Search results for: thermal processing

Authors: R. Tamborrino, F. Rinaudo

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Digital technologies offer possibilities to effectively convert historical archives into instruments of knowledge able to provide a guide for the interpretation of historical phenomena. Digital conversion and management of those documents allow the possibility to add other sources in a unique and coherent model that permits the intersection of different data able to open new interpretations and understandings. Urban history uses, among other sources, the inventories that register human activities in a specific space (e.g. cadastres, censuses, etc.). The geographic localisation of that information inside cartographic supports allows for the comprehension and visualisation of specific relationships between different historical realities registering both the urban space and the peoples living there. These links that merge the different nature of data and documentation through a new organisation of the information can suggest a new interpretation of other related events. In all these kinds of analysis, the use of GIS platforms today represents the most appropriate answer. The design of the related databases is the key to realise the ad-hoc instrument to facilitate the analysis and the intersection of data of different origins. Moreover, GIS has become the digital platform where it is possible to add other kinds of data visualisation. This research deals with the industrial development of Turin at the beginning of the 20th century. A census of factories realized just prior to WWI provides the opportunity to test the potentialities of GIS platforms for the analysis of urban landscape modifications during the first industrial development of the town. The inventory includes data about location, activities, and people. GIS is shaped in a creative way linking different sources and digital systems aiming to create a new type of platform conceived as an interface integrating different kinds of data visualisation. The data processing allows linking this information to an urban space, and also visualising the growth of the city at that time. The sources, related to the urban landscape development in that period, are of a different nature. The emerging necessity to build, enlarge, modify and join different buildings to boost the industrial activities, according to their fast development, is recorded by different official permissions delivered by the municipality and now stored in the Historical Archive of the Municipality of Turin. Those documents, which are reports and drawings, contain numerous data on the buildings themselves, including the block where the plot is located, the district, and the people involved such as the owner, the investor, and the engineer or architect designing the industrial building. All these collected data offer the possibility to firstly re-build the process of change of the urban landscape by using GIS and 3D modelling technologies thanks to the access to the drawings (2D plans, sections and elevations) that show the previous and the planned situation. Furthermore, they access information for different queries of the linked dataset that could be useful for different research and targets such as economics, biographical, architectural, or demographical. By superimposing a layer of the present city, the past meets to the present-industrial heritage, and people meet urban history.

Keywords: digital urban history, census, digitalisation, GIS, modelling, digital humanities

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Authors: R. R. Galiev, I. I. Lykov, A. E. Shitikov, I. A. Bilenko

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Dual-comb interferometry is based on the mixing of two optical frequency combs with slightly different lines spacing which results in the mapping of the optical spectrum into the radio-frequency domain for future digitizing and numerical processing. The dual-comb approach enables diverse applications, including metrology, fast high-precision spectroscopy, and distance range. Ordinary frequency-modulated continuous-wave (FMCW) laser-based Light Identification Detection and Ranging systems (LIDARs) suffer from two main disadvantages: slow and unreliable mechanical, spatial scan and a rather wide linewidth of conventional lasers, which limits speed measurement resolution. Dual-comb distance measurements with Allan deviations down to 12 nanometers at averaging times of 13 microseconds, along with ultrafast ranging at acquisition rates of 100 megahertz, allowing for an in-flight sampling of gun projectiles moving at 150 meters per second, was previously demonstrated. Nevertheless, pump lasers with EDFA amplifiers made the device bulky and expensive. An alternative approach is a direct coupling of the laser to a reference microring cavity. Backscattering can tune the laser to the eigenfrequency of the cavity via the so-called self-injection locked (SIL) effect. Moreover, the nonlinearity of the cavity allows a solitonic frequency comb generation in the very same cavity. In this work, we developed a fully integrated, power-efficient, electrically driven dual-micro comb source based on the semiconductor lasers SIL to high-quality integrated Si3N4 microresonators. We managed to obtain robust 1400-1700 nm combs generation with a 150 GHz or 1 THz lines spacing and measure less than a 1 kHz Lorentzian withs of stable, MHz spaced beat notes in a GHz band using two separated chips, each pumped by its own, self-injection locked laser. A deep investigation of the SIL dynamic allows us to find out the turn-key operation regime even for affordable Fabry-Perot multifrequency lasers used as a pump. It is important that such lasers are usually more powerful than DFB ones, which were also tested in our experiments. In order to test the advantages of the proposed techniques, we experimentally measured a minimum detectable speed of a reflective object. It has been shown that the narrow line of the laser locked to the microresonator provides markedly better velocity accuracy, showing velocity resolution down to 16 nm/s, while the no-SIL diode laser only allowed 160 nm/s with good accuracy. The results obtained are in agreement with the estimations and open up ways to develop LIDARs based on compact and cheap lasers. Our implementation uses affordable components, including semiconductor laser diodes and commercially available silicon nitride photonic circuits with microresonators.

Keywords: dual-comb spectroscopy, LIDAR, optical microresonator, self-injection locking

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Authors: Vitor M. Vilas Boas, Cleison D. Silva, Gustavo S. Mafra, Alexandre Trofino Neto

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Motor imagery (MI) based brain-computer interfaces (BCI) uses event-related (de)synchronization (ERS/ ERD), typically recorded using electroencephalography (EEG), to translate brain electrical activity into control commands. To mitigate undesirable artifacts and noise measurements on EEG signals, methods based on band-pass filters defined by a specific frequency band (i.e., 8 – 30Hz), such as the Infinity Impulse Response (IIR) filters, are typically used. Spatial techniques, such as Common Spatial Patterns (CSP), are also used to estimate the variations of the filtered signal and extract features that define the imagined motion. The CSP effectiveness depends on the subject's discriminative frequency, and approaches based on the decomposition of the band of interest into sub-bands with smaller frequency ranges (SBCSP) have been suggested to EEG signals classification. However, despite providing good results, the SBCSP approach generally increases the computational cost of the filtering step in IM-based BCI systems. This paper proposes the use of the Fast Fourier Transform (FFT) algorithm in the IM-based BCI filtering stage that implements SBCSP. The goal is to apply the FFT algorithm to reduce the computational cost of the processing step of these systems and to make them more efficient without compromising classification accuracy. The proposal is based on the representation of EEG signals in a matrix of coefficients resulting from the frequency decomposition performed by the FFT, which is then submitted to the SBCSP process. The structure of the SBCSP contemplates dividing the band of interest, initially defined between 0 and 40Hz, into a set of 33 sub-bands spanning specific frequency bands which are processed in parallel each by a CSP filter and an LDA classifier. A Bayesian meta-classifier is then used to represent the LDA outputs of each sub-band as scores and organize them into a single vector, and then used as a training vector of an SVM global classifier. Initially, the public EEG data set IIa of the BCI Competition IV is used to validate the approach. The first contribution of the proposed method is that, in addition to being more compact, because it has a 68% smaller dimension than the original signal, the resulting FFT matrix maintains the signal information relevant to class discrimination. In addition, the results showed an average reduction of 31.6% in the computational cost in relation to the application of filtering methods based on IIR filters, suggesting FFT efficiency when applied in the filtering step. Finally, the frequency decomposition approach improves the overall system classification rate significantly compared to the commonly used filtering, going from 73.7% using IIR to 84.2% using FFT. The accuracy improvement above 10% and the computational cost reduction denote the potential of FFT in EEG signal filtering applied to the context of IM-based BCI implementing SBCSP. Tests with other data sets are currently being performed to reinforce such conclusions.

Keywords: brain-computer interfaces, fast Fourier transform algorithm, motor imagery, sub-band common spatial patterns

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Authors: Mona Mihailescu, Rebeca Tudor, Irina A. Paun, Cristian Kusko, Eugen I. Scarlat, Mihai Kusko

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Specific intensity distributions in the laser beams are required in many fields: optical communications, material processing, microscopy, optical tweezers. In optical communications, the information embedded in specific beams and the superposition of multiple beams can be used to increase the capacity of the communication channels, employing spatial modulation as an additional degree of freedom, besides already available polarization and wavelength multiplexing. In this regard, optical vortices present interest due to their potential to carry independent data which can be multiplexed at the transmitter and demultiplexed at the receiver. Also, in the literature were studied their combinations: 1) axial or perpendicular superposition of multiple optical vortices or 2) with other laser beam types: Bessel, Airy. Optical vortices, characterized by stationary ring-shape intensity and rotating phase, are achieved using computer generated holograms (CGH) obtained by simulating the interference between a tilted plane wave and a wave passing through a helical phase object. Here, we propose a method to combine information through the reunion of two CGHs. One is obtained using the helical phase distribution, characterized by its topological charge, m. The other is obtained using conical phase distribution, characterized by its radial factor, r0. Each CGH is obtained using plane wave with different tilts: km and kr for CGH generated from helical phase object and from conical phase object, respectively. These reunions of two CGHs are calculated to be phase optical elements, addressed on the liquid crystal display of a spatial light modulator, to optically process the incident beam for investigations of the diffracted intensity pattern in far field. For parallel reunion of two CGHs and high values of the ratio between km and kr, the bright ring from the first diffraction order, specific for optical vortices, is changed in an asymmetric intensity pattern: a number of circle arcs. Both diffraction orders (+1 and -1) are asymmetrical relative to each other. In different planes along the optical axis, it is observed that this asymmetric intensity pattern rotates around its centre: in the +1 diffraction order the rotation is anticlockwise and in the -1 diffraction order, the rotation is clockwise. The relation between m and r0 controls the diameter of the circle arcs and the ratio between km and kr controls the number of arcs. For perpendicular reunion of the two CGHs and low values of the ratio between km and kr, the optical vortices are multiplied and focalized in different planes, depending on the radial parameter. The first diffraction order contains information about both phase objects. It is incident on the phase masks placed at the receiver, computed using the opposite values for topological charge or for the radial parameter and displayed successively. In all, the proposed method is exploited in terms of constructive parameters, for the possibility offered by the combination of different types of beams which can be used in robust optical communications.

Keywords: asymmetrical diffraction orders, computer generated holograms, conical phase distribution, optical vortices, spatial light modulator

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Authors: B. Körner

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This paper compares deviant behaviour in two different readings: 1) as symptomatic for so-called ‘mental illness’ and 2) as part of artistic creation. It analyses works of performance art in the respective frames of psychiatric evaluation and performance studies. This speculative comparison offers an alternative interpretation of mad behaviour beyond pathologisation. It questions the distinction of psychiatric diagnosis, which can contribute to reducing the stigmatisation of mad people. The stigma associated with madness entails exclusion, prejudice, and systemic oppression. Symptoms of psychiatric diagnoses can be considered as behaviour exceptional to the psychological norm. This deviant behaviour constitutes an outsider role which is also defining for the societal role of ‘the artist’, whose transgressions of the norm are expected and celebrated. The research proposes the term ‘artistic exceptionalism’ for this phenomenon. In this study, a set of performance artworks are analysed within the frame of an art-theoretical interpretation and as if they were the basis of a psychiatric assessment. This critical comparison combines the perspective on ‘mental illness’ of mad studies with methods of interpretation used in performance studies. The research employs auto theory and artistic research; interweaving lived experience with scientific theory building through the double role of the author as both performance artist and survivor researcher. It is a distinctly personal and mad thought experiment. The research proposes three major categories of artistic strategies approaching madness: (a) confronting madness (processing and publicly addressing one's own experiences with mental distress through artistic creation), (b) creating critical conditions (conscious or unconscious, voluntary or involuntary creation of crisis situations in order to create an intense experience for a work of art), and (c) symptomatic strategies. This paper focuses on the last of the three categories: symptomatic strategies. These can be described as artistic methods with parallels to forms of coping with and/or symptoms of ‘mental disorders.’ These include, for example feverish activity, a bleak worldview, additional perceptions, an urge for order, and the intensification of emotional experience. The proposed categories are to be understood as a spectrum of approaches that are not mutually exclusive. This research does not aim to diagnose or pathologise artists or their strategies; disease value is neither sought nor assumed. Neither does it intend to belittle psychological suffering, implying that it cannot be so bad if it is productive for artists. It excludes certain approaches that romanticise and/or exoticise mental distress, for example, artistic portrayal of people in mental crisis (e.g., documentary-observational or exoticising depictions) or the deliberate and exaggerated imitation of their forms of expression and behaviour as ‘authentic’ (e.g., Art Brut). These are based on the othering of the Mad and thus perpetuate the social stigma to which they are subjected. By noting that the same deviant behaviour can be interpreted as the opposite in different contexts, this research offers an alternative approach to madness beyond the confines of psychiatry. It challenges the distinction of psychiatric diagnosis and exposes its social constructedness. Hereby, it aims to empower survivors and reduce the stigmatisation of madness.

Keywords: artistic research, mad studies, mental health, performance art, psychiatric stigma

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Authors: Georgios Boustras, Cleo Varianou Mikellidou, Christos Argyropoulos

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Summer 2021 was marked by a number of prolific fires in the EU (Greece, Cyprus, France) as well as outside the EU (USA, Turkey, Israel). This series of dramatic events have stretched national civil protection systems and first responders in particular. Despite the introduction of National, Regional and International frameworks (e.g. rescEU), a number of challenges have arisen, not only related to climate change. RESPOND-A (funded by the European Commission by Horizon 2020, Contract Number 883371) introduces a unique five-tier project architectural structure for best associating modern telecommunications technology with novel practices for First Responders of saving lives, while safeguarding themselves, more effectively and efficiently. The introduced architecture includes Perception, Network, Processing, Comprehension, and User Interface layers, which can be flexibly elaborated to support multiple levels and types of customization, so, the intended technologies and practices can adapt to any European Environment Agency (EEA)-type disaster scenario. During the preparation of the RESPOND-A proposal, some of our First Responder Partners expressed the need for an information management system that could boost existing emergency response tools, while some others envisioned a complete end-to-end network management system that would offer high Situational Awareness, Early Warning and Risk Mitigation capabilities. The intuition behind these needs and visions sits on the long-term experience of these Responders, as well, their smoldering worry that the evolving threat of climate change and the consequences of industrial accidents will become more frequent and severe. Three large-scale pilot studies are planned in order to illustrate the capabilities of the RESPOND-A system. The first pilot study will focus on the deployment and operation of all available technologies for continuous communications, enhanced Situational Awareness and improved health and safety conditions for First Responders, according to a big fire scenario in a Wildland Urban Interface zone (WUI). An important issue will be examined during the second pilot study. Unobstructed communication in the form of the flow of information is severely affected during a crisis; the flow of information between the wider public, from the first responders to the public and vice versa. Call centers are flooded with requests and communication is compromised or it breaks down on many occasions, which affects in turn – the effort to build a common operations picture for all firstr esponders. At the same time the information that reaches from the public to the operational centers is scarce, especially in the aftermath of an incident. Understandably traffic if disrupted leaves no other way to observe but only via aerial means, in order to perform rapid area surveys. Results and work in progress will be presented in detail and challenges in relation to civil protection will be discussed.

Keywords: first responders, safety, civil protection, new technologies

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Svetlana Petrikova, Alexander Yu Kostinskiy

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Management of research evaluation in the Higher School of Economics (HSE) originates from the HSE Academic Fund created in 2004 to facilitate and support academic research and presents its results to international academic community. As the means to inspire the applicants, science projects went through competitive selection process evaluated by the group of experts. Drastic development of HSE, quantity of applied projects for each Academic Fund competition and the need to coordinate the conduct of expert evaluation resulted in founding of the Office for Research Evaluation in 2013. The Office’s primary objective is management of research evaluation of science projects. The standards to conduct the evaluation are defined as follows: - The exercise of the process approach, the unification of the functioning of department. - The uniformity of regulatory, organizational and methodological framework. - The development of proper on-line evaluation system. - The broad involvement of external Russian and international experts, the renouncement of the usage of own employees. - The development of an algorithm to make a correspondence between experts and science projects. - The methodical usage of opened/closed international and Russian databases to extend the expert database. - The transparency of evaluation results – free access to assessment while keeping experts confidentiality. The management of research evaluation of projects is based on the sole standard, organization and financing. The standard way of conducting research evaluation at HSE is based upon Regulations on basic principles for research evaluation at HSE. These Regulations have been developed from the moment of establishment of the Office for Research Evaluation and are based on conventional corporate standards for regulatory document management. The management system of research evaluation is implemented on the process approach basis. Process approach means deployment of work as a process, which is the aggregation of interrelated and interacting activities processing inputs into outputs. Inputs are firstly client asking for the assessment to be conducted, defining the conditions for organizing and carrying of the assessment and secondly the applicant with proper for the competition application; output is assessment given to the client. While exercising process approach to clarify interrelation and interacting main parties or subjects of the assessment are determined and the way for interaction between them forms up. Parties to expert assessment are: - Ordering Party – The department of the university taking the decision to subject a project to expert assessment; - Providing Party – The department of the university authorized to provide such assessment by the Ordering Party; - Performing Party – The legal and natural entities that have expertise in the area of research evaluation. Experts assess projects in accordance with criteria and states of expert opinions approved by the Ordering Party. Objects of assessment generally are applications or HSE competition project reports. Mainly assessments are deployed for internal needs, i.e. the most ordering parties are HSE branches and departments, but assessment can also be conducted for external clients. The financing of research evaluation at HSE is based on the established corporate culture and traditions of HSE.

Keywords: expert assessment, management of research evaluation, process approach, research evaluation

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Authors: Muhammad Karim Ahmadzai

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Floods are natural phenomena and are an integral part of the water cycle. The majority of them are the result of climatic conditions, but are also affected by the geology and geomorphology of the area, topography and hydrology, the water permeability of the soil and the vegetation cover, as well as by all kinds of human activities and structures. However, from the moment that human lives are at risk and significant economic impact is recorded, this natural phenomenon becomes a natural disaster. Flood management is now a key issue at regional and local levels around the world, affecting human lives and activities. The majority of floods are unlikely to be fully predicted, but it is feasible to reduce their risks through appropriate management plans and constructions. The aim of this Case Study is to identify, and map areas of flood risk in the Khinch District of Panjshir Province, Afghanistan specifically in the area of Peshghore, causing numerous damages. The main purpose of this study is to evaluate the contribution of remote sensing technology and Geographic Information Systems (GIS) in assessing the susceptibility of this region to flood events. Panjsher is facing Seasonal floods and human interventions on streams caused floods. The beds of which have been trampled to build houses and hotels or have been converted into roads, are causing flooding after every heavy rainfall. The streams crossing settlements and areas with high touristic development have been intensively modified by humans, as the pressure for real estate development land is growing. In particular, several areas in Khinch are facing a high risk of extensive flood occurrence. This study concentrates on the construction of a flood susceptibility map, of the study area, by combining vulnerability elements, using the Analytical Hierarchy Process/ AHP. The Analytic Hierarchy Process, normally called AHP, is a powerful yet simple method for making decisions. It is commonly used for project prioritization and selection. AHP lets you capture your strategic goals as a set of weighted criteria that you then use to score projects. This method is used to provide weights for each criterion which Contributes to the Flood Event. After processing of a digital elevation model (DEM), important secondary data were extracted, such as the slope map, the flow direction and the flow accumulation. Together with additional thematic information (Landuse and Landcover, topographic wetness index, precipitation, Normalized Difference Vegetation Index, Elevation, River Density, Distance from River, Distance to Road, Slope), these led to the final Flood Risk Map. Finally, according to this map, the Priority Protection Areas and Villages and the structural and nonstructural measures were demonstrated to Minimize the Impacts of Floods on residential and Agricultural areas.

Keywords: flood hazard, flood risk map, flood mitigation measures, AHP analysis

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Authors: Jessie Rapoza, Petr Moroshkin, Jimmy Xu

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Chirality is omnipresent, in nature, in life, and in the field of physics. One intriguing example is the homochirality that has remained a great secret of life. Another is the pairs of mirror-image molecules – enantiomers. They are identical in atomic composition and therefore indistinguishable in the scalar physical properties. Yet, they can be either therapeutic or toxic, depending on their chirality. Recent studies suggest a potential link between abnormal levels of certain D-amino acids and some serious health impairments, including schizophrenia, amyotrophic lateral sclerosis, and potentially cancer. Although indistinguishable in their scalar properties, the chirality of a molecule reveals itself in interaction with the surrounding of a certain chirality, or more generally, a broken mirror-symmetry. In this work, we report on a system for chiral molecule detection, in which the mirror-symmetry is doubly broken, first by asymmetric structuring a nanopatterned plasmonic surface than by the incidence of circularly polarized light (CPL). In this system, the incident circularly-polarized light induces a surface plasmon polariton (SPP) wave, propagating along the asymmetric plasmonic surface. This SPP field itself is chiral, evanescently bound to a near-field zone on the surface (~10nm thick), but with an amplitude greatly intensified (by up to 104) over that of the incident light. It hence probes just the molecules on the surface instead of those in the volume. In coupling to molecules along its path on the surface, the chiral SPP wave favors one chirality over the other, allowing for chirality detection via the change in an optical rectification current measured at the edges of the sample. The asymmetrically structured surface converts the high-frequency electron plasmonic-oscillations in the SPP wave into a net DC drift current that can be measured at the edge of the sample via the mechanism of optical rectification. The measured results validate these design concepts and principles. The observed optical rectification current exhibits a clear differentiation between a pair of enantiomers. Experiments were performed by focusing a 1064nm CW laser light at the sample - a gold grating microchip submerged in an approximately 1.82M solution of either L-arabinose or D-arabinose and water. A measurement of the current output was then recorded under both rights and left circularly polarized lights. Measurements were recorded at various angles of incidence to optimize the coupling between the spin-momentums of the incident light and that of the SPP, that is, spin-momentum locking. In order to suppress the background, the values of the photocurrent for the right CPL are subtracted from those for the left CPL. Comparison between the two arabinose enantiomers reveals a preferential signal response of one enantiomer to left CPL and the other enantiomer to right CPL. In sum, this work reports on the first experimental evidence of the feasibility of chiral molecule detection via optical rectification in a metal meta-grating. This nanoscale interfaced electrical detection technology is advantageous over other detection methods due to its size, cost, ease of use, and integration ability with read-out electronic circuits for data processing and interpretation.

Keywords: Chirality, detection, molecule, spin

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Authors: Leila Noori, Rosario Barone, Francesca Rappa, Antonella Marino Gammazza, Alessandra Maria Vitale, Giuseppe Donato Mangano, Giusy Sentiero, Filippo Macaluso, Kathryn H. Myburgh, Francesco Cappello, Federica Scalia

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The neuromuscular system controls, directs, and allows movement of the body through the action of neural circuits, which include motor neurons, sensory neurons, and skeletal muscle fibers. Protein homeostasis of the involved cytotypes appears crucial to maintain the correct and prolonged functions of the neuromuscular system, and both neuronal cells and skeletal muscle fibers express significant quantities of protein chaperones, the molecular machinery responsible to maintain the protein turnover. Genetic mutations or defective post-translational modifications of molecular chaperones (i.e., genetic or acquired chaperonopathies) may lead to neuromuscular disorders called as neurochaperonopathies. The limited knowledge of the effects of the defective chaperones on skeletal muscle fibers and neurons impedes the progression of therapeutic approaches. A distinct genetic variation of CCT5 gene encoding for the subunit 5 of the chaperonin CCT (Chaperonin Containing TCP1; also known as TRiC, TCP1 Ring Complex) was recently described associated with severe distal motor neuropathy by our team. In this study, we investigated the histopathological abnormalities of the skeletal muscle biopsy of the pediatric patient affected by the mutation Leu224Val in the CCT5 subunit. We provide molecular and structural features of the diseased skeletal muscle tissue that we believe may be useful to identify undiagnosed cases of this rare genetic disorder. We investigated the histological abnormalities of the affected tissue via hematoxylin and eosin staining. Then we used immunofluorescence and qPCR techniques to explore the expression and distribution of CCT5 in diseased and healthy skeletal muscle tissue. Immunofluorescence and immunohistochemistry assays were performed to study the sarcomeric and structural proteins of skeletal muscle, including actin, myosin, tubulin, troponin-T, telethonin, and titin. We performed Western blot to examine the protein expression of CCT5 and some heat shock proteins, Hsp90, Hsp60, Hsp27, and α-B crystallin, along with the main client proteins of the CCT5, actin, and tubulin. Our findings revealed muscular atrophy, abnormal morphology, and different sizes of muscle fibers in affected tissue. The swollen nuclei and wide interfiber spaces were seen. Expression of CCT5 had been decreased and showed a different distribution pattern in the affected tissue. Altered expression, distribution, and bandage pattern were detected by confocal microscopy for the interested muscular proteins in tissue from the patient compared to the healthy control. Protein levels of the studied Hsps normally located at the Z-disk were reduced. Western blot results showed increased levels of the actin and tubulin proteins in the diseased skeletal muscle biopsy compared to healthy tissue. Chaperones must be expressed at high levels in skeletal muscle to counteract various stressors such as mechanical, oxidative, and thermal crises; therefore, it seems relevant that defects of molecular chaperones may result in damaged skeletal muscle fibers. So far, several chaperones or cochaperones involved in neuromuscular disorders have been defined. Our study shows that alteration of the CCT5 subunit is associated with the damaged structure of skeletal muscle fibers and alterations of chaperone system components and paves the way to explore possible alternative substrates of chaperonin CCT. However, further studies are underway to investigate the CCT mechanisms of action to design applicable therapeutic strategies.

Keywords: molecular chaperones, neurochaperonopathy, neuromuscular system, protein homeostasis

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Authors: Dimitra C. Banti, Gesthimani Liona, Petros Samaras, Manasis Mitrakas

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Municipal and industrial wastewaters are often treated biologically, by the activated sludge process (ASP). The ASP not only requires large aeration and sedimentation tanks, but also generates large quantities of excess sludge. An alternative technology is the membrane bioreactor (MBR), which replaces two stages of the conventional ASP—clarification and settlement—with a single, integrated biotreatment and clarification step. The advantages offered by the MBR over conventional treatment include reduced footprint and sludge production through maintaining a high biomass concentration in the bioreactor. Notwithstanding these advantages, the widespread application of the MBR process is constrained by membrane fouling. Fouling leads to permeate flux decline, making more frequent membrane cleaning and replacement necessary and resulting to increased operating costs. In general, membrane fouling results from the interaction between the membrane material and the components in the activated sludge liquor. The latter includes substrate components, cells, cell debris and microbial metabolites, such as Extracellular Polymeric Substances (EPS) and Sludge Microbial Products (SMPs). The challenge for effective MBR operation is to minimize the rate of Transmembrane Pressure (TMP) increase. This can be achieved by several ways, one of which is the addition of specific additives, that enhance the coagulation and flocculation of compounds, which are responsible for fouling, hence reducing biofilm formation on the membrane surface and limiting the fouling rate. In this project the effectiveness of a non-commercial composite coagulant was studied as an agent for fouling control in a lab scale MBR system consisting in two aerated tanks. A flat sheet membrane module with 0.40 um pore size was submerged into the second tank. The system was fed by50 L/d of municipal wastewater collected from the effluent of the primary sedimentation basin. The TMP increase rate, which is directly related to fouling growth, was monitored by a PLC system. EPS, MLSS and MLVSS measurements were performed in samples of mixed liquor; in addition, influent and effluent samples were collected for the determination of physicochemical characteristics (COD, BOD5, NO3-N, NH4-N, Total N and PO4-P). The coagulant was added in concentrations 2, 5 and 10mg/L during a period of 2 weeks and the results were compared with the control system (without coagulant addition). EPS fractions were extracted by a three stages physical-thermal treatment allowing the identification of Soluble EPS (SEPS) or SMP, Loosely Bound EPS (LBEPS) and Tightly Bound EPS (TBEPS). Proteins and carbohydrates concentrations were measured in EPS fractions by the modified Lowry method and Dubois method, respectively. Addition of 2 mg/L coagulant concentration did not affect SEPS proteins in comparison with control process and their values varied between 32 to 38mg/g VSS. However a coagulant dosage of 5mg/L resulted in a slight increase of SEPS proteins at 35-40 mg/g VSS while 10mg/L coagulant further increased SEPS to 44-48mg/g VSS. Similar results were obtained for SEPS carbohydrates. Carbohydrates values without coagulant addition were similar to the corresponding values measured for 2mg/L coagulant; the addition of mg/L coagulant resulted to a slight increase of carbohydrates SEPS to 6-7mg/g VSS while a dose of 10 mg/L further increased carbohydrates content to 9-10mg/g VSS. Total LBEPS and TBEPS, consisted of proteins and carbohydrates of LBEPS and TBEPS respectively, presented similar variations by the addition of the coagulant. Total LBEPS at 2mg/L dose were almost equal to 17mg/g VSS, and their values increased to 22 and 29 mg/g VSS during the addition of 5 mg/L and 10 mg/L of coagulant respectively. Total TBEPS were almost 37 mg/g VSS at a coagulant dose of 2 mg/L and increased to 42 and 51 mg/g VSS at 5 mg/L and 10 mg/L doses, respectively. Therefore, it can be concluded that coagulant addition could potentially affect microorganisms activities, excreting EPS in greater amounts. Nevertheless, EPS increase, mainly SEPS increase, resulted to a higher membrane fouling rate, as justified by the corresponding TMP increase rate. However, the addition of the coagulant, although affected the EPS content in the reactor mixed liquor, did not change the filtration process: an effluent of high quality was produced, with COD values as low as 20-30 mg/L.

Keywords: extracellular polymeric substances, MBR, membrane fouling, EPS

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Authors: Sarah Lister, Pauline Palmer

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Research findings presented within this paper form part of a larger scale collaboration between academics at Manchester Metropolitan University and a technology company. The overarching aims of this project focus on developing a series of game-based resources to promote the teaching of aspects of mathematics through a second language (L2) in primary schools. This study explores the potential of game-based learning (GBL) as a dynamic way to engage and motivate learners, making learning fun and purposeful. The research examines the capacity of GBL resources to provide a meaningful and purposeful context for CLIL. GBL is a powerful learning environment and acts as an effective vehicle to promote the learning of mathematics through an L2. The fun element of GBL can minimise stress and anxiety associated with mathematics and L2 learning that can create barriers. GBL provides one of the few safe domains where it is acceptable for learners to fail. Games can provide a life-enhancing experience for learners, revolutionizing the routinized ways of learning through fusing learning and play. This study argues that playing games requires learners to think creatively to solve mathematical problems, using the L2 in order to progress, which can be associated with the development of higher-order thinking skills and independent learning. GBL requires learners to engage appropriate cognitive processes with increased speed of processing, sensitivity to environmental inputs, or flexibility in allocating cognitive and perceptual resources. At surface level, GBL resources provide opportunities for learners to learn to do things. Games that fuse subject content and appropriate learning objectives have the potential to make learning academic subjects more learner-centered, promote learner autonomy, easier, more enjoyable, more stimulating and engaging and therefore, more effective. Data includes observations of the children playing the games and follow up group interviews. Given that learning as a cognitive event cannot be directly observed or measured. A Cognitive Discourse Functions (CDF) construct was used to frame the research, to map the development of learners’ conceptual understanding in an L2 context and as a framework to observe the discursive interactions that occur learner to learner and between learner and teacher. Cognitively, the children were required to engage with mathematical content, concepts and language to make decisions quickly, to engage with the gameplay to reason, solve and overcome problems and learn through experimentation. The visual elements of the games supported the learning of new concepts. Children recognised the value of the games to consolidate their mathematical thinking and develop their understanding of new ideas. The games afforded them time to think and reflect. The teachers affirmed that the games provided meaningful opportunities for the learners to practise the language. The findings of this research support the view that using the game-based resources supported children’s grasp of mathematical ideas and their confidence and ability to use the L2. Engaging with the content and language through the games led to deeper learning.

Keywords: CLIL, gaming, language, mathematics

Procedia PDF Downloads 110

Authors: Luisa Kynast

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It is obvious that buildings and infrastructure are highly impacted by climate change (CC). Both, design and material of buildings need to be resilient to weather events in order to shelter humans, animals, or goods. As well as buildings and infrastructure are exposed to weather events, the construction process itself is generally carried out outdoors without being protected from extreme temperatures, heavy rain, or storms. The production process is restricted by technical limitations for processing materials with machines and physical limitations due to human beings (“outdoor-worker”). In future due to CC, average weather patterns are expected to change as well as extreme weather events are expected to occur more frequently and more intense and therefore have a greater impact on production processes and on the construction businesses itself. This research aims to examine this impact by analyzing an association between responses to CC and financial performance of businesses within the construction industry. After having embedded the above depicted field of research into the resource dependency theory, a literature review was conducted to expound the state of research concerning a contingent relation between climate change adaptation measures (CCAM) and corporate financial performance for construction businesses. The examined studies prove that this field is rarely investigated, especially for construction businesses. Therefore, reports of the Carbon Disclosure Project (CDP) were analyzed by applying content analysis using the software tool MAXQDA. 58 construction companies – located worldwide – could be examined. To proceed even more systematically a coding scheme analogous to findings in literature was adopted. Out of qualitative analysis, data was quantified and a regression analysis containing corporate financial data was conducted. The results gained stress adaptation measures as a response to CC as a crucial proxy to handle climate change impacts (CCI) by mitigating risks and exploiting opportunities. In CDP reports the majority of answers stated increasing costs/expenses as a result of implemented measures. A link to sales/revenue was rarely drawn. Though, CCAM were connected to increasing sales/revenues. Nevertheless, this presumption is supported by the results of the regression analysis where a positive effect of implemented CCAM on construction businesses´ financial performance in the short-run was ascertained. These findings do refer to appropriate responses in terms of the implemented number of CCAM. Anyhow, still businesses show a reluctant attitude for implementing CCAM, which was confirmed by findings in literature as well as by findings in CDP reports. Businesses mainly associate CCAM with costs and expenses rather than with an effect on their corporate financial performance. Mostly companies underrate the effect of CCI and overrate the costs and expenditures for the implementation of CCAM and completely neglect the pay-off. Therefore, this research shall create a basis for bringing CC to the (financial) attention of corporate decision-makers, especially within the construction industry.

Keywords: climate change adaptation measures, construction businesses, financial implication, resource dependency theory

Procedia PDF Downloads 116

Authors: David X. Dong, Qingming Zhang, Meng Lu

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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

Procedia PDF Downloads 46

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

Procedia PDF Downloads 148

Authors: Hamda M. Al-Ali

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The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 98

Authors: Grant Bifolchi

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As global environmental problems continue to have highly adverse effects, finding long-term, sustainable solutions to combat ecological distress are of growing paramount concern. Ghost Gear—also known as abandoned, lost or otherwise discarded fishing gear (ALDFG) and derelict fishing gear (DFG)—represents one of the greatest threats to the world’s oceans, posing a significant hazard to human health, livelihoods, and global food security. In fact, according to the UN Food and Agriculture Organization (FAO), abandoned, lost and discarded fishing gear represents approximately 10% of marine debris by volume. Around the world, many governments, governmental and non-profit organizations are doing their best to manage the reporting and retrieval of nets, lines, ropes, traps, floats and more from their respective bodies of water. However, these organizations’ ability to effectively manage files and documents about the environmental problem further complicates matters. In Ghost Gear monitoring and management, organizations face additional complexities. Whether it’s data ingest, industry regulations and standards, garnering actionable insights into the location, security, and management of data, or the application of enforcement due to disparate data—all of these factors are placing massive strains on organizations struggling to save the planet from the dangers of Ghost Gear. In this 90-minute educational session, globally recognized Ghost Gear technology expert Grant Bifolchi CET, BBA, Bcom, will provide real-world insight into how governments currently manage Ghost Gear and the technology that can accelerate success in combatting ALDFG and DFG. In this session, attendees will learn how to: • Identify specific technologies to solve the ingest and management of Ghost Gear data categories, including type, geo-location, size, ownership, regional assignment, collection and disposal. • Provide enhanced access to authorities, fisheries, independent fishing vessels, individuals, etc., while securely controlling confidential and privileged data to globally recognized standards. • Create and maintain processing accuracy to effectively track ALDFG/DFG reporting progress—including acknowledging receipt of the report and sharing it with all pertinent stakeholders to ensure approvals are secured. • Enable and utilize Business Intelligence (BI) and Analytics to store and analyze data to optimize organizational performance, maintain anytime-visibility of report status, user accountability, scheduling, management, and foster governmental transparency. • Maintain Compliance Reporting through highly defined, detailed and automated reports—enabling all stakeholders to share critical insights with internal colleagues, regulatory agencies, and national and international partners.

Keywords: ghost gear, ALDFG, DFG, abandoned, lost or otherwise discarded fishing gear, data, technology

Procedia PDF Downloads 71

Authors: Jiri Cecrdle

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This paper describes the concept of the W-WING whirl flutter aeroelastic demonstrator. Whirl flutter is the specific case of flutter that accounts for the additional dynamic and aerodynamic influences of the engine rotating parts. The instability is driven by motion-induced unsteady aerodynamic propeller forces and moments acting in the propeller plane. Whirl flutter instability is a serious problem that may cause the unstable vibration of a propeller mounting, leading to the failure of an engine installation or an entire wing. The complicated physical principle of whirl flutter required the experimental validation of the analytically gained results. W-WING aeroelastic demonstrator has been designed and developed at Czech Aerospace Research Centre (VZLU) Prague, Czechia. The demonstrator represents the wing and engine of the twin turboprop commuter aircraft. Contrary to the most of past demonstrators, it includes a powered motor and thrusting propeller. It allows the changes of the main structural parameters influencing the whirl flutter stability characteristics. Propeller blades are adjustable at standstill. The demonstrator is instrumented by strain gauges, accelerometers, revolution-counting impulse sensor, sensor of airflow velocity, and the thrust measurement unit. Measurement is supported by the in house program providing the data storage and real-time depiction in the time domain as well as pre-processing into the form of the power spectral densities. The engine is linked with a servo-drive unit, which enables maintaining of the propeller revolutions (constant or controlled rate ramp) and monitoring of immediate revolutions and power. Furthermore, the program manages the aerodynamic excitation of the demonstrator by the aileron flapping (constant, sweep, impulse). Finally, it provides the safety guard to prevent any structural failure of the demonstrator hardware. In addition, LMS TestLab system is used for the measurement of the structure response and for the data assessment by means of the FFT- and OMA-based methods. The demonstrator is intended for the experimental investigations in the VZLU 3m-diameter low-speed wind tunnel. The measurement variant of the model is defined by the structural parameters: pitch and yaw attachment stiffness, pitch and yaw hinge stations, balance weight station, propeller type (duralumin or steel blades), and finally, angle of attack of the propeller blade 75% section (). The excitation is provided either by the airflow turbulence or by means of the aerodynamic excitation by the aileron flapping using a frequency harmonic sweep. The experimental results are planned to be utilized for validation of analytical methods and software tools in the frame of development of the new complex multi-blade twin-rotor propulsion system for the new generation regional aircraft. Experimental campaigns will include measurements of aerodynamic derivatives and measurements of stability boundaries for various configurations of the demonstrator.

Keywords: aeroelasticity, flutter, whirl flutter, W WING demonstrator

Procedia PDF Downloads 55

Authors: Mabel Y. C. Yau, Roy C. F. Lai, Hugo Y. H. Or

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This study is a pilot surveillance of hygiene compliance and food microbial safety of both licensed and mobile vendors selling Chinese ready–to-eat snack foods in Hong Kong. The study reflects similar situations in running mobile food vending business on trucks. Hong Kong is about to launch the Food Truck Pilot Scheme by the end of 2016 or early 2017. Technically, selling food on the vehicle is no different from hawking food on the street or vending food on the street. Each type of business bears similar food safety issues and cast the same impact on public health. Present findings demonstrate exemplarily situations that also apply to food trucks. 9 types of Cantonese style snacks of 32 samples in total were selected for microbial screening. A total of 16 vending sites including supermarkets, street markets, and snack stores were visited. The study finally focused on a traditional snack, the steamed rice cake with red beans called Put Chai Ko (PCK). PCK is a type of classical Cantonese pastry sold on push carts on the street. It used to be sold at room temperature and served with bamboo sticks in the old days. Some shops would have them sold steam fresh. Microbial examinations on aerobic counts, yeast, and mould, coliform, salmonella as well as Staphylococcus aureus detections were carried out. Salmonella was not detected in all samples. Since PCK does not contain ingredients of beef, poultry, eggs or dairy products, the risk of the presence of Salmonella in PCK was relatively lower although other source of contamination might be possible. Coagulase positive Staphylococcus aureus was found in 6 of the 14 samples sold at room temperature. Among these 6 samples, 3 were PCK. One of the samples was in an unacceptable range of total colony forming units higher than 105. The rest were only satisfactory. Observational evaluations were made with checklists on personal hygiene, premises hygiene, food safety control, food storage, cleaning and sanitization as well as waste disposals. The maximum score was 25 if total compliance were obtained. The highest score among vendors was 20. Three stores were below average, and two of these stores were selling PCK. Most of the non-compliances were on food processing facilities, sanitization conditions and waste disposal. In conclusion, although no food poisoning outbreaks happened during the time of the investigation, the risk of food hazard existed in these stores, especially among street vendors. Attention is needed in the traditional practice of food selling, and that food handlers might not have sufficient knowledge to properly handle food products. Variations in food qualities existed among supply chains or franchise eateries or shops. It was commonly observed that packaging and storage conditions are not properly enforced in the retails. The same situation could be reflected across the food business. It did indicate need of food safety training in the industry and loopholes in quality control among business.

Keywords: cantonese snacks, food safety, microbial, hygiene, street food

Procedia PDF Downloads 273

Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

Procedia PDF Downloads 104

Authors: Desmond Appiah, Fan Zhang, Shouqi Yuan, Wei Xueyuan, Stephen N. Asomani

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The side channel pump has distinctive hydraulic performance characteristics over other vane pumps because of its generation of high pressure heads in only one impeller revolution. Hence, there is soaring utilization and application in the fields of petrochemical, food processing fields, automotive and aerospace fuel pumping where high heads are required at low flows. The side channel pump is characterized by unstable flow because after fluid flows into the impeller passage, it moves into the side channel and comes back to the impeller again and then moves to the next circulation. Consequently, the flow leaves the side channel pump following a helical path. However, the pressure fluctuation exhibited in the flow greatly contributes to the unwanted noise and vibration which is associated with the flow. In this paper, a side channel pump prototype was examined thoroughly through numerical calculations based on SST k-ω turbulence model to ascertain the pressure fluctuation behavior. The pressure fluctuation intensity of the 3D unstable flow dynamics were carefully investigated under different working conditions 0.8QBEP, 1.0 QBEP and 1.2QBEP. The results showed that the pressure fluctuation distribution around the pressure side of the blade is greater than the suction side at the impeller and side channel interface (z=0) for all three operating conditions. Part-load condition 0.8QBEP recorded the highest pressure fluctuation distribution because of the high circulation velocity thus causing an intense exchanged flow between the impeller and side channel. Time and frequency domains spectra of the pressure fluctuation patterns in the impeller and the side channel were also analyzed under the best efficiency point value, QBEP using the solution from the numerical calculations. It was observed from the time-domain analysis that the pressure fluctuation characteristics in the impeller flow passage increased steadily until the flow reached the interrupter which separates low-pressure at the inflow from high pressure at the outflow. The pressure fluctuation amplitudes in the frequency domain spectrum at the different monitoring points depicted a gentle decreasing trend of the pressure amplitudes which was common among the operating conditions. The frequency domain also revealed that the main excitation frequencies occurred at 600Hz, 1200Hz, and 1800Hz and continued in the integers of the rotating shaft frequency. Also, the mass flow exchange plots indicated that the side channel pump is characterized with many vortex flows. Operating conditions 0.8QBEP, 1.0 QBEP depicted less and similar vortex flow while 1.2Q recorded many vortex flows around the inflow, middle and outflow regions. The results of the numerical calculations were finally verified experimentally. The performance characteristics curves from the simulated results showed that 0.8QBEP working condition recorded a head increase of 43.03% and efficiency decrease of 6.73% compared to 1.0QBEP. It can be concluded that for industrial applications where the high heads are mostly required, the side channel pump can be designed to operate at part-load conditions. This paper can serve as a source of information in order to optimize a reliable performance and widen the applications of the side channel pumps.

Keywords: exchanged flow, pressure fluctuation, numerical simulation, side channel pump

Procedia PDF Downloads 101

Authors: Liang Zhao, Chongquan Zhong

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Introduction: According to statistics, people spend 80% to 90% of time indoor, so indoor air quality, either at home or in the office, greatly impacts the quality of life, health and work efficiency. Therefore, indoor air quality is very important to human activities. With the acceleration of urbanization, people are spending more time in indoor activity. The time in indoor environment, the living space, and the frequency interior decoration are all increasingly increased. However, housing decoration materials contain formaldehyde and other harmful substances, causing environmental and air quality problems, which have brought serious damage to countless families and attracted growing attention. According to World Health Organization statistics, the indoor environments in more than 30% of buildings in China are polluted by poisonous and harmful gases. Indoor pollution has caused various health problems, and these widespread public health problems can lead to respiratory diseases. Long-term inhalation of low-concentration formaldehyde would cause persistent headache, insomnia, weakness, palpitation, weight loss and vomiting, which are serious impacts on human health and safety. On the other hand, as for offices, some surveys show that good indoor air quality helps to enthuse the staff and improve the work efficiency by 2%-16%. Therefore, people need to further understand the living and working environments. There is a need for easy-to-use indoor environment monitoring instruments, with which users only have to power up and monitor the environmental parameters. The corresponding real-time data can be displayed on the screen for analysis. Environment monitoring should have the sensitive signal alarm function and send alarm when harmful gases such as formaldehyde, CO, SO2, are excessive to human body. System design: According to the monitoring requirements of various gases, temperature and humidity, we designed a portable, light, real-time and accurate monitor for various environmental parameters, including temperature, humidity, formaldehyde, methane, and CO. This monitor will generate an alarm signal when a target is beyond the standard. It can conveniently measure a variety of harmful gases and provide the alarm function. It also has the advantages of small volume, convenience to carry and use. It has a real-time display function, outputting the parameters on the LCD screen, and a real-time alarm function. Conclusions: This study is focused on the research and development of a portable parameter monitoring instrument for indoor environment. On the platform of an STM32 development board, the monitored data are collected through an external sensor. The STM32 platform is for data acquisition and processing procedures, and successfully monitors the real-time temperature, humidity, formaldehyde, CO, methane and other environmental parameters. Real-time data are displayed on the LCD screen. The system is stable and can be used in different indoor places such as family, hospital, and office. Meanwhile, the system adopts the idea of modular design and is superior in transplanting. The scheme is slightly modified and can be used similarly as the function of a monitoring system. This monitor has very high research and application values.

Keywords: indoor air quality, gas concentration detection, embedded system, sensor

Procedia PDF Downloads 209

Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 77

Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: Hasti Ebrahimi

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This study sheds light on the challenges and difficulties caused by the Iranian clerical system’s intervention in the country’s school education during the COVID-19 pandemic, when schools remained closed for almost two years. The pandemic brought Iranian elementary school education to a standstill for almost 6 months before the country developed a nationwide learning platform – a customized television network. While the initiative seemed to have been welcomed by the majority of Iranian parents, it resented some of the more traditional strata of the society, including the influential Friday Prayer Leaders who found the televised version of the elementary education ‘less spiritual’ and ‘more ‘material’ or science-based. That prompted the Iranian Channel of Education, the specialized television network that had been chosen to serve as a nationally televised school during the pandemic, to try to redefine much of its online elementary school educational content within the religious ideology of the Islamic Republic of Iran. As a result, young clergies appeared on the television screen as preachers of Islamic morality, religious themes and even sociology, history, and arts. The present research delves into the consequences of such an intervention, how it might have impacted the infrastructure of Iranian elementary education and whether or not the new ideology-infused curricula would withstand the opposition of students and mainstream teachers. The main methodology used in this study is Critical Discourse Analysis with a cognitive approach. It systematically finds and analyzes the alternative ideological structures of discourse in the Iranian Channel of Education from September 2021 to July 2022, when the clergy ‘teachers’ replaced ‘regular’ history and arts teachers on the television screen for the first time. It has aimed to assess how the various uses of the alternative ideological discourse in elementary school content have influenced the processes of learning: the acquisition of knowledge, beliefs, opinions, attitudes, abilities, and other cognitive and emotional changes, which are the goals of institutional education. This study has been an effort aimed at understanding and perhaps clarifying the relationships between the traditional textual structures and processing on the one hand and socio-cultural contexts created by the clergy teachers on the other. This analysis shows how the clerical portion of elementary education on the Channel of Education that seemed to have dominated the entire televised teaching and learning process faded away as the pandemic was contained and mainstream classes were restored. It nevertheless reflects the deep ideological rifts between the clerical approach to school education and the mainstream teaching process in Iranian schools. The semantic macrostructures of social content in the current Iranian elementary school education, this study suggests, have remained intact despite the temporary ideological intervention of the ruling clerical elite in their formulation and presentation. Finally, using thematic and schematic frameworks, the essay suggests that the ‘clerical’ social content taught on the Channel of Education during the pandemic cannot have been accepted cognitively by the channel’s target audience, including students and mainstream teachers.

Keywords: televised elementary school learning, Covid 19, critical discourse analysis, Iranian clerical ideology

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Authors: Elodie Niemiec, Philippe Champagne, Jean-Francois Blach, Philippe Moreau, Anthony Thuault, Arnaud Tricoteaux

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Hygiene of equipment in contact with users is an important issue in the railroad industry. The numerous cleanings to eliminate bacteria and dirt cost a lot. Besides, mechanical solicitations on contact parts are observed daily. It should be interesting to elaborate on a self-cleaning and antibacterial coating with sufficient adhesion and good resistance against mechanical and chemical solicitations. Thus, a Hauts-de-France and Maubeuge Val-de-Sambre conurbation authority co-financed Ph.D. thesis has been set up since October 2017 based on anterior studies carried by the Laboratory of Ceramic Materials and Processing. To accomplish this task, a soft chemical route has been implemented to bring a lotus effect on metallic substrates. It involves nanometric liquid zinc oxide synthesis under 100°C. The originality here consists in a variation of surface texturing by modification of the synthesis time of the species in solution. This helps to adjust wettability. Nanostructured zinc oxide has been chosen because of the inherent photocatalytic effect, which can activate organic substance degradation. Two methods of heating have been compared: conventional and microwave assistance. Tested subtracts are made of stainless steel to conform to transport uses. Substrate preparation was the first step of this protocol: a meticulous cleaning of the samples is applied. The main goal of the elaboration protocol is to fix enough zinc-based seeds to make them grow during the next step as desired (nanorod shaped). To improve this adhesion, a silica gel has been formulated and optimized to ensure chemical bonding between substrate and zinc seeds. The last step consists of deposing a wide carbonated organosilane to improve the superhydrophobic property of the coating. The quasi-proportionality between the reaction time and the nanorod length will be demonstrated. Water Contact (superior to 150°) and Roll-off Angle at different steps of the process will be presented. The antibacterial effect has been proved with Escherichia Coli, Staphylococcus Aureus, and Bacillus Subtilis. The mortality rate is found to be four times superior to a non-treated substrate. Photocatalytic experiences were carried out from different dyed solutions in contact with treated samples under UV irradiation. Spectroscopic measurements allow to determinate times of degradation according to the zinc quantity available on the surface. The final coating obtained is, therefore, not a monolayer but rather a set of amorphous/crystalline/amorphous layers that have been characterized by spectroscopic ellipsometry. We will show that the thickness of the nanostructured oxide layer depends essentially on the synthesis time set in the hydrothermal growth step. A green, easy-to-process and control coating with self-cleaning and antibacterial properties has been synthesized with a satisfying surface structuration.

Keywords: antibacterial, biomimetism, soft-chemistry, zinc oxide

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Authors: Andreas Latz, Daniela Heinz, Fatima Hashemi, Melek Baygül

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Introduction: Feline leukemia virus (FeLV), feline immunodeficiency virus (FIV), and feline coronavirus (FCoV) are serious infectious diseases affecting cats worldwide. Transmission of these viruses occurs primarily through close contact with infected cats (via saliva, nasal secretions, faeces, etc.). FeLV, FIV, and FCoV infections can occur in combination and are expressed in similar clinical symptoms. Diagnosis can therefore be challenging: Symptoms are variable and often non-specific. Sick cats show very similar clinical symptoms: apathy, anorexia, fever, immunodeficiency syndrome, anemia, etc. Sample volume for small companion animals for diagnostic purposes can be challenging to collect. In addition, multiplex diagnosis of diseases can contribute to an easier, cheaper, and faster workflow in the lab as well as to the better differential diagnosis of diseases. For this reason, we wanted to develop a new diagnostic tool that utilizes less sample volume, reagents, and consumables than multiplesingleplex ELISA assays Methods: The Multiplier from Dynextechonogies (USA) has been used as platform to develop a Multiplex diagnostic tool for the detection of antibodies against FIV and FCoV/FIP and antigens for FeLV. Multiplex diagnostics. The Dynex®Multiplier®is a fully automated chemiluminescence immunoassay analyzer that significantly simplifies laboratory workflow. The Multiplier®ease-of-use reduces pre-analytical steps by combining the power of efficiently multiplexing multiple assays with the simplicity of automated microplate processing. Plastic beads have been coated with antigens for FIV and FCoV/FIP, as well as antibodies for FeLV. Feline blood samples are incubated with the beads. Read out of results is performed via chemiluminescence Results: Bead coating was optimized for each individual antigen or capture antibody and then combined in the multiplex diagnostic tool. HRP: Antibody conjugates for FIV and FCoV antibodies, as well as detection antibodies for FeLV antigen, have been adjusted and mixed. 3 individual prototyple batches of the assay have been produced. We analyzed for each disease 50 well defined positive and negative samples. Results show an excellent diagnostic performance of the simultaneous detection of antibodies or antigens against these feline diseases in a fully automated system. A 100% concordance with singleplex methods like ELISA or IFA can be observed. Intra- and Inter-Assays showed a high precision of the test with CV values below 10% for each individual bead. Accelerated stability testing indicate a shelf life of at least 1 year. Conclusion: The new tool can be used for multiplex diagnostics of the most important feline infectious diseases. Only a very small sample volume is required. Fully automation results in a very convenient and fast method for diagnosing animal diseases.With its large specimen capacity to process over 576 samples per 8-hours shift and provide up to 3,456 results, very high laboratory productivity and reagent savings can be achieved.

Keywords: Multiplex, FIV, FeLV, FCoV, FIP

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