An intelligent system based on concurrent engineering for innovative product design at the conceptual design stage

This paper describes the development of an intelligent system based on concurrent engineering for generating design alternatives at the conceptual design stage. The proposed system encompasses a design analysis module, a design evaluation module, a knowledge acquisition and storing module, a user interface and databases. It is also integrated with a spreadsheet application for storing data and numerical analysis and works in combination with a material selection software Cambridge engineering selector (CES) to facilitate the material selection process. The tangible advantage of implementing this system is that it enables the designer to explore and experiment with alternative ideas in the early design stage, and it results in design solutions that are functionally sound- and cost-effective. It also has the capability for design alternatives evaluation, material selection and modelling the product detailed design on the computer-aided design system. Therefore, an efficient product development process is generated. Three case studies are demonstrated and discussed to validate the proposed system.     

Minocycline incorporated cobalt oxide nanoparticles in dental sealants: An in vitro study

The purpose of this study was to introduce antibacterial property to pits and fissure sealant (PFS) in order to mitigate the major clinical problems associated with PFS, such as microleakage and secondary caries. We prepared a pH reliant cobalt oxide nanoparticle incorporated with minocycline (MNC@CO) and characterized to investigate its antibacterial potential against Streptococcus sobrinus. The physiochemical, morphological, and drug release kinetics at different pH (7.4, 5.0, and 3.5) from nanoparticles were investigated. The MNC@CO were added at 2.5% and 5.0% into experimental PFS and characterized for their antibiofilm capacity, biocompatibility, and mechanical properties including compressive and flexural strength. The groups 2.5% and 5.0% has shown statistically significant antimicrobial capacity against S. sobrinus compared to control (p < .05). The highest percentage of MNC release at different pH (especially at pH 5.0 and 3.5) was observed from 5.0% MNC@CO doped PFS. The PFS doped with 2.5% MNC@CO showed a highest compressive strength (110 MPa) over a period of 70 days as compared to 5.0% MNC@CO (75 MPa) and control (80 MPa). The flexural strength of both experimental groups was lower for both time points (24 h and 30 days) than control. In conclusion, the present study found that 2.5% MNC@CO doped PFS showed considerable anti-biofilm potential without compromising mechanical properties.     

Analysis of effect of nanoporous alumina substrate coated with polypyrrole nanowire on cell morphology based on AFM topography

In this study, in situ electrochemical synthesis of polypyrrole nanowires with nanoporous alumina template was described. The formation of highly ordered porous alumina substrate was demonstrated with Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). In addition, Fourier transform infrared analysis confirmed that polypyrrole (PP) nanowires were synthesized by direct electrochemical oxidation of pyrrole. HeLa cancer cells and HMCF normal cells were immobilized on the polypyrrole nanowires/nanoporous alumina substrates to determine the effects of the substrate on the cell morphology, adhesion and proliferation as well as the biocompatibility of the substrate. Cell adhesion and proliferation were characterized using a standard MTT assay. The effects of the polypyrrole nanowires/nanoporous alumina substrate on the cell morphology were studied by AFM. The nanoporous alumina coated with polypyrrole nanowires was found to exhibit better cell adhesion and proliferation than polystyrene petridish, aluminum foil, 1st anodized and uncoated 2nd anodized alumina substrate. This study showed the potential of the polypyrrole nanowires/nanoporous alumina substrate as biocompatibility electroactive polymer substrate for both healthy and cancer cell cultures applications.     

Effect of vibration after filling on mechanical reliability in thin wall investment casting with fillability filling regime—part 1

A vibration technique is used in this study to explore the effect of low frequency vibration on the mechanical reliability of Al-7Si-Mg castings. The quality of castings is related to the number and the size of porosity and oxide film in thin wall investment casting. The quality of each method of casting (casting with and without vibration) was assessed by the density of the defects within the thin strips. Weibull distribution function is used to analyze the tensile strength data. The Weibull modulus is applied as a criterion to assess the mechanical reliability to identify the optimized casting condition. The results show that the effect of the vibration on the mechanical reliability is markedly dependent on acceleration of vibration, and the Weibull modulus is in the range of 12 to 12.7 when the acceleration is in range of 0 to 1 g; however, in more than 1 g, the range is 30–35.     

Coding-based ultra-wideband digital beamformer with significant hardware reduction

We propose a novel transceiver architecture for cognitive sensing. The architecture supports agile beam forming, jamming mitigation, as well as MIMO communications. An essential aspect of the new architecture is its departure from the traditional digital beamforming approaches. Specifically, a single ADC is assigned to a group of array elements instead of having one ADC per element. To facilitate this approach, code division multiplexing is applied to each received antenna signal prior to combining them for digitization using a single ADC. Thus full signal recovery is possible at digital baseband via decoding. The proposed architecture significantly reduces the number of ADCs and I/O channels and hence drastically improves size, weight, area, power and cost of the system with minimal impact on receiver signal-to-noise ratios.     

High‐Conductivity Polymer Nanocomposites Obtained by Tailoring the Characteristics of Carbon Nanotube Fillers

We present a detailed study of the influence of carbon nanotube (CNT) characteristics on the electrical conductivity of polystyrene nanocomposites produced using a latex‐based approach. We processed both industrially‐produced multi‐wall CNT (MWCNT) powders and MWCNTs from vertically‐aligned films made in‐house, and demonstrate that while the raw CNTs are individualized and dispersed comparably within the polymer matrix, the electrical conductivity of the final nanocomposites differs significantly due to the intrinsic characteristics of the CNTs. Owing to their longer length after dispersion, the percolation threshold observed using MWCNTs from vertically‐aligned films is five times lower than the value for industrially‐produced MWCNT powders. Further, owing to the high structural quality of the CNTs from vertically‐aligned films, the resulting composite films exhibit electrical conductivity of 10³ S m^?1 at 2 wt% CNTs. On the contrary, composites made using the industrially‐produced CNTs exhibit conductivity of only tens of S m^?1. To our knowledge, the measured electrical conductivity for CNT/PS composites using CNTs from vertically‐aligned films is by far the highest value yet reported for CNT/PS nanocomposites at this loading.     

Bat algorithm–based beamforming for mmWave massive MIMO systems

In this paper, an optimized analog beamforming scheme for millimeter‐wave (mmWave) massive MIMO system is presented. This scheme aims to achieve the near‐optimal performance.by searching for the optimized combination of analog precoder and combiner. In order to compensate for the occurrence of attenuation in the magnitude of mmWave signals, the codebook‐dependent analog beamforming in conjunction with precoding at transmitting end and combining signals at the receiving end is utilized. Nonetheless, the existing and traditional beamforming schemes involve a more difficult and complicated search for the optimal combination of analog precoder/combiner matrices from predefined codebooks. To solve this problem, we have referred to a modified bat algorithm to find the optimal combination value. This algorithm will explore the possible pairs of analog precoder/combiner as a way to come up with the best match in order to attain near‐optimal performance. The analysis shows that the optimized beamforming scheme presented in this paper can improve the performance that is very close to the beam steering benchmark that we have considered.     

Genome Assembly of a Relict Arabian Species of Daphnia O. F. Müller (Crustacea: Cladocera) Adapted to the Desert Life

The water flea Daphnia O.F. Müller 1776 (Crustacea: Cladocera) is an important model of recent evolutionary biology. Here, we report a complete genome of Daphnia (Ctenodaphnia) arabica (Crustacea: Cladocera), recently described species endemic to deserts of the United Arab Emirates. In this study, genome analysis of D. arabica was carried out to investigate its genomic differences, complexity as well as its historical origins within the subgenus Daphnia (Ctenodaphnia). Hybrid genome assembly of D. arabica resulted in ~116 Mb of the assembled genome, with an N50 of ~1.13 Mb (BUSCO score of 99.2%). From the assembled genome, in total protein coding, 5374 tRNA and 643 rRNA genes were annotated. We found that the D. arabica complete genome differed from those of other Daphnia species deposited in the NCBI database but was close to that of D. cf. similoides. However, its divergence time estimate sets D. arabica in the Mesozoic, and our demographic analysis showed a great reduction in its genetic diversity compared to other Daphnia species. Interestingly, the population expansion in its diversity occurred during the megadrought climate around 100 Ka ago, reflecting the adaptive feature of the species to arid and drought-affected environments. Moreover, the PFAM comparative analysis highlights the presence of the important domain SOSS complex subunit C in D. arabica, which is missing in all other studied species of Daphnia. This complex consists of a few subunits (A, B, C) working together to maintain the genome stability (i.e., promoting the reparation of DNA under stress). We propose that this domain could play a role in maintaining the fitness and survival of this species in the desert environment. The present study will pave the way for future research to identify the genes that were gained or lost in this species and identify which of these were key factors to its adaptation to the harsh desert environment.     

Automatic Data Clustering Based Mean Best Artificial Bee Colony Algorithm

Fuzzy C-means (FCM) is a clustering method that falls under unsupervised machine learning. The main issues plaguing this clustering algorithm are the number of the unknown clusters within a particular dataset and initialization sensitivity of cluster centres. Artificial Bee Colony (ABC) is a type of swarm algorithm that strives to improve the members’ solution quality as an iterative process with the utilization of particular kinds of randomness. However, ABC has some weaknesses, such as balancing exploration and exploitation. To improve the exploration process within the ABC algorithm, the mean artificial bee colony (MeanABC) by its modified search equation that depends on solutions of mean previous and global best is used. Furthermore, to solve the main issues of FCM, Automatic clustering algorithm was proposed based on the mean artificial bee colony called (AC-MeanABC). It uses the MeanABC capability of balancing between exploration and exploitation and its capacity to explore the positive and negative directions in search space to find the best value of clusters number and centroids value. A few benchmark datasets and a set of natural images were used to evaluate the effectiveness of AC-MeanABC. The experimental findings are encouraging and indicate considerable improvements compared to other state-of-the-art approaches in the same domain.