Evaluation on some finishing properties of oil palm plywood

Oil palm is the largest and most important plantation crop in Malaysia. The oil palm generally lasts for 25–30 years before the next replantation is done. Substantial amount of biomass in the form of palm trunk results from plantation cycle. This resource is simply left on the ground to decay and is not used as raw material to manufacture any kind of value-added products. The objective of this study was to investigate the possibility of manufacturing plywood from oil palm trunks and to evaluate some of the finishing properties of such experimental panels in comparison to those from Shorea sp as control samples. Three-ply plywood samples were produced from 5 mm thick veneers of oil palm using urea formaldehyde adhesive. Three types of chemicals, namely nitrocellulose, pre-catalyzed lacquer and polyurethane were used to finish experimental panels. The surface finished with nitrocellulose had the lowest contact angle on raw surface of oil palm plywood and wood. The average cross cut tape index of oil palm plywood was comparable to Shorea sp. All finishing materials of oil palm plywood produced impact rating of 4 except for surface finished with nitrocellulose while finishing on wood indicated an impact rating of 3. Oil palm plywood had higher weight loss compared to Shorea sp. Based on results from contact angle, cross cut tape index, impact rate test, weathering, and soil burial test methods it appears that the samples showed acceptable finishing properties comparable to those of solid wood.     

Antioxidant constituents from Lawsonia inermis leaves: Isolation,structure elucidation and antioxidative capacity

The antioxidant potential of different fractions of Lawsonia inermis (Lythraceae) was investigated. The n-butanolic fraction showed the highest yield of extraction; it also exhibited a strong antioxidant activity in the DPPH assay and a potent capacity in preventing linoleic acid oxidation. Five phenolic glycosides were identified in this fraction. The structure of a new compound was established as 1,2,4-trihydroxynaphthalene-1-Ο-β-d-glucopyranoside. In addition, the known 2,4,6-trihydroxyacetophenone-2-Ο-β-d-glucopyranoside was described for the first time in this species. The three other compounds, lalioside (2,3,4,6-tetrahydroxyacetophenone-2-Ο-β-d-glucopyranoside), lawsoniaside (1,2,4-trihydroxynaphthalene-1,4-di-Ο-β-d-glucopyranoside) and luteolin-7-Ο-β-d-glucopyranoside, have been previously reported in L. inermis. The antioxidant activity of these glycosides was evaluated by DPPH and β-carotene assays, and compared to those of commercial standards. 1,2,4-Trihydroxynaphthalene-1-Ο-β-d-glucopyranoside was the most active in the DPPH free-radical scavenging test (EC₅₀ = 6.5 μg/ml) and showed a moderate inhibition in the β-carotene bleaching assay. Chemical components of L. inermis have good antioxidant capacities and this species could be used as a potential source of new natural antioxidants.     

Aerobic and Anaerobic Bacterial and Fungal Degradation of Pyrene: Mechanism Pathway Including Biochemical Reaction and Catabolic Genes

Microbial biodegradation is one of the acceptable technologies to remediate and control the pollution by polycyclic aromatic hydrocarbon (PAH). Several bacteria, fungi, and cyanobacteria strains have been isolated and used for bioremediation purpose. This review paper is intended to provide key information on the various steps and actors involved in the bacterial and fungal aerobic and anaerobic degradation of pyrene, a high molecular weight PAH, including catabolic genes and enzymes, in order to expand our understanding on pyrene degradation. The aerobic degradation pathway by Mycobacterium vanbaalenii PRY-1 and Mycobactetrium sp. KMS and the anaerobic one, by the facultative bacteria anaerobe Pseudomonas sp. JP1 and Klebsiella sp. LZ6 are reviewed and presented, to describe the complete and integrated degradation mechanism pathway of pyrene. The different microbial strains with the ability to degrade pyrene are listed, and the degradation of pyrene by consortium is also discussed. The future studies on the anaerobic degradation of pyrene would be a great initiative to understand and address the degradation mechanism pathway, since, although some strains are identified to degrade pyrene in reduced or total absence of oxygen, the degradation pathway of more than 90% remains unclear and incomplete. Additionally, the present review recommends the use of the combination of various strains of anaerobic fungi and a fungi consortium and anaerobic bacteria to achieve maximum efficiency of the pyrene biodegradation mechanism.     

Artificial neural networks: a novel tool for detecting GMO

Introduction of artificial neural network (ANN) into the field of GMO detection is the aim of this investigation. The usefulness of ANN to predict transgenic maize (Bt-176) based on chemical composition of the extracted crude oil was evaluated. The training set, comprised of a composition of major and minor lipid components as inputs and outputs. Crude oil extracted from the genetically modified maize (Bt-176) and non-transgenic maize was characterized in terms of its fatty acids, phytosterols and tocopherols distribution as well as of its lipid classes and unsaponifiables amounts. The results obtained from lipid distribution analysis showed that the grains of Bt-176 maize were comparable in their composition to that of the control maize. The analytical data have been elaborated by supervised pattern recognition technique ANN in order to classify genetically modified maize (Bt-176) and conventional maize as well as to authenticate the origin of the samples.     

Meaningful Learning for Deep Facial Emotional Features

Neural Processing Letters - Facial expression is an important aspect to recognize emotions between humans. However, this task remains difficult for machines. Several approaches have been developed...     

Synthesis and Characterization of Hetero-metallic Oxides-Reduced Graphene Oxide Nanocomposites for Photocatalytic Applications

A new AgO.CuO.WO₃/rGO nanocomposite was designed for the investigation of the degradation ability of the hybrid material under visible light irradiation. The AgO, CuO, WO₃ NPs, and AgO.CuO.WO₃ hetero-metallic oxides were fabricated via the chemical co-precipitation method. The crystallite sizes and phase analyses were investigated by recording X-ray diffraction patterns. The crystallite sizes of three metal oxides in the AgO.CuO.WO₃ hetero metal oxide were 16.7, 15.9, and 16.9 nm, respectively. The FESEM images at various magnifications were probed to study the morphology of synthesized materials. The micrographs of hetero-metallic oxides AgO.CuO.WO₃ exposed that three metal oxides merged like small particles and gives a large bulbous appearance. EDX analyses confirmed the formation of required materials with high purity. FTIR data was in agreement with the literature which facilitated to ensure the purity of synthesized samples. The optical bandgap energy was calculated via the Tauc plot indicating that the blend of three metal oxides generated a new energy level in the electronic structure is suitable for photocatalysis in the presence of visible light. The bandgap energy of hetero metallic oxides was 1.25 eV which is less than individual metal oxides signifying the tuning of the bandgap. The incorporation of rGO in AgO.CuO.WO₃ hetero-metallic oxides gives a new photocatalyst for optimum photodegradation of methylene blue in minimum time. The percentage degradation via AgO.CuO.WO₃ was 87.20% in 70 min while the percentage degradation via AgO.CuO.WO₃/rGO recorded by photocatalytic experiment was 95% in 40 min. The photocatalysis data revealed that AgO.CuO.WO₃ hetero-metallic oxides-rGO nanocomposite ensured a strong potential to uptake organic dyes from water by promoting redox reactions during photocatalysis in the minimum time limit.     

Hybrid marine predators algorithm for image segmentation: analysis and validations

Naturally, to analyze an image accurately, all the similar objects within it should be separated to pay attention to the most important object for reaching more details and hence achieving better accuracy. Therefore, multilevel thresholding is an indispensable image processing technique in the field of image segmentation and is employed widely to separate those similar objects. However, with increasing thresholds, the existing image segmentation techniques might suffer from exponentially-grown computational cost and low accuracy due to local optima shortage. Therefore, in this paper, a new image segmentation algorithm based on the improved marine predators algorithm (MPA) is proposed. MPA is improved using a strategy to find a number of the worst solutions within the population then tries to search for other better ones for those solutions by moving them gradually towards the best solutions to avoid accelerating to local optima and randomly within the search space based on a certain probability. In addition, this number of the worst solutions is increased with the iteration. This strategy is known as the linearly increased worst solutions improvement strategy (LIS). Also, we suggested that apply the ranking strategy based on a novel updating scheme, namely ranking-based updating strategy (RUS), on the solutions that could find better solutions in the last number iterations, perIter, in the hope of finding better solutions near it. RUS updates the particles/solutions which could not find better solutions than the best-local one in a number of consecutive iterations, with those that are generated based on a novel updating strategy. LIS is integrated with MPA to produce a new segmentation meta-heuristic algorithm abbreviated as MPALS. Also, MPALS and RUS are combined to tackle ISP in a strong variant abbreviated as HMPA for overcoming the image segmentation problem. The two proposed algorithms are validated on 14 test images and compared with seven state-of-the-arts meta-heuristic algorithms. The experimental results show the effectiveness of HMPA with increasing the threshold levels compared to the seven state-of-the-arts algorithms when segmenting an image, while their performance is roughly the same for the image with a small threshold level.

     

Production of a halotolerant lipase from Halomonas sp. strain C2SS100: Optimization by response-surface methodology and application in detergent formulations

The aim of this work was to optimize the production of a new lipase by a halotolerant bacterial strain Halomonas sp. C2SS100, by means of the response-surface methodology (RSM). The process parameters having the most significant effect on lipase production were identified using the Plackett–Burman screening design-of-experiments. Then, Box–Behnken design was applied to optimize lipase activity and the quadratic regression model of the lipase production was built. Indeed, the lipase yield was increased, and the value obtained experimentally (39 ± 2 U/ml) was very close to the rate predicted by the model (40.3 U/ml). Likewise, optimization of parameters by RSM resulted in 2.78-fold increase in lipase activity. These findings provide the first report on lipase production and optimization by a halotolerant bacterial strain belonging to Halomonas genus. Afterward, the biochemical properties of the produced lipase were studied for apply in oil stains removal. The crude lipase showed a maximum activity at 60°C and at pH ranging from 7 to 10. It displayed an important stability at high temperature, pH, and NaCl. Interestingly, this bacterial lipase exhibited a prominent stability toward some commercial solid and liquid detergents after 30 min of incubation at 50°C. The capability of the crude lipase to eliminate stain was ascertained on polycotton fabric pieces stained with lubricating oil. Whether with the addition of hot water alone or of a commercially available detergent, lipase is able to considerably boost the elimination of oil stains. The actual findings highlight the capacity of Halomonas sp. lipase for energy-efficient biocatalytic application.