoculum) were used in an in vitro gas production trial. Results showed that cumulative and maximum gas productions were higher in inocula from Lantang than those from the Duroc breed (P
Papaya leaf methanolic extract (PLE) at concentrations of 0 (CON), 5 (LLE), 10 (MLE) and 15 (HLE) mg/250 mg dry matter (DM) with 30 mL buffered rumen fluid were incubated for 24 h to identify its effect on in vitro ruminal methanogenesis and ruminal biohydrogenation (BH). Total gas production was not affected (P > 0.05) by addition of PLE compared to the CON at 24 h of incubation. Methane (CH4 ) production (mL/250 mg DM) decreased (P
Leachate is one of the main surface water pollution sources in Selangor State (SS), Malaysia. The prediction of leachate amounts is elementary in sustainable waste management and leachate treatment processes, before discharging to surrounding environment. In developing countries, the accurate evaluation of leachate generation rates has often considered a challenge due to the lack of reliable data and high measurement costs. Leachate generation is related to several factors, including meteorological data, waste generation rates, and landfill design conditions. The high variations in these factors lead to complicating leachate modeling processes. This study aims at identifying the key elements contributing to leachate production and developing various AI-based models to predict leachate generation rates. These models included Artificial Neural Network (ANN)-Multi-linear perceptron (MLP) with single and double hidden layers, and support vector machine (SVM) regression time series algorithms. Various performance measures were applied to evaluate the developed model's accuracy. In this study, input optimization process showed that three inputs were acceptable for modeling the leachate generation rates, namely dumped waste quantity, rainfall level, and emanated gases. The initial performance analysis showed that ANN-MLP2 model-which applies two hidden layers-achieved the best performance, then followed by ANN-MLP1 model-which applies one hidden layer and three inputs-while SVM model gave the lowest performance. Ranges and frequency of relative error (RE%) also demonstrate that ANN-MLP models outperformed SVM models. Furthermore, low and peak flow criterion (LFC and PFC) assessment of leachate inflow values in ANN-MLP model with two hidden layers made more accurate values than other models. Since minimizing data collection and processing efforts as well as minimizing modeling complexity are critical in the hydrological modeling process, the applied input optimization process and the developed models in this study were able to provide a good performance in the modeling of leachate generation efficiently.
BACKGROUND AND OBJECTIVE: Welding fume exposure has led to the respiratory problems among welders including cough, phlegm, chest illnesses, nausea and fatigue. Inadequate ventilation during welding works causes the situation to worsen. Welding fumes can cause a decrease in lung function among welders. Chronic exposure will lead to other health effects especially COPD (Chronic Obstructive Pulmonary Disease). The objective of this study is to determine the exposure of welding fumes (Cd, Fe, Pb and Zn) towards respiratory health including lung function test (FEV1, FVC, FEV1/FVC, PEFR) of workers in Lumut shipyard, Perak.
MATERIAL AND METHODS: This research study the relationship between exposures of welding fumes towards lung function test among workers in Lumut shipyard, Perak. Lung function test was measured by spirometry among 30 welders and 31 non-welders. The concentration welding fume exposure was measured using OSHA ID-121 method. Sociodemographic data, respiratory symptoms and smoking habit data was analyzed based on the ATS 1987 questionnaire.
RESULTS: The mean concentration for Pb in welding fumes was 2.752 mg m-3 which is above 0.5 mg m-3 PEL-TWA. The FEV1 and FVC readings showed significant different between welders and non-welders (p = 0.001). Cough and phlegm symptoms showed significant different between welders and non-welders (p = 0.001). Welders had higher prevalence in smoking habit than the non-welders. Chest illnesses symptom showed an association with the smoking habit (p = 0.01).
CONCLUSION: There is relationship between welding fumes exposure on lung function test of workers in Lumut shipyard. Pb in welding fumes has high concentration and exceeded PEL-TWA level. The FEV1 and FVC in welders are lower than non-welder due to the fumes exposure. Welders showed higher respiratory symptoms than non-welders. Smoking habit is a contributing factor towards respiratory problem.
Dehydration-responsive element binding (DREB) transcription factor plays an important role in controlling the expression of abiotic stress responsive genes. An intronless oil palm EgDREB1 was isolated and confirmed to be a nuclear localized protein. Electrophoretic mobility shift and yeast one-hybrid assays validated its ability to interact with DRE/CRT motif. Its close evolutionary relation to the dicot NtDREB2 suggests a universal regulatory role. In order to determine its involvement in abiotic stress response, functional characterization was performed in oil palm seedlings subjected to different levels of drought severity and in EgDREB1 transgenic tomato seedlings treated by abiotic stresses. Its expression in roots and leaves was compared with several antioxidant genes using quantitative real-time PCR. Early accumulation of EgDREB1 in oil palm roots under mild drought suggests possible involvement in the initiation of signaling communication from root to shoot. Ectopic expression of EgDREB1 in T1 transgenic tomato seedlings enhanced expression of DRE/CRT and non-DRE/CRT containing genes, including tomato peroxidase (LePOD), ascorbate peroxidase (LeAPX), catalase (LeCAT), superoxide dismutase (LeSOD), glutathione reductase (LeGR), glutathione peroxidase (LeGP), heat shock protein 70 (LeHSP70), late embryogenesis abundant (LeLEA), metallothionine type 2 (LeMET2), delta 1-pyrroline-5- carboxylate synthetase (LePCS), ABA-aldehyde oxidase (LeAAO) and 9-cis- Epoxycarotenoid dioxygenase (LeECD) under PEG treatment and cold stress (4 °C). Altogether, these findings suggest that EgDREB1 is a functional regulator in enhancing tolerance to drought and cold stress.