Search results

Fibre content can influence the intensity of odour that develops within clothing fabrics. However, little is known about how effective laundering is at removing malodours in clothing which differ by fibre type. The purpose of this paper is to investigate whether a selected cotton fabric differed in odour intensity following multiple wear and wash cycles compared to a polyester fabric.

Eight (male and female) participants wore bisymmetrical cotton/polyester t-shirts during 20 exercise sessions over a ten-week trial period. Odour was evaluated via a sensory panel, bacterial populations were counted and selected odorous volatile organic compounds were measured with comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry detection. Analysis occurred both before and after the final (20th) wash cycle.

Findings showed that laundering was effective in reducing overall odour intensity (p0.001) and bacterial populations (p0.001) in both cotton and polyester fabrics. Odour was most intense on polyester fabrics following wear, not just before, but also after washing (p0.001); although, no differences in bacterial counts were found between fibre types (p>0.05). Chemical analysis found C4-C8 chained carboxylic acids on both types of unwashed fabrics, although they were more prevalent on polyester.

The findings suggest that the build-up of odour in polyester fabrics may be cumulative as important odorants such as the carboxylic acids were not as effectively removed from polyester compared to cotton.

Advancements in real-time water monitoring technologies permit rapid detection of water quality, and threats from waste loads. Water Framework Directive mandating the establishment of Member States’ water resources monitoring, presence of hazardous contaminants in effluents, and perception of vulnerability of water distribution system to attacks, have spurred technical and economic interests. The paper aims to discuss these issues.

As alternative to traditional analyzers, chemosensors, operate according to physical principles, without sample collection (online), and are capable of supplying parameter values continuously and in real-time. Their low selectivity and stability issues have been overcome by technological developments. This review paper contains a comprehensive survey of existing and expected online monitoring technologies for measurement/detection of pollutants in water.

The state-of-the-art in online water monitoring is presented. Application examples are reported. Monitoring costs will become a lesser part of a water utility budget due to the fact that automation and technological simplification will abate human cost factors, and reduce the complexity of laboratory procedures.

An overview of applicable instrumentation, and forthcoming developments, is given. Technological development in this field is very rapid, and astonishing advances are anticipated in several areas (fingerprinting, optochemical sensors, biosensors, molecular techniques). Online monitoring is becoming an ever-important tool not only for compliance control or plant management purposes, but also as a useful approach to pollution control and reduction, minimizing the environmental impact of discharges.

Sensing technology has been extensively researched and used due to its applications in industrial production and daily life. Due to inherent limitations of conventional silicon-based technology, researchers are now-a-days paying more attention to flexible electronics to design low-cost, high-sensitivity devices. This observational and analytical study aims to emphasis on carbon monoxide gas sensor. This review also focuses the challenges faced by flexible devices, offers the most recent research on paper-based gas sensors and pays special focus on various sensing materials and fabrication techniques.

To get the better insight into opportunities for future improvement, a number of research papers based on sensors were studied and realized the need to design carbon monoxide gas sensor. A number of parameters were then gone through to decide the flexibility parameter to be considered for design purposes. This review also focuses on the challenges faced by flexible devices and how they can be overcome.

It has been shown that carbon monoxide gas, being most contaminated gas, needs to be fabricated to sense low concentration at room temperature, considering flexibility as an important parameter. Regarding this parameter, some tests must be done to test whether the structure sustains or degrades after bending. The parameters required to perform bending are also described.

Due to inherent limitations of conventional silicon-based technology, now-a-days attention is paid towards flexible electronics to design low-cost, high-sensitivity devices. A number of research articles are provided in the literature concerning gas sensing for different applications using several sensing principles. This study aims to provide a comprehensive overview of recent developments in carbon monoxide gas sensors along with the design possibilities for flexible paper-based gas sensors. All the aspects have been taken into consideration for the fabrication, starting with paper characterization techniques, various sensing materials, manufacturing methodologies, challenges in the fabrication of flexible devices and effects of bending and humidity on the sensing performance.

This paper aims to investigate influence of extraction solvent on the efficacy of apricot pomace extract (APE) as a sustainable corrosion inhibitor for mild steel in sodium chloride solution.

The chemical profiles of the extracts were analyzed using gas chromatography–mass spectrometry. Total phenolic, total flavonoid content and antioxidant properties of the extracts were determined. Besides, gravimetric, potentiodynamic polarization and atomic force microscopy were used to study the corrosion inhibition. The effect of immersion period on inhibition efficiency was evaluated. The reaction mechanism of the inhibitor was also discussed.

Corrosion inhibition decreasing is in the following order: solution of 2-propanol/ethanol apricot pomace (E/PAPE) extract > ethanol (EAPE) > 2-propanol (PAPE). The gravimetric, polarization measurements and surface analysis revealed that the growth of inhibitory properties is prolonged, and corrosion rate reduction after 40–48 h of exposure was studied.

APEs play an important role in the corrosion inhibition of mild steel in sodium chloride solution. Moreover, its application is potentially possible in industries.

The results contribute to the integrated valorization of food waste.

The different compositions of the conversion/oxidation products of organic substances in solution were studied. The formation of polymerized flavanol-aldehyde adducts and oxidized quinone compounds or tautomers structures because of extract transformation in water causes main corrosion reduction in 40–48 h.

The electronic nose is an array of chemical or gas sensors and associated with a pattern-recognition framework competent in identifying and classifying odorant or non-odorant and simple or complex gases. Despite more than 30 years of research, the robust e-nose device is still limited. Most of the challenges towards reliable e-nose devices are associated with the non-stationary environment and non-stationary sensor behaviour. Data distribution of sensor array response evolves with time, referred to as non-stationarity. The purpose of this paper is to provide a comprehensive introduction to challenges related to non-stationarity in e-nose design and to review the existing literature from an application, system and algorithm perspective to provide an integrated and practical view.

The authors discuss the non-stationary data in general and the challenges related to the non-stationarity environment in e-nose design or non-stationary sensor behaviour. The challenges are categorised and discussed with the perspective of learning with data obtained from the sensor systems. Later, the e-nose technology is reviewed with the system, application and algorithmic point of view to discuss the current status.

The discussed challenges in e-nose design will be beneficial for researchers, as well as practitioners as it presents a comprehensive view on multiple aspects of non-stationary learning, system, algorithms and applications for e-nose. The paper presents a review of the pattern-recognition techniques, public data sets that are commonly referred to as olfactory research. Generic techniques for learning in the non-stationary environment are also presented. The authors discuss the future direction of research and major open problems related to handling non-stationarity in e-nose design.

The authors first time review the existing literature related to learning with e-nose in a non-stationary environment and existing generic pattern-recognition algorithms for learning in the non-stationary environment to bridge the gap between these two. The authors also present details of publicly available sensor array data sets, which will benefit the upcoming researchers in this field. The authors further emphasise several open problems and future directions, which should be considered to provide efficient solutions that can handle non-stationarity to make e-nose the next everyday device.

This paper presents the results of laboratory experiments that investigate the removal of volatile organic compounds from saturated soils through the use of air sparging. Three series of experiments were performed in a column test apparatus using two different soils to represent actual field conditions, namely, a fine gravel and a medium‐to‐fine Ottawa sand (both obtained from sources near Chicago, Illinois, USA) contaminated with toluene, a major constituent of petroleum products. The results showed that toluene was removed from gravel very efficiently using air sparging; complete removal was achieved using a variety of air flow rates. However the toluene removal rates in tests using sand were significantly less. Even at the highest air flow rate used during testing, complete toluene removal took eight times longer than in comparable tests using gravel. With low air flow rates this was not achieved even after 17 hours of testing. It was further found that the injection of foams generated with surfactants, SDS and witconol SN70, at low air flow rates during the use of air sparging was found to accelerate the bulk removal of toluene in sand, but the use of surfactants did not facilitate the removal of residual levels of contamination.

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

This study aims at developing a comprehensive model for the analysis of electro-osmotic flow (EOF) through a fluid-saturated porous medium. To fully understand and exploit a number of applications, such a model for EOF through porous media is essential.

The proposed model is based on a generalised set of governing equations used for modelling flow through fluid saturated porous media. These equations are modified to incorporate appropriate modifications to represent electro-osmosis (EO). The model is solved through the finite element method (FEM). The validity of the proposed numerical model is demonstrated by comparing the numerical results of internal potential and velocity distribution with corresponding analytical expressions. The model introduced is also used to carry out a sensitivity analysis of the main parameters that control EOF.

The analysis carried out confirms that EO in free channels without porous obstruction is effective only at small scales, as largely discussed in the available literature. Using porous media makes EO independent of the channel scale. Indeed, as the channel size increases, the presence of the charged porous medium is essential to induce fluid flow. Moreover, results demonstrate that flow is significantly affected by the characteristics of the porous medium, such as particle size, and by the zeta potential acting on the charged surfaces.

To the best of the authors’ knowledge, a comprehensive FEM model, based on the generalised equations to simulate EOF in porous media, is proposed here for the first time.

This article introduces the Special Issue on Sustainable Management of Heritage Buildings in long-term perspective.

It starts by reviewing the gaps in knowledge and practice which led to the creation and implementation of the research project SyMBoL—Sustainable Management of Heritage Buildings in long-term perspective funded by the Norwegian Research Council over the 2018–2022 period. The SyMBoL project is the motivation at the base of this special issue.

The editorial paper briefly presents the main outcomes of SyMBoL. It then reviews the contributions to the Special Issue, focussing on the connection or differentiation with SyMBoL and on multidisciplinary findings that address some of the initial referred gaps.

The article shortly summarizes topics related to sustainable preservation of heritage buildings in time of reduced resources, energy crisis and impacts of natural hazards and global warming. Finally, it highlights future research directions targeted to overcome, or partially mitigate, the above-mentioned challenges, for example, taking advantage of no sestructive techniques interoperability, heritage building information modelling and digital twin models, and machine learning and risk assessment algorithms.

This study aims to describe a bibliometric analysis of recent articles addressing the applications of e- noses with particular emphasis on those dealing with fuel-related products. Documents covering the general area of e-nose research and published between 1975 and 2021 were retrieved from the Web of Science database, and peer-reviewed articles were selected and appraised according to specific descriptors and criteria.

Analyses were performed by mapping the knowledge domain using the software tools VOSviewer and RStudio. It was possible to identify the countries, research organizations, authors and disciplines that were most prolific in the area, together with the most cited articles and the most frequent keywords. A total of 3,921 articles published in peer-reviewed journals were initially retrieved but only 47 (1.19%) described fuel-related e-nose applications with original articles published in indexed journals. However, this number was reduced to 38 (0.96%) articles strictly related to the target subject.

Rigorous appraisal of these documents yielded 22 articles that could be classified into two groups, those aimed at predicting the values of key parameters and those dealing with the discrimination of samples. Most of these 22 selected articles (68.2%) were published between 2017 and 2021, but little evidence was apparent of international collaboration between researchers and institutions currently working on this topic. The strategy of switching energy systems away from fossil fuels towards low-carbon renewable technologies that has been adopted by many countries will generate substantial research opportunities in the prediction, discrimination and quantification of volatiles in biofuels using e-nose.

It is important to highlight that the greatest difficulty in using the e-nose is the interpretation of the data generated by the equipment; most studies have so far used the maximum value of the electrical resistance signal of each e-nose sensor as the only data provided by this sensor; however, from 2019 onwards, some works began to consider the entire electrical resistance curve as a data source, extracting more information from it.

This study opens a new and promising way for the effective use of e-nose as a fuel analysis instrument, as low-cost sensors can be developed for use with the new data analysis methodology, enabling the production of portable, cheaper and more reliable equipment.