Futuristic CRISPR-based biosensing in the cloud and internet of things era: an overview

Multimedia Tools and Applications - Biosensors-based devices are transforming medical diagnosis of diseases and monitoring of patient signals. The development of smart and automated molecular...     

Development of the supply chain oriented quality assurance system for aerospace manufacturing SMEs and its implementation perspectives

Aerospace manufacturing SMEs are continuously facing the challenge on managing their supply chain and complying with the aerospace manufacturing quality standard requirement due to their lack of resources and the nature of business. In this paper, the ERP system based approach is presented to quality control and assurance work in light of seamless integration of in-process production data and information internally and therefore managing suppliers more effectively and efficiently. The Aerospace Manufacturing Quality Assurance Standard (BS/EN9100) is one of the most recognised and essential protocols for developing the industry-operated-and-driven quality assurance systems. The research investigates using the ERP based system as an enabler to implement BS/EN9100 quality management system at manufacturing SMEs and the associated implementation and application perspectives. An application case study on a manufacturing SME is presented by using the SAP based implementation, which helps further evaluate and validate the approach and application system development.     

Nestmate Recognition and the Role of Cuticular Hydrocarbons in the African Termite Raiding Ant <Emphasis Type="Italic">Pachycondyla analis</Emphasis>

Cuticular hydrocarbons (CHCs) are used for chemical communication among nestmates in many ant species, and they may play a role in the discrimination of nestmates and non-nestmates. Using the mandible opening response (MOR) bioassay, we tested the response of the African termite raiding ant, Pachycondyla analis, to CHC extracts of nestmates and non-nestmates. The ants were able to distinguish control chemical cues, from nestmate CHCs, and from non-nestmate CHCs, and, based on a CHC recognition threshold, aggression was demonstrated toward non-nestmates. Gas chromatography (GC) and GC-mass spectrometric analyses showed that CHC components of different ant colonies had chain lengths ranging from C₈ to C₃₁, comprising mainly n-alkanes, alkenes, and methyl branched alkanes, with the n-alkanes occurring in the same proportions among all colonies. The ants were grouped successfully according to their colonies of origin by using discriminant analysis of CHCs. We demonstrate that nestmate recognition occurs in P. analis, and that some of the cues involved are evidently alkenes and methyl-branched alkanes.     

Prevalence of helminth parasites found on vegetables sold in Maiduguri, Northeastern Nigeria

Background

For a healthy diet, people have been encouraged to eat lots of raw (fresh) vegetables and these can serve as vehicles of transmitting enteric parasitic pathogens throughout the process of planting to consumption. The aim of the present study was to determine the prevalence of helminth parasites found on vegetables sold in Maiduguri, northeastern Nigeria.

Methods

A total of 1130 samples of fresh salad vegetables obtained from retail markets were examined for helminth eggs and larvae by using standard methods.

Results

Out of the 300 lettuce, 250 cabbage, 200 garden egg, 150 carrot, 130 cucumber and 100 green-peppers samples examined, eggs of Ascaris spp., hookworm, Trichuris spp., Taenia/Echinococcus spp., and Strongyloides stercoralis were detected in 0.5%, 1.2%, 0.5%, 0.5%, and 0.6% respectively of all samples. The lettuce, cabbage, garden-egg, carrot, and cucumber samples were 8.2%, 2.0%, 1.0%, 1.3%, 2.3% contaminated with helminth parasites respectively with an overall prevalence of 3.5%. No helminth parasites were detected in green-peppers. Vegetables from the Gamboru Market were contaminated with helminth parasites more than the other markets (P < 0.05).

Conclusion

Proper washing of vegetables is imperative for a healthy diet as the results of this study showed the presence of helminth parasites from raw vegetables used as salads in Nigeria.     

Fine-tuning of neural computing using whale optimization algorithm for predicting compressive strength of concrete

Due to the important role of concrete in construction sector, a novel metaheuristic method, namely whale optimization algorithm (WOA), is employed for simulating 28-day compressive strength of concrete (CSC). To this end, the WOA is coupled with a neural network (NN) to optimize its computational parameters. Also, dragonfly algorithm (DA) and ant colony optimization (ACO) techniques are considered as the benchmark methods. The CSC influential parameters are cement, slag, water, fly ash, superplasticizer (SP), fine aggregate (FA), and coarse aggregate (CA). First, a population-based sensitivity analysis is carried out to achieve the most efficient structure of the proposed model. In this sense, the WOA-NN with the population size of 400 and five hidden nodes constructed the best-fitted network. The results revealed that the WOA-NN (Error = 2.0746 and Correlation = 0.8976) presents the most reliable prediction of the CSC, followed by the DA-NN (Error = 2.5138 and Correlation = 0.8209) and ACO-NN (Error = 2.8843 and Correlation = 0.8000) benchmark models. The findings showed that utilizing the WOA optimization technique, along with typical neural network, results in developing a promising tool for modeling the CSC.

     

Strategies for designing geometric transformations on quantum images

Three design strategies for constructing new geometric transformations on quantum images from other transformations are proposed. The strategies focus on the affected areas in the images, the separability, and smoothness of the transformations by exploiting a representation of images on quantum computers extensively. The complexity in terms of the number of basic gates and the depth of the corresponding circuits are analyzed to understand the advantages and disadvantages of each strategy. Examples to demonstrate the applicability of the proposed strategies are presented. The strategies provide high level tools to explore and analyze transformations which are necessary to build practical image processing applications on quantum computers.     

Application of PSO–ANN modelling for predicting the exergetic performance of a building integrated photovoltaic/thermal system

Engineering with Computers - The main objective of this study is to examine the feasibility of hybrid PSO–ANN technique to estimate the exergetic performance of a building integrated...     

Energy-efficient Nature-Inspired techniques in Cloud computing datacenters

Telecommunication Systems - Cloud computing is a systematic delivery of computing resources as services to the consumers via the Internet. Infrastructure as a Service (IaaS) is the capability...     

Consultants’ Perceptions on Construction Delay Analysis Methodologies

Resolving the delay claims that usually trail delayed completion of construction projects is beset with immense difficulties that often lead to disputes between the parties involved. The research reported in this paper is a part of a wider study aimed at developing a framework for reducing the attendant disputes and aiding cost-efficient dispute resolution. The focus of the part reported here is owner consultants’ perceptions on existing methodologies for analyzing project delay. Based on a survey of U.K. construction consulting organizations, the study examined, among others, the awareness and use of these methodologies, their perceived reliability, expert involvement, and obstacles to their use. The main study findings are: (i) delay analysis is a multidisciplinary task, with the project quantity surveyor often playing the leading role on the owner’s side; (ii) the simpler methodologies are used more often than the complex ones although the former are known to be less reliable than the latter; and (iii) the principal obstacles to the use of the sophisticated methodologies are: lack of adequate project information, the use of programmes not in CPM network form, and poorly updated programmes. It is thus argued that improvement in current programming and record-keeping practices will promote the use of the more reliable methodologies which, in turn, will facilitate smoother resolution of delay claims.     

Electrical Tree Image Segmentation Using Hybrid Multi Scale Line TrackingAlgorithm

Electrical trees are an aging mechanism most associated with partial discharge (PD) activities in crosslinked polyethylene (XLPE) insulation of high-voltage (HV) cables. Characterization of electrical tree structures gained considerable attention from researchers since a deep understanding of the tree morphology is required to develop new insulation material. Two-dimensional (2D) optical microscopy is primarily used to examine tree structures and propagation shapes with image segmentation methods. However, since electrical trees can emerge in different shapes such as bush-type or branch-type, treeing images are complicated to segment due to manifestation of convoluted tree branches, leading to a high misclassification rate during segmentation. Therefore, this study proposed a new method for segmenting 2D electrical tree images based on the multi-scale line tracking algorithm (MSLTA) by integrating batch processing method. The proposed method, h-MSLTA aims to provide accurate segmentation of electrical tree images obtained over a period of tree propagation observation under optical microscopy. The initial phase involves XLPE sample preparation and treeing image acquisition under real-time microscopy observation. The treeing images are then sampled and binarized in pre-processing. In the next phase, segmentation of tree structures is performed using the h-MSLTA by utilizing batch processing in multiple instances of treeing duration. Finally, the comparative investigation has been conducted using standard performance assessment metrics, including accuracy, sensitivity, specificity, Dice coefficient and Matthew’s correlation coefficient (MCC). Based on segmentation performance evaluation against several established segmentation methods, h-MSLTA achieved better results of 95.43% accuracy, 97.28% specificity, 69.43% sensitivity rate with 23.38% and 24.16% average improvement in Dice coefficient and MCC score respectively over the original algorithm. In addition, h-MSLTA produced accurate measurement results of global tree parameters of length and width in comparison with the ground truth image. These results indicated that the proposed method had a solid performance in terms of segmenting electrical tree branches in 2D treeing images compared to other established techniques.