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Developments in the use of ultra high performance fiber reinforced concrete as strengthening material
Get PDFUltra High Performance Fiber Reinforced Concrete (UHPFRC) is a novel material which has been developed the last few decades and has been applied in applications that require high strength, ductility and durability. Recently, the material has been applied in strengthening applications. The present study aims to investigate new techniques for the application of UHPFRC as strengthening material and to provide an insight into the parameters affecting the performance of elements strengthened with UHPFRC. The present research investigates for the first time the effectiveness of the use of dowels at the interface between UHPFRC and concrete to improve the connection between these two materials. Additionally, the effectiveness of the use of UHPFRC jackets for the strengthening of Reinforced Concrete (RC) beams has been examined. In the present research, a systematic experimental study has been conducted together with numerical study.
The results demonstrate that both examined techniques are effective and should be taken into consideration when UHPFRC is applied for strengthening applications. The dowels result in better bonding at the interface and can delay the formation of cracks in the post elastic phase, leading to reduced interface slip values and subsequent enhanced load bearing capacity. This technique should be taken into consideration to eliminate the risk of premature de-bonding of the strengthening layer. The construction of UHPFRC jackets on the other hand, results in a dramatic increase of the stiffness and the load carrying capacity of the strengthened elements and should be preferred in cases of heavily damaged RC members
Development and characterization of fish myofibrillar protein/chitosan/rosemary extract composite edible films and the improvement of lipid oxidation stability during the grass carp fillets storage
Get PDFBiofilm composition from fish myofibrillar protein (FMP) and chitosan solution (CS) incorporated with rosemary extract (RE) was developed and applied to monitor the freshness of fish fillets. The effects of different concentrations of RE as well as physical, mechanical, structural and functional properties of FMP/CS films were investigated. Films containing RE showed reduced water solubility and water vapor permeability and enhanced tensile strength and elongation at break. Results also showed good compatibility of the components and good dispersion of RE in the matrix. However, the content of RE (0.2%, v/v) added in the composite films produced aggregations and had negative effects on their film-forming properties. The antioxidant capacity of composite films was related to the level of RE and demonstrated by the DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical scavenging assay. Chilled grass carp fillets wrapped with different films to evaluate the preservative effect. Results of thiobarbituric acid reactive substances, pH value, Free amino acid and total volatile basic nitrogen indicated that FMP/CS/RE composite film could protect the fish fillet well and inhibit the lipid oxidation. The developed FMP/CS/RE composite films possess the potential to be applied as edible films in the food packaging industry and food cold chain transportation
The deuce-ace of Lassa Fever, Ebola virus disease and COVID-19 simultaneous infections and epidemics in West Africa: clinical and public health implications
No full textGlobally, the prevailing COVID-19 pandemic has caused unprecedented clinical and public health concerns with increasing morbidity and mortality. Unfortunately, the burden of COVID-19 in Africa has been further exacerbated by the simultaneous epidemics of Ebola virus disease (EVD) and Lassa Fever (LF) which has created a huge burden on African healthcare systems. As Africa struggles to contain the spread of the second (and third) waves of the COVID-19 pandemic, the number of reported cases of LF is also increasing, and recently, new outbreaks of EVD. Before the pandemic, many of Africa’s frail healthcare systems were already overburdened due to resource limitations in staffing and infrastructure, and also, multiple endemic tropical diseases. However, the shared epidemiological and pathophysiological features of COVID-19, EVD and LF as well their simultaneous occurrence in Africa may result in misdiagnosis at the onset of infection, an increased possibility of co-infection, and rapid and silent community spread of the virus(es). Other challenges include high population mobility across porous borders, risk of human-to-animal transmission and reverse zoonotic spread, and other public health concerns. This review highlights some major clinical and public health challenges toward responses to the COVID-19 pandemic amidst the deuce-ace of recurrent LF and EVD epidemics in Africa. Applying the One Health approach in infectious disease surveillance and preparedness is essential in mitigating emerging and re-emerging (co-)epidemics in Africa and beyond
Crisis and organisational learning: the hidden links between aviation and hospitality industry
Get PDFGlobal nature of hospitality and aviation is crucial when addressing the need for emphatic, effective and efficient Crisis Management (CM) of significant events. Nowadays, the “visibility” of adverse events is almost immediate worldwide. It projects to the general public, family, and friends of those involved directly or indirectly (e.g. emergency landing on Hudson River US Airways Flight 1549 (National Transportation Safety Board, 2010) or Mumbai Hotel Attacks (Garg, 2010)). Presently, aviation had more chances to deal with adverse events, mainly due to its higher profile and the World’s focus on its developments. Regardless of that, sudden and unexpected nature of the crisis affects organisations in both industries in unpredictable ways offering little or no time to react at the very moment when it happens
Testing sentinel-1 SAR interferometry data for airport runway monitoring: a geostatistical analysis
Get PDFMulti-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs)
Tree trunk inspections using a polarimetric GPR system
Get PDFIn this work, a novel signal processing framework for polarimetric GPR measurements is presented for inspection of tree trunks decay. The framework combines a polarimetric noise filter and an arc-shaped diffraction imaging algorithm. The polarimetric noise filter can increase the signal-to-noise ratio (SNR) of B-scans caused by the bark and the high-loss propriety of the tree trunk based on a 3D Pauli feature vector of the Bragg scattering theory. The arc-shaped diffraction stacking and an imaging aperture are then designed to suppress the effects of the irregular shape of the tree trunk on the signal. The proposed detection scheme is successfully validated with real tree trunk measurements. The viability of the proposed processing framework is demonstrated by the high consistency between the results and the real-truth trunk
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Strength of eccentrically loaded slender columns made with high-strength concrete
Get PDFA non-linear finite-element analysis model was developed to predict the strength analysis of high- strength-concrete slender columns. The studied parameters were compressive strength, load eccentricity, slenderness ratio, longitudinal and transverse reinforcement ratio. The model results were verified by comparison with analytical results and experimental results in literature. A parametric study was also carried out by comparing the model results with those obtained using design codes, which were predominantly based on data derived from tests on normal-strength concrete. The model proved to be a suitable tool for the strength analysis of slender high-strength-concrete columns. ACI-318-14 gave the most conservative predictions of the load-carrying capacity of centrally loaded columns but was close to the model results for eccentric loading. The procedures specified by BS EN 1992-1-1:2004 Eurocode 2 resulted in a significant under-estimation of the load-carrying capacity of slender columns, particularly for eccentric loading, and this increases with greater slenderness ratios. This is probably because the confinement index taken into consideration in the software was not consistent, ranging from 0.03% to 5.14%. It was concluded that special clauses need to be introduced in design codes for the accurate design of high-strength-concrete columns
You’ll never walk alone: snapshots of British football, love, loss, pride, shame, hope, inclusion and a song
Get PDFThis reflections explores some of the highs and lows of songs sung on the terraces at British football clubs. In particular I draw on some of my childhood experience to explore how songs can breathe hope and inclusio
In-situ and one-step preparation of protein film in capillary column for open tubular capillary electrochromatography enantioseparation
Get PDFIn this work, the phase-transitioned BSA (PTB) film using the mild and fast fabrication process adhered to the capillary inner wall uniformly and the fabricated PTB film-coated capillary column was applied to realize open tubular capillary electrochromatography (OT-CEC) enantioseparation. The enantioseparation ability of the PTB film-coated capillary was evaluated with eight pairs of chiral analytes including drugs and neurotransmitters, all achieving good resolution and symmetrical peak shape. For three consecutive runs, the relative standard deviations (RSD) of migration time for intra-day, inter-day and column-to-column repeatability were in the range of 0.3-3.5%, 0.2-4.9% and 2.1-7.7%, respectively. Moreover, the PTB film-coated capillary column ran continuously over 300 times with high separation efficiency. Therefore, the coating method based on BSA self-assembly supramolecular film can be extended to the preparation of other proteinaceous capillary columns.
Keywords: Open tubular capillary electrochromatography Proteinaceous phase-transitioned film Bovine serum albumin (BSA) Enantioseparation
In-situ preparatio
Alzheimer's disease detection using depthwise separable convolutional neural networks
Get PDFTo diagnose Alzheimer's disease (AD), neuroimaging methods such as magnetic resonance imaging have been employed. Recent progress in computer vision with deep learning (DL) has further inspired research focused on machine learning algorithms. However, a few limitations of these algorithms, such as the requirement for large number of training images and the necessity for powerful computers, still hinder the extensive usage of AD diagnosis based on machine learning. In addition, large number of training parameters and heavy computation make the DL systems difficult in integrating with mobile embedded devices, for example the mobile phones. For AD detection using DL, most of the current research solely focused on improving the classification performance, while few studies have been done to obtain a more compact model with less complexity and relatively high recognition accuracy. In order to solve this problem and improve the efficiency of the DL algorithm, a deep separable convolutional neural network model is proposed for AD classification in this paper. The depthwise separable convolution (DSC) is used in this work to replace the conventional convolution. Compared to the traditional neural networks, the parameters and computing cost of the proposed neural network are found greatly reduced. The parameters and computational costs of the proposed neural network are found to be significantly reduced compared with conventional neural networks. With its low power consumption, the proposed model is particularly suitable for embedding mobile devices. Experimental findings show that the DSC algorithm, based on the OASIS magnetic resonance imaging dataset, is very successful for AD detection. Moreover, transfer learning is employed in this work to improve model performance. Two trained models with complex networks, namely AlexNet and GoogLeNet, are used for transfer learning, with average classification rates of 91.40%, 93.02% and a less power consumption