Study Of The Carbon Dioxide (Co2) Laser Inert Gas Cutting On Inconel 718 Using Empirical Approach And Finite Element Analysis

Laser cutting is a thermal cutting process in which a highly intense laser beam melts the material throughout the material thickness and form a cut kerf width. In Malaysia, laser cutting become one of the most common industrial application of laser especially in sheet metal processing industries. Inconel 718 is a type of high strength nickel-based alloy, thus makes it difficult to cut using conventional cutting methods. In this research, laser inert gas cutting was identified as the best method to cut the material and nitrogen gas is chosen as the inert gas. Laser cutting of Inconel 718 for 1 mm and 2 mm thicknesses were simulated by using commercial finite element analysis (FEA) code

A Study of Weld Seams on Low Carbon Steel ABS Grade a Marine Plates Using SMAW Process

The research aims to study and assess the impact of weld seams of low carbon steel ABS Grade A marine plates of 12.7mm thick using manual SMAW process as per AWS D1.1 structural welding code requirements and fulfilments of ASME Section IX pressurized equipment welding code requirements too. Different voltages, currents, and travel speeds were used to weld the test specimen plates. After the manual SMAW process, a series of testing techniques, including non-destructive tests, such as VT and RT, and destructive tests, such as tensile tests, bend tests, impact tests, microhardness tests, and metallographic examination has been conducted to assess/evaluate on the welded seam profiles and analyses/determines whether the accepted welded seam profiles have fulfilled the relevant welding code requirements. From the series of assessments and analyses, it is confirmed that the welded test specimen 1 having the welding parameters (i.e., voltage 23 V, current 70 A, and travel speeds 56.52 – 312.50 mm/min, having a range of heat inputs from 0.31kJ/mm to 1.71kJ/mm) is accepted as the quality good weld seam

Durian recognition based on multiple features and linear discriminant analysis

Many fruit recognition approaches today are designed to classify different type of fruits but there is little effort being done for content-based fruit recognition specifically focuses on durian species. Durian, known as the king of tropical fruits, have few similar characteristics between different species where the skin have almost the same colour from green to yellowish brown with just slightly different shape and pattern of thorns. Therefore, it is hard to differentiate them with the current methods. It would be valuable to have an automated content-based recognition framework that can automatically represent and recognise a durian species given a durian image as the input. Therefore, this work aims to contribute to a new representation method based on multiple features for effective durian recognition. Two features based on shape and texture is considered in this work. Simple shape signatures which include area, perimeter, and circularity are used to determine the shape of the fruit durian and its base while the texture of the fruit is constructed based on Local Binary Pattern. We extracted these features from 240 durian images and trained this proposed method using few classifiers. Based on 10-fold cross validation, it is found that Logistic Regression, Gaussian Naïve Bayesian, and Linear Discriminant Analysis classifiers performed equally well with 100% achievement of accuracy, precision, recall, and F1-score. We further tested the proposed algorithm on larger dataset which consisted of 42337 fruit images (64 various categories). Experimental results based on larger and more general dataset have shown that the proposed multiple features trained on Linear Discriminant Analysis classifier able to achieve 72.38% accuracy, 73% precision, 72% recall, and 72% F1-score

Mediated amperometric immunosensing using single walled carbon nanotube forests

A prototype amperometric immunosensor was evaluated based on the adsorption of antibodies onto perpendicularly oriented assemblies of single wall carbon nanotubes called SWNT forests. The forests were self-assembled from oxidatively shortened SWNTs onto Nafion/iron oxide coated pyrolytic graphite electrodes. The nanotube forests were characterized using atomic force microscopy and resonance Raman spectroscopy. Anti-biotin antibody strongly adsorbed to the SWNT forests. In the presence of a soluble mediator, the detection limit for horseradish peroxidase (HRP) labeled biotin was 2.5 pmol ml[-1] (2.5 nM). Unlabelled biotin was detected in a competitive approach with a detection limit of 16 nmol ml[-1] (16 μM) and a relative standard deviation of 12%. The immunosensor showed low non-specific adsorption of biotin-HRP (approx. 0.1%) when blocked with bovine serum albumin. This immunosensing approach using high surface area, patternable, conductive SWNT assemblies may eventually prove useful for nano-biosensing arrays

Therapeutic target-site variability in α1-antitrypsin characterized at high resolution

The intrinsic propensity of [alpha]1-antitrypsin to undergo conformational transitions from its metastable native state to hyperstable forms provides a motive force for its antiprotease function. However, aberrant conformational change can also occur via an intermolecular linkage that results in polymerization. This has both loss-of-function and gain-of-function effects that lead to deficiency of the protein in human circulation, emphysema and hepatic cirrhosis. One of the most promising therapeutic strategies being developed to treat this disease targets small molecules to an allosteric site in the [alpha]1-antitrypsin molecule. Partial filling of this site impedes polymerization without abolishing function. Drug development can be improved by optimizing data on the structure and dynamics of this site. A new 1.8 Å resolution structure of [alpha]1-antitrypsin demonstrates structural variability within this site, with associated fluctuations in its upper and lower entrance grooves and ligand-binding characteristics around the innermost stable enclosed hydrophobic recess. These data will allow a broader selection of chemotypes and derivatives to be tested in silico and in vitro when screening and developing compounds to modulate conformational change to block the pathological mechanism while preserving function

Durian species recognition system based on global shape representations and k-nearest neighbors

Many fruit recognition systems today are designed to classify different type of fruits but there is no content-based fruit recognition system focuses on durian species. Durian, known as the king of tropical fruits, have few similar characteristics between different species where the skin have almost the same color from green to yellowish brown with slightly different shape of thorns and it is hard to differentiate them with the current methods. Sometimes it is even hard for general consumers to differentiate durian species by themselves. This work aims to contribute to an automatic content-based durian species recognition that will be able to assist users in differentiating various species of durian. Few global contour-based and region-based shape descriptors such as area, perimeter, and circularity are computed as feature vectors and K-Nearest Neighbors algorithm is used to classify the durian based on the extracted features. 10-fold cross-validation is used to evaluate the proposed system. Experimental results have shown that the proposed feature extraction method for the durian species recognition system has successfully obtained a positive recognition rate of 100%

Site-specific Forest-assembly of Single-Wall Carbon Nanotubes on Electron-beam Patterned SiOx/Si Substrates

Based on electron-beam direct writing on the SiOx/Si substrates, favorable absorption sites for ferric cations (Fe3+ ions) were created on the surface oxide layer. This allowed Fe3+-assisted self-assembled arrays of single-wall carbon nanotube (SWNT) probes to be produced. Auger investigation indicated that the incident energetic electrons depleted oxygen, creating more dangling bonds around Si atoms at the surface of the SiOx layer. This resulted in a distinct difference in the friction forces from unexposed regions as measured by lateral force microscopy (LFM). Atomic force microscopy (AFM) affirmed that the irradiated domains absorbed considerably more Fe3+ ions upon immersion into pH 2.2 aqueous FeCl3 solution. This rendered a greater yield of FeO(OH)/FeOCl precipitates, primarily FeO(OH), upon subsequent washing with lightly basic dimethylformamide (DMF) solution. Such selective metalfunctionalization established the basis for the subsequent patterned forest-assembly of SWNTs as demonstrated by resonance Raman spectroscopy

An integrative approach combining ion mobility mass spectrometry, X-ray crystallography and NMR spectroscopy to study the conformational dynamics of α1-antitrypsin upon ligand binding

Native mass spectrometry (MS) methods permit the study of multiple protein species within solution equilibria, whilst ion mobility (IM)-MS can report on conformational behaviour of specific states. We used IM-MS to study a conformationally labile protein (α1-antitrypsin) that undergoes pathological polymerisation in the context of point mutations. The folded, native state of the Z variant remains highly polymerogenic in physiological conditions, despite only minor thermodynamic destabilisation relative to the wild-type variant. Various data implicate kinetic instability (conformational lability within a native state ensemble) as the basis of Z α1-antitrypsin polymerogenicity. We show the ability of IM-MS to track such disease-relevant conformational behaviour in detail by studying the effects of peptide binding on α1-antitrypsin conformation and dynamics. IM-MS is therefore an ideal platform for the screening of compounds that result in therapeutically-beneficial kinetic stabilisation of native α1-antitrypsin. Our findings are confirmed with high resolution X-ray crystallographic and NMR spectroscopic studies of the same event, which together dissect structural changes from dynamic effects caused by peptide binding at a residue specific level. IM-MS methods therefore have great potential for further study of biologically-relevant thermodynamic and kinetic instability of proteins and provide rapid and multidimensional characterisation of ligand interactions of therapeutic interest. This article is protected by copyright. All rights reserved

Reactive centre loop mutants of α-1-antitrypsin reveal position-specific effects on intermediate formation along the polymerization pathway

The common severe Z mutation (E342K) of α1-antitrypsin forms intracellular polymers that are associated with liver cirrhosis. The native fold of this protein is well-established and models have been proposed from crystallographic and biophysical data for the stable inter-molecular configuration that terminates the polymerization pathway. Despite these molecular 'snapshots', the details of the transition between monomer and polymer remain only partially understood. We surveyed the RCL (reactive centre loop) of α1-antitrypsin to identify sites important for progression, through intermediate states, to polymer. Mutations at P14P12 and P4, but not P10P8 or P2P1', resulted in a decrease in detectable polymer in a cell model that recapitulates the intracellular polymerization of the Z variant, consistent with polymerization from a near-native conformation. We have developed a FRET (Förster resonance energy transfer)-based assay to monitor polymerization in small sample volumes. An in vitro assessment revealed the position-specific effects on the unimolecular and multimolecular phases of polymerization: the P14P12 region self-inserts early during activation, while the interaction between P6P4 and β-sheet A presents a kinetic barrier late in the polymerization pathway. Correspondingly, mutations at P6P4, but not P14P12, yield an increase in the overall apparent activation energy of association from ~360 to 550 kJ mol-1