Search results for: non-destructive testing

Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

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Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

Procedia PDF Downloads 132

Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

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Contemporary cities are facing serious congestion and parking problems. In urban transport policy the introduction of the park and ride system (P&R) is an increasingly popular way of limiting vehicular traffic. The determining of P&R facilities location is a key aspect of the system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. The research outsourced to specialists are expensive and time consuming. The most focus is on the examination of a few selected places. The practice has shown that the choice of the location of these sites in a intuitive way without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. Methods of location as a research topic are also widely taken in the scientific literature. Built mathematical models often do not bring the problem comprehensively, e.g. assuming that the city is linear, developed along one important communications corridor. The paper presents a new method where the expert knowledge is applied to fuzzy inference model. With such a built system even a less experienced person could benefit from it, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed location can also be verified in a short time. The proposed method is intended for testing of car parks location in a city. The paper will show selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analysis of existing objects will also be shown in the paper and they will be confronted with the opinions of the system users, with particular emphasis on unpopular locations. The research are executed using the fuzzy inference model which was built and described in more detail in the earlier paper of the authors. The results of analyzes are compared to documents of P&R facilities location outsourced by the city and opinions of existing facilities users expressed on social networking sites. The research of existing facilities were conducted by means of the fuzzy model. The results are consistent with actual users feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. The performed studies show that the method has been confirmed. The method can be applied in urban planning of the P&R facilities location in relation to the accompanying functions. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: fuzzy logic inference, park and ride system, P&R facilities, P&R location

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Authors: Abayomi O. Adetuyi, Jamiu M. Jabar, Samuel O. Afolabi

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Vegetable fibres are classes of fibres of low density, biodegradable and non-abrasive that are largely abundant fibre materials with specific properties and mostly found/ obtained in plants on earth surface. They are classified into three categories, depending on the part of the plant from which they are gotten from namely: fruit, Blast and Leaf fibre. Ever since four/five millennium B.C, attention has been focussing on the commonest and highly utilized cotton fibre obtained from the fruit of cotton plants (Gossypium spp), for the production of cotton fabric used in every home today. The present study, therefore, focused on the ability of three underutilized vegetable (fruit) fibres namely: coir fiber (Eleas coniferus), palm kernel fiber and empty fruit bunch fiber (Elias guinensis) through chemical modifications for better composite value addition performance to polyurethane form and dye adsorption. These fibres were sourced from their parents’ plants, identified and cleansed with 2% hot detergent solution 1:100, rinsed in distilled water and oven-dried to constant weight, before been chemically modified through alkali bleaching, mercerization and acetylation. The alkali bleaching involves treating 0.5g of each fiber material with 100 mL of 2% H2O2 in 25 % NaOH solution with refluxing for 2 h. While that of mercerization and acetylation involves the use of 5% sodium hydroxide NaOH solution for 2 h and 10% acetic acid- acetic anhydride 1:1 (v/v) (CH3COOH) / (CH3CO)2O solution with conc. H2SO4 as catalyst for 1 h, respectively on the fibres. All were subsequently washed thoroughly with distilled water and oven dried at 105 0C for 1 h. These modified fibres were incorporated as composite into polyurethane form and used in dye adsorption study of indigo. The first two treatments led to fiber weight reduction, while the acidified acetic anhydride treatment gave the fibers weight increment. All the treated fibers were found to be of less hydrophilic nature, better mechanical properties, higher thermal stabilities as well as better adsorption surfaces/capacities than the untreated ones. These were confirmed by gravimetric analysis, Instron Universal Testing Machine, Thermogravimetric Analyser and the Scanning Electron Microscope (SEM) respectively. The fiber morphology of the modified fibers showed smoother surfaces than unmodified fibres.The empty fruit bunch fibre and the coconut coir fibre are better than the palm kernel fibres as reinforcers for composites or as adsorbents for waste-water treatment. Acetylation and alkaline bleaching treatment improve the potentials of the fibres more than mercerization treatment. Conclusively, vegetable fibres, especially empty fruit bunch fibre and the coconut coir fibre, which are cheap, abundant and underutilized, can replace the very costly powdered activated carbon in wastewater treatment and as reinforcer in foam.

Keywords: chemical modification, industrial application, value addition, vegetable fibre

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Authors: Dustin Schöder

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The potential benefits of the utilization of highly automated and autonomous trucks in logistics operations are the subject of interest to the entire logistics industry. The benefits of the use of these new technologies were scientifically investigated and implemented in roadmaps. So far, reliable data and experiences from real life use cases are still limited. A German research consortium of both academics and industry developed a highly automated (SAE level 4) vehicle for yard operations at railports and container depots. After development and testing, a several month field test at the DUSS Terminal in Ulm-Dornstadt (Germany) and the nearby DB Intermodal Services Container Depot in Ulm-Dornstadt was conducted. The truck was piloted in a shuttle service between both sites. In a holistic automation approach, the vehicle was integrated into a digital communication platform so that the truck could move autonomously without a driver and his manual interactions with a wide variety of stakeholders. The main goal is to investigate the effects of highly automated trucks in the key processes of container loading, unloading and container relocation on holistic railport yard operation. The field test data were used to investigate changes in process efficiency of key processes of railport and container yard operations. Moreover, effects on the capacity utilization and potentials for smothering peak workloads were analyzed. The results state that process efficiency in the piloted use case was significantly higher. The reason for that could be found in the digitalized data exchange and automated dispatch. However, the field test has shown that the effect is greatly varying depending on the ratio of highly automated and manual trucks in the yard as well as on the congestion level in the loading area. Furthermore, the data confirmed that under the right conditions, the capacity utilization of highly automated trucks could be increased. In regard to the potential for smothering peak workloads, no significant findings could be made based on the limited requirements and regulations of railway operation in Germany. In addition, an empirical survey among railport managers, operational supervisors, innovation managers and strategists (n=15) within the logistics industry in Germany was conducted. The goal was to identify key characteristics of future railports and terminals as well as requirements that railports will have to meet in the future. Furthermore, the railport processes where automation and autonomization make the greatest impact, as well as hurdles and challenges in the introduction of new technologies, have been surveyed. Hence, further potential use cases of highly automated and autonomous applications could be identified, and expectations have been mapped. As a result, a highly detailed and practice-based roadmap towards a ‘terminal 4.0’ was developed.

Keywords: highly automated driving, autonomous driving, SAE level 4, railport operations, container depot, intermodal logistics, potentials of autonomization

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Authors: Bolatbek Rysbaiuly, Nazerke Rysbayeva, Aigerim Rysbayeva

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Relevance: Energy saving elevated to public policy in almost all developed countries. One of the areas for energy efficiency is improving and tightening design standards. In the tie with the state standards, make high demands for thermal protection of buildings. Constructive arrangement of layers should ensure normal operation in which the humidity of materials of construction should not exceed a certain level. Elevated levels of moisture in the walls can be attributed to a defective condition, as moisture significantly reduces the physical, mechanical and thermal properties of materials. Absence at the design stage of modeling the processes occurring in the construction and predict the behavior of structures during their work in the real world leads to an increase in heat loss and premature aging structures. Method: To solve this problem, widely used method of mathematical modeling of heat and mass transfer in materials. The mathematical modeling of heat and mass transfer are taken into the equation interconnected layer [1]. In winter, the thermal and hydraulic conductivity characteristics of the materials are nonlinear and depends on the temperature and moisture in the material. In this case, the experimental method of determining the coefficient of the freezing or thawing of the material becomes much more difficult. Therefore, in this paper we propose an approximate method for calculating the thermal conductivity and moisture permeability characteristics of freezing or thawing material. Questions. Following the development of methods for solving the inverse problem of mathematical modeling allows us to answer questions that are closely related to the rational design of fences: Where the zone of condensation in the body of the multi-layer fencing; How and where to apply insulation rationally his place; Any constructive activities necessary to provide for the removal of moisture from the structure; What should be the temperature and humidity conditions for the normal operation of the premises enclosing structure; What is the longevity of the structure in terms of its components frost materials. Tasks: The proposed mathematical model to solve the following problems: To assess the condition of the thermo-physical designed structures at different operating conditions and select appropriate material layers; Calculate the temperature field in a structurally complex multilayer structures; When measuring temperature and moisture in the characteristic points to determine the thermal characteristics of the materials constituting the surveyed construction; Laboratory testing to significantly reduce test time, and eliminates the climatic chamber and expensive instrumentation experiments and research; Allows you to simulate real-life situations that arise in multilayer enclosing structures associated with freezing, thawing, drying and cooling of any layer of the building material.

Keywords: energy saving, inverse problem, heat transfer, multilayer walling

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Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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Authors: Tiffany Riggleman, Andrea Schultheis, Kalyn Jannace, Jerika Taylor, Michelle Nordstrom, Paul F. Pasquina

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Introduction: Posttraumatic Stress (PTS) and Posttraumatic Stress Disorder (PTSD) remain significant problems for military and veteran communities. Symptoms of PTSD often include poor sleep, intrusive thoughts, difficulty concentrating, and trouble with emotional regulation. Unfortunately, despite its high prevalence, service members diagnosed with PTSD often do not seek help, usually because of the perceived stigma surrounding behavioral health care. To help address these challenges, non-pharmacological, therapeutic approaches are being developed to help improve care and enhance compliance. The Service Dog Training Program (SDTP), which involves teaching patients how to train puppies to become mobility service dogs, has been successfully implemented into PTS/PTSD care programs with anecdotal reports of improved outcomes. This study was designed to assess the biopsychosocial effects of SDTP from military beneficiaries with PTS symptoms. Methods: Individuals between the ages of 18 and 65 with PTS symptom were recruited to participate in this prospective study. Each subject completes 4 weeks of baseline testing, followed by 6 weeks of active service dog training (twice per week for one hour sessions) with a professional service dog trainer. Outcome measures included the Posttraumatic Stress Checklist for the DSM-5 (PCL-5), Generalized Anxiety Disorder questionnaire-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), social support/interaction, anthropometrics, blood/serum biomarkers, and qualitative interviews. Preliminary analysis of 17 participants examined mean scores on the GAD-7, PCL-5, and PHQ-9, pre- and post-SDTP, and changes were assessed using Wilcoxon Signed-Rank tests. Results: Post-SDTP, there was a statistically significant mean decrease in PCL-5 scores of 13.5 on an 80-point scale (p=0.03) and a significant mean decrease of 2.2 in PHQ-9 scores on a 27 point scale (p=0.04), suggestive of decreased PTSD and depression symptoms. While there was a decrease in mean GAD-7 scores post-SDTP, the difference was not significant (p=0.20). Recurring themes among results from the qualitative interviews include decreased pain, forgetting about stressors, improved sense of calm, increased confidence, improved communication, and establishing a connection with the service dog. Conclusion: Preliminary results of the first 17 participants in this study suggest that individuals who received SDTP had a statistically significant decrease in PTS symptom, as measured by the PCL-5 and PHQ-9. This ongoing study seeks to enroll a total of 156 military beneficiaries with PTS symptoms. Future analyses will include additional psychological outcomes, pain scores, blood/serum biomarkers, and other measures of the social aspects of PTSD, such as relationship satisfaction and sleep hygiene.

Keywords: post-concussive syndrome, posttraumatic stress, service dog, service dog training program, traumatic brain injury

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Authors: Lina Psarra, Manogj Sundaresan, Purjeet Sutar

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In response to the global imperative for sustainable solutions, this article proposes the development of a comprehensive circularity index applicable to a wide range of products across various industries. The absence of a consensus on using a universal metric to assess circularity performance presents a significant challenge in prioritizing and effectively managing sustainable initiatives. This circularity index serves as a quantitative measure to evaluate the adherence of products, processes, and systems to the principles of a circular economy. Unlike traditional distinct metrics such as recycling rates or material efficiency, this index considers the entire lifecycle of a product in one single metric, also incorporating additional factors such as reusability, scarcity of materials, reparability, and recyclability. Through a systematic approach and by reviewing existing metrics and past methodologies, this work aims to address this gap by formulating a circularity index that can be applied to diverse product portfolio and assist in comparing the circularity of products on a scale of 0%-100%. Project objectives include developing a formula, designing and implementing a pilot tool based on the developed Product Circularity Index (PCI), evaluating the effectiveness of the formula and tool using real product data, and assessing the feasibility of integration into various sustainability initiatives. The research methodology involves an iterative process of comprehensive research, analysis, and refinement where key steps include defining circularity parameters, collecting relevant product data, applying the developed formula, and testing the tool in a pilot phase to gather insights and make necessary adjustments. Major findings of the study indicate that the PCI provides a robust framework for evaluating product circularity across various dimensions. The Excel-based pilot tool demonstrated high accuracy and reliability in measuring circularity, and the database proved instrumental in supporting comprehensive assessments. The PCI facilitated the identification of key areas for improvement, enabling more informed decision-making towards circularity and benchmarking across different products, essentially assisting towards better resource management. In conclusion, the development of the Product Circularity Index represents a significant advancement in global sustainability efforts. By providing a standardized metric, the PCI empowers companies and stakeholders to systematically assess product circularity, track progress, identify improvement areas, and make informed decisions about resource management. This project contributes to the broader discourse on sustainable development by offering a practical approach to enhance circularity within industrial systems, thus paving the way towards a more resilient and sustainable future.

Keywords: circular economy, circular metrics, circularity assessment, circularity tool, sustainable product design, product circularity index

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Authors: Ali Kadir, O. Anwar Beg

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Thermal barrier coatings are among the most popular methods for providing corrosion protection in high temperature applications including aircraft engine systems, external spacecraft structures, rocket chambers etc. Many different materials are available for such coatings, of which ceramics generally perform the best. Motivated by these applications, the current investigation presents detailed finite element simulations of coating stress analysis for a 3- dimensional, 3-layered model of a test sample representing a typical gas turbine component scenario. Structural steel is selected for the main inner layer, Titanium (Ti) alloy for the middle layer and Silicon Carbide (SiC) for the outermost layer. The model dimensions are 20 mm (width), 10 mm (height) and three 1mm deep layers. ANSYS software is employed to conduct three types of analysis- static structural, thermal stress analysis and also computational fluid dynamic erosion/corrosion analysis (via ANSYS FLUENT). The specified geometry which corresponds to corrosion test samples exactly is discretized using a body-sizing meshing approach, comprising mainly of tetrahedron cells. Refinements were concentrated at the connection points between the layers to shift the focus towards the static effects dissipated between them. A detailed grid independence study is conducted to confirm the accuracy of the selected mesh densities. To recreate gas turbine scenarios; in the stress analysis simulations, static loading and thermal environment conditions of up to 1000 N and 1000 degrees Kelvin are imposed. The default solver was used to set the controls for the simulation with the fixed support being set as one side of the model while subjecting the opposite side to a tabular force of 500 and 1000 Newtons. Equivalent elastic strain, total deformation, equivalent stress and strain energy were computed for all cases. Each analysis was duplicated twice to remove one of the layers each time, to allow testing of the static and thermal effects with each of the coatings. ANSYS FLUENT simulation was conducted to study the effect of corrosion on the model under similar thermal conditions. The momentum and energy equations were solved and the viscous heating option was applied to represent improved thermal physics of heat transfer between the layers of the structures. A Discrete Phase Model (DPM) in ANSYS FLUENT was employed which allows for the injection of continuous uniform air particles onto the model, thereby enabling an option for calculating the corrosion factor caused by hot air injection (particles prescribed 5 m/s velocity and 1273.15 K). Extensive visualization of results is provided. The simulations reveal interesting features associated with coating response to realistic gas turbine loading conditions including significantly different stress concentrations with different coatings.

Keywords: thermal coating, corrosion, ANSYS FEA, CFD

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Authors: Barbara Urasinska-Wojcik, Neil Chilton, Peter Todd, Christopher Elsworthy, Gregory J. Gibbons

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The recent increase in the application of Additive Manufacturing (AM) of products has resulted in new demands on capability. The ability to integrate both form and function within printed objects is the next frontier in the 3D printing area. To move beyond prototyping into low volume production, we demonstrate a UK-designed and built AM hybrid system that combines polymer based structural deposition with digital deposition of electrically conductive elements. This hybrid manufacturing system is based on a multi-planar build approach to improve on many of the limitations associated with AM, such as poor surface finish, low geometric tolerance, and poor robustness. Specifically, the approach involves a multi-planar Material Extrusion (ME) process in which separated build stations with up to 5 axes of motion replace traditional horizontally-sliced layer modeling. The construction of multi-material architectures also involved using multiple print systems in order to combine both ME and digital deposition of conductive material. To demonstrate multi-material 3D printing, three thermoplastics, acrylonitrile butadiene styrene (ABS), polyamide 6,6/6 copolymers (CoPA) and polyamide 12 (PA) were used to print specimens, on top of which our high viscosity Ag-particulate ink was printed in a non-contact process, during which drop characteristics such as shape, velocity, and volume were assessed using a drop watching system. Spectroscopic analysis of these 3D printed materials in the IR region helped to determine the optimum in-situ curing system for implementation into the AM system to achieve improved adhesion and surface refinement. Thermal Analyses were performed to determine the printed materials glass transition temperature (Tg), stability and degradation behavior to find the optimum annealing conditions post printing. Electrical analysis of printed conductive tracks on polymer surfaces during mechanical testing (static tensile and 3-point bending and dynamic fatigue) was performed to assess the robustness of the electrical circuits. The tracks on CoPA, ABS, and PA exhibited low electrical resistance, and in case of PA resistance values of tracks remained unchanged across hundreds of repeated tensile cycles up to 0.5% strain amplitude. Our developed AM printer has the ability to fabricate fully functional objects in one build, including complex electronics. It enables product designers and manufacturers to produce functional saleable electronic products from a small format modular platform. It will make 3D printing better, faster and stronger.

Keywords: additive manufacturing, conductive tracks, hybrid 3D printer, integrated manufacture

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Authors: Sweta Agrawal, Sachin Chaugule, Gargi Rane, Shashank More, Madhavi Indap

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Angiogenesis and metastasis are two of the most important hallmarks of cancer. Hence, most of the cancer therapies nowadays are multi-targeted so as to reduce resistance and have better efficacy. As synthetic molecules arise with a burden of their toxicities and side-effects, more and more research is being focussed on exploiting the vast natural resources of drugs, in the form of plants and animals. Although, the idea of using marine organisms as a source of pharmaceuticals is not new, the pace at which marine drugs are being discovered, has definitely up surged! In the present study, we have assessed the anti-angiogenic and in vitro anti-metastatic activity of aqueous fraction from the extract of marine gastropod Euchelus asper. The soft body of Euchelus Asper was extracted with methanol and named EAME. Partition chromatography of EAME gave three fractions EAME I, II and III. Biochemical analysis revealed the presence of proteins in EAME III. Preliminary analysis had revealed the anti-angiogenic activity was exhibited by EAME III out of the three fractions. Hereafter, EAME III (concentration 25µg/ml-400µg/ml) was tested on chick chorioallantoic membrane (CAM) model for the detailed analysis of its potential anti-angiogenic effect. In vitro testing of the fraction (concentration 0.25µg/ml - 1µg/ml), involved cytotoxicity by SRB assay, cell cycle analysis by flow cytometry and anti-proliferative effect by scratch wound healing assay on A549 lung carcinoma cells. Apart from this, a portion of treated CAM as well as conditioned medium from treated A549 were subjected to gelatin zymography for assessment of matrix metalloproteinases MMP-2 and MMP-9 levels. Our results revealed that EAME III exhibited significant anti-angiogenic activity on CAM which was also supported by histological observations. During histological studies of CAM, it was found that EAME III caused reduction in angiogenesis by altering the extracellular matrix of the CAM membrane. In vitro analysis disclosed that EAME III exhibited moderate cytotoxic effect on A549 cells and its effect was not dose-dependent. The results of flow cytometry confirmed that EAME III caused cell cycle arrest in A549 cell line as almost all of the treated cells were found in G1 phase. Further, the migration and proliferation of A549 was significantly reduced by EAME III as observed from the scratch wound assay. Moreover, Gelatin zymography analysis revealed that EAME III caused suppression of MMP-2 in CAM membrane and reduced MMP-9 and MMP-2 expression in A549 cells. This verified that the anti-angiogenic and anti-metastatic effects of EAME III were correlated with the suppression of MMP-2 and -9. To conclude, EAME III shows dual anti-tumour action by reducing angiogenesis and exerting anti-metastatic effect on lung cancer cells, thus it has the potential to be used as an anti-cancer agent against lung carcinoma.

Keywords: angiogenesis, anti-cancer, marine drugs, matrix metalloproteinases

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Authors: Piyush Sharma, Laltu Chandra, P. S. Ghoshdastidar, Rajiv Shekhar

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Metals processing operations such as melting and heat treatment of metals are energy-intensive, requiring temperatures greater than 500oC. The desired temperature in these industrial furnaces is attained by circulating electrically-heated air. In most of these furnaces, electricity produced from captive coal-based thermal power plants is used. Solar thermal energy could be a viable heat source in these furnaces. A retrofitted solar convective furnace (SCF) concept, which uses solar thermal generated hot air, has been proposed. Critical to the success of a SCF is the design of an open volumetric air receiver (OVAR), which can heat air in excess of 800oC. The OVAR is placed on top of a tower and receives concentrated solar radiation from a heliostat field. Absorbers, mixer assembly, and the return air flow chamber (RAFC) are the major components of an OVAR. The absorber is a porous structure that transfers heat from concentrated solar radiation to ambient air, referred to as primary air. The mixer ensures uniform air temperature at the receiver exit. Flow of the relatively cooler return air in the RAFC ensures that the absorbers do not fail by overheating. In an earlier publication, the detailed design basis, fabrication, and characterization of a 2 kWth open volumetric air receiver (OVAR) based laboratory solar air tower simulator was presented. Development of an experimentally-validated, CFD based mathematical model which can ultimately be used for the design and scale-up of an OVAR has been the major objective of this investigation. In contrast to the published literature, where flow and heat transfer have been modeled primarily in a single absorber module, the present study has modeled the entire receiver assembly, including the RAFC. Flow and heat transfer calculations have been carried out in ANSYS using the LTNE model. The complex return air flow pattern in the RAFC requires complicated meshes and is computational and time intensive. Hence a simple, realistic 1-D mathematical model, which circumvents the need for carrying out detailed flow and heat transfer calculations, has also been proposed. Several important results have emerged from this investigation. Circumferential electrical heating of absorbers can mimic frontal heating by concentrated solar radiation reasonably well in testing and characterizing the performance of an OVAR. Circumferential heating, therefore, obviates the need for expensive high solar concentration simulators. Predictions suggest that the ratio of power on aperture (POA) and mass flow rate of air (MFR) is a normalizing parameter for characterizing the thermal performance of an OVAR. Increasing POA/MFR increases the maximum temperature of air, but decreases the thermal efficiency of an OVAR. Predictions of the 1-D mathematical are within 5% of ANSYS predictions and computation time is reduced from ~ 5 hours to a few seconds.

Keywords: absorbers, mixer assembly, open volumetric air receiver, return air flow chamber, solar thermal energy

Procedia PDF Downloads 198

Authors: Christos E. Lampropoulos, Maria Konsta, Vicky Dradaki, Irini Dri, Tamta Sirbilatze, Ifigenia Apostolou, Christina Kordali, Konstantina Panouria, Kostas Argyros, Georgios Mavras

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Malnutrition in hospitalized patients is related to increased morbidity and mortality. Purpose of our study was to assess nutritional status of hospitalized, elderly patients with various nutritional scores and to detect unfavorable prognostic factors, related to increased mortality and extended duration of admission. Methods: 150 patients (78 men, 72 women, mean age 80±8.2) were included in this cross-sectional study. Nutritional status was assessed by Mini Nutritional Assessment (MNA full, short-form), Malnutrition Universal Screening Tool (MUST) and short Nutritional Appetite Questionnaire (sNAQ). The following data were incorporated in analysis: Anthropometric and laboratory data, physical activity (International Physical Activity Questionnaires, IPAQ), smoking status, dietary habits and mediterranean diet (assessed by MedDiet score), cause and duration of current admission, medical history (co-morbidities, previous admissions). Primary endpoints were the mortality (from admission until 6 months afterwards) and duration of admission, compared to national guidelines for closed consolidated medical expenses. Mann-Whitney two-sample statistics or t-test was used for group comparisons and Spearman or Pearson coefficients for testing correlation between variables. Results: Normal nutrition was assessed in 54/150 (36%), 92/150 (61.3%) and in 106/150 (70.7%) of patients, according to full MNA, MUST and sNAQ questionnaires respectively. Mortality rate was 20.7% (31/150 patients). The patients who died until 6 months after admission had lower BMI (24±4.4 vs 26±4.8, p=0.04) and albumin levels (2.9±0.7 vs 3.4±0.7, p=0.002), significantly lower full MNA (14.5±7.3 vs 20.7±6, p<0.0001) and short-form MNA scores (7.3±4.2 vs 10.5±3.4, p=0.0002) compared to non-dead one. In contrast, the aforementioned patients had higher MUST (2.5±1.8 vs 0.5±1.02, p=<0.0001) and sNAQ scores (2.9±2.4 vs 1.1±1.3, p<0.0001). Additionally, they showed significantly lower MedDiet (23.5±4.3 vs 31.1±5.6, p<0.0001) and IPAQ scores (37.2±156.2 vs 516.5±1241.7, p<0.0001) compared to remaining one. These patients had extended hospitalization [5 (0-13) days vs 0 (-1-3) days, p=0.001]. Patients who admitted due to cancer depicted higher mortality rate (10/13, 77%), compared to those who admitted due to infections (12/73, 18%), stroke (4/15, 27%) or other causes (4/49, 8%) (p<0.0001). Extension of hospitalization was negatively correlated to both full (Spearman r=-0.35, p<0.0001) and short-form MNA (Spearman r=-0.33, p<0.0001) and positively correlated to MUST (Spearman r=0.34, p<0.0001) and sNAQ (Spearman r=0.3, p=0.0002). Additionally, the extension was inversely related to MedDiet score (Spearman r=-0.35, p<0.0001), IPAQ score (Spearman r=-0.34, p<0.0001), albumin levels (Pearson r=-0.36, p<0.0001), Ht (Pearson r=-0.2, p=0.02) and Hb (Pearson r=-0.18, p=0.02). Conclusion: A great proportion of elderly, hospitalized patients are malnourished or at risk of malnutrition. All nutritional scores, physical activity and albumin are significantly related to mortality and increased hospitalization.

Keywords: dietary habits, duration of admission, malnutrition, prognostic factors for mortality

Procedia PDF Downloads 289

Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

Procedia PDF Downloads 123

Authors: Anna Costanza Russo, Daniele Landi, Michele Germani

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Nowadays, the European Ecodesign Directive has emerged as a new approach to integrate environmental concerns into the product design and related processes. Ecodesign aims to minimize environmental impacts throughout the product life cycle, without compromising performances and costs. In addition, the recent Ecodesign Directives require products which are increasingly eco-friendly and eco-efficient, preserving high-performances. It is very important for producers measuring performances, for electric cooking ranges, hobs, ovens, and grills for household use, and a low power consumption of appliances represents a powerful selling point, also in terms of ecodesign requirements. The Ecodesign Directive provides a clear framework about the sustainable design of products and it has been extended in 2009 to all energy-related products, or products with an impact on energy consumption during the use. The European Regulation establishes measures of ecodesign of ovens, hobs, and kitchen hoods, and domestic use and energy efficiency of a product has a significant environmental aspect in the use phase which is the most impactful in the life cycle. It is important that the product parameters and performances are not affected by ecodesign requirements from a user’s point of view, and the benefits of reducing energy consumption in the use phase should offset the possible environmental impact in the production stage. Accurate measurements of cooking appliance performance are essential to help the industry to produce more energy efficient appliances. The development of ecodriven products requires ecoinnovation and ecodesign tools to support the sustainability improvement. The ecodesign tools should be practical and focused on specific ecoobjectives in order to be largely diffused. The main scope of this paper is the development, implementation, and testing of an innovative tool, which could be an improvement for the sustainable design of induction hobs. In particular, a prototypical software tool is developed in order to simulate the energy performances of the induction hobs. The tool is focused on a multiphysics model which is able to simulate the energy performances and the efficiency of induction hobs starting from the design data. The multiphysics model is composed by an electromagnetic simulation and a thermal simulation. The electromagnetic simulation is able to calculate the eddy current induced in the pot, which leads to the Joule heating of material. The thermal simulation is able to measure the energy consumption during the operational phase. The Joule heating caused from the eddy currents is the output of electromagnetic simulation and the input of thermal ones. The aims of the paper are the development of integrated tools and methodologies of virtual prototyping in the context of the ecodesign. This tool could be a revolutionary instrument in the field of industrial engineering and it gives consideration to the environmental aspects of product design and focus on the ecodesign of energy-related products, in order to achieve a reduced environmental impact.

Keywords: ecodesign, energy efficiency, induction hobs, virtual prototyping

Procedia PDF Downloads 251

Authors: Daniel Tscharnuter, Eliza Truszkiewicz, Gerald Pinter

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High-quality surfaces of plastic parts can be achieved in a very cost-effective manner using in-mold processes, where e.g. scratch resistant or high gloss polymer films are pre-formed and subsequently receive their support structure by injection molding. The pre-forming may be done by high-pressure forming. In this process, a polymer sheet is heated and subsequently formed into the mold by pressurized air. Due to the heat transfer to the cooled mold the polymer temperature drops below its glass transition temperature. This ensures that the deformed microstructure is retained after depressurizing, giving the sheet its final formed shape. The development of a forming process relies heavily on the experience of engineers and trial-and-error procedures. Repeated mold design and testing cycles are however both time- and cost-intensive. It is, therefore, desirable to study the process using reliable computer simulations. Through simulations, the construction of the mold and the effect of various process parameters, e.g. temperature levels, non-uniform heating or timing and magnitude of pressure, on the deformation of the polymer sheet can be analyzed. Detailed knowledge of the deformation is particularly important in the forming of polymer films with integrated electro-optical functions. Care must be taken in the placement of devices, sensors and electrical and optical paths, which are far more sensitive to deformation than the polymers. Reliable numerical prediction of the deformation of the polymer sheets requires sophisticated material models. Polymer films are often either transversely isotropic or orthotropic due to molecular orientations induced during manufacturing. The anisotropic behavior affects the resulting strain field in the deformed film. For example, parts of the same shape but different strain fields may be created by varying the orientation of the film with respect to the mold. The numerical simulation of the high-pressure forming of such films thus requires material models that can capture the nonlinear anisotropic mechanical behavior. There are numerous commercial polymer grades for the engineers to choose from when developing a new part. The effort required for comprehensive material characterization may be prohibitive, especially when several materials are candidates for a specific application. We, therefore, propose a class of models for compressible hyperelasticity, which may be determined from basic experimental data and which can capture key features of the mechanical response. Invariant-based hyperelastic models with a reduced number of invariants are formulated in a semi-numerical way, such that the models are determined from a single uniaxial tensile tests for isotropic materials, or two tensile tests in the principal directions for transversely isotropic or orthotropic materials. The simulation of the high pressure forming of an orthotropic polymer film is finally done using an orthotropic formulation of the hyperelastic model.

Keywords: hyperelastic, anisotropic, polymer film, thermoforming

Procedia PDF Downloads 618

Authors: Alireza Barari, Ahmad Abdi

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Introduction: Plyometric training (PT) is popular among individuals involved in dynamic sports, and is executed with a goal to improve muscular performance. Cytokines are considered as immunoregulatory molecules for regulation of immune function and other body responses. In addition, the pro-inflammatory cytokines, TNF-α andIL-1β, have been reported to be increased during and after exercises. If some of the cytokines which cause responses such as inflammation of cells in skeletal muscles, with manipulating of training program or optimizing nutrition, it can be avoided or limited from those injuries caused by cytokines release. Its shows that mistletoe extracts show immune-modulating effects. Materials and methods: present study was to investigate the effect of six weeks PT with or without mistletoe supplementation (MS)(10 mg/kg) on cytokine responses and performance in male basketball players. This study is semi-experimental. Statistic society of this study was basketball player’s male students of Mahmoud Abad city. Statistic samples are concluded of 32 basketball players with an age range of 14–17 years was selected from randomly. Selection of samples in four groups of 8 individuals Participants were randomly assigned to either an experimental group (E, n=16) that performed plyometric exercises with (n=8) or without (n=8) MS, or a control group that rested (C, n=16) with (n=8) or without (n=8) MS. Plants were collected in June from the Mazandaran forest in north of Iran. Then they dried in exposure to air without any exposition to sunlight, on a clean textile. For better drying the plants were high and down until they lost their water. Each subject consumed 10 mg/kg/day of extract for six weeks of intervention. Pre and post-testing was performed in the afternoon of the same day. Blood samples (10 ml) were collected from the intermediate cubital vein of the subjects. Serum concentration of IL-1β and TNF-α were measured by ELISA method. Data analysis was performed using pretest to posttest changes that assessed by t-test for paired samples. After the last plyometric training program, the second blood samples were in the next day. Group differences at baseline were evaluated using One-way ANOVA (post-hock Tukey) test is used for analysis and comparison of three group’s variables. Results: PT with or without MS improved the one repetition maximum leg and chest press, Sargeant test and power in RAST (P < 0.05). However there were no statistically significant differences between groups in Vo2max measures (P > 0.05). PT resulted in a significant increase in plasma IL-1β concentration from 1.08±0.4 mg/ml in pre-training to 1.68±0.18 mg/ml in post-training (P=0.006). While the MS significantly decreased the training-induced increment of IL-1β (P=0.007). In contrast, neither PT nor MS had any effect on TNF-α levels (P > 0.05). Discussion: The results of this investigation indicate that PT improved muscular performance and increases the IL-1β concentration. Increasing of IL-1β after exercise in damaged skeletal muscle has shown of the role of this cytokine in inflammation processes and damaged skeletal muscle repair. However mistletoe supplementation ameliorates the increment of IL-1β levels, indicating the beneficial effect of mistletoe on immune response following plyometric training.

Keywords: mistletoe supplementation, training, IL-1β, TNF-α

Procedia PDF Downloads 653

Authors: Gift Udoh, Diane S. Rohlman, Benjamin Sindt

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BACKGROUND: There is concern regarding the widespread use of pesticides and impacts on public health. Farmers in Nigeria frequently apply pesticides, including organophosphate pesticides which are known neurotoxicants. They receive little guidance on how much to apply or information about safe handling practices. Pesticide poisoning is one of the major hazards that farmers face in Nigeria. Farmers continue to use highly neurotoxic pesticides for agricultural activities. Because farmers receive little or no information on safe handling and how much to apply, they continue to develop severe and mild illnesses caused by high exposures to pesticides. The project aimed to reduce pesticide exposure among rural farmers in Nigeria by identifying hazards associated with pesticide use and developing and pilot testing training to reduce exposures to pesticides utilizing the hierarchy of controls system. METHODS: Information on pesticide knowledge, behaviors, barriers to safety, and prevention methods was collected from farmers in Nigeria through workplace observations, questionnaires, and interviews. Pre and post-surveys were used to measure farmer’s knowledge before and after the delivery of pesticide safety training. Training topics included the benefits and risks of using pesticides, routes of exposure and health effects, pesticide label activity, use and selection of PPE, ways to prevent exposure and information on local resources. The training was evaluated among farmers and changes in knowledge, attitudes and behaviors were collected prior to and following the training. RESULTS: The training was administered to 60 farmers, a mean age of 35, with a range of farming experience (<1 year to > 50 years). There was an overall increase in knowledge after the training. In addition, farmers perceived a greater immediate risk from exposure to pesticides and their perception of their personal risk increased. For example, farmers believed that pesticide risk is greater to children than to adults, recognized that just because a pesticide is put on the market doesn’t mean it is safe, and they were more confident that they could get advice about handling pesticides. Also, there was greater awareness about behaviors that can increase their exposure (mixing pesticides with bare hands, eating food in the field, not washing hands before eating after applying pesticides, walking in fields recently sprayed, splashing pesticides on their clothes, pesticide storage). CONCLUSION: These results build on existing evidence from a 2022 article highlighting the need for pesticide safety training in Nigeria which suggested that pesticide safety educational programs should focus on community-based, grassroots-style, and involve a family-oriented approach. Educating farmers on agricultural safety while letting them share their experiences with their peers is an effective way of creating awareness on the dangers associated with handling pesticides. Also, for rural communities, especially in Nigeria, pesticide safety pieces of training may not be able to reach some locations, so intentional scouting of rural farming communities and delivering pesticide safety training will improve knowledge of pesticide hazards. There is a need for pesticide information centers to be situated in rural farming communities or agro supply stores, which gives rural farmers information.

Keywords: pesticide exposure, pesticide safety, nigeria, rural farming, pesticide education

Procedia PDF Downloads 178

Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger

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Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.

Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia

Procedia PDF Downloads 74

Authors: Mohamed Habireche, Nacer E. Bacha, Mohamed Djeghdjough

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In the brick industry, smooth double roll crusher is used for medium and fine crushing of soft to medium hard material. Due to opposite inward rotation of the rolls, the feed material is nipped between the rolls and crushed by compression. They are subject to intense wear, known as three-body abrasion, due to the action of abrasive products. The production downtime affecting productivity stems from two sources: the bi-monthly rectification of the roll crushers and their replacement when they are completely worn out. Choosing the right material for the roll crushers should result in longer machine cycles, and reduced repair and maintenance costs. All roll crushers are imported from outside Algeria. This results in sometimes very long delivery times which handicap the brickyards, in particular in respecting delivery times and honored the orders made by customers. The aim of this work is to investigate the effect of alloying additions on microstructure and wear behavior of grey lamellar cast iron for smooth roll crushers in brick industry. The base gray iron was melted in an induction furnace with low frequency at a temperature of 1500 °C, in which return cast iron scrap, new cast iron ingot, and steel scrap were added to the melt to generate the desired composition. The chemical analysis of the bar samples was carried out using Emission Spectrometer Systems PV 8050 Series (Philips) except for the carbon, for which a carbon/sulphur analyser Elementrac CS-i was used. Unetched microstructure was used to evaluate the graphite flake morphology using the image comparison measurement method. At least five different fields were selected for quantitative estimation of phase constituents. The samples were observed under X100 magnification with a Zeiss Axiover T40 MAT optical microscope equipped with a digital camera. SEM microscope equipped with EDS was used to characterize the phases present in the microstructure. The hardness (750 kg load, 5mm diameter ball) was measured with a Brinell testing machine for both treated and as-solidified condition test pieces. The test bars were used for tensile strength and metallographic evaluations. Mechanical properties were evaluated using tensile specimens made as per ASTM E8 standards. Two specimens were tested for each alloy. From each rod, a test piece was made for the tensile test. The results showed that the quenched and tempered alloys had best wear resistance at 400 °C for alloyed grey cast iron (containing 0.62%Mn, 0.68%Cr, and 1.09% Cu) due to fine carbides in the tempered matrix. In quenched and tempered condition, increasing Cu content in cast irons improved its wear resistance moderately. Combined addition of Cu and Cr increases hardness and wear resistance for a quenched and tempered hypoeutectic grey cast iron.

Keywords: casting, cast iron, microstructure, heat treating

Procedia PDF Downloads 105

Authors: Francesca Marsili

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The reliability assessment of existing structures with probabilistic methods is becoming an increasingly important and frequent engineering task. However probabilistic reliability methods are based on an exhaustive knowledge of the stochastic modeling of the variables involved in the assessment; at the moment standards for the modeling of variables are absent, representing an obstacle to the dissemination of probabilistic methods. The framework according to probability distribution functions (PDFs) are established is represented by the Bayesian statistics, which uses Bayes Theorem: a prior PDF for the considered parameter is established based on information derived from the design stage and qualitative judgments based on the engineer past experience; then, the prior model is updated with the results of investigation carried out on the considered structure, such as material testing, determination of action and structural properties. The application of Bayesian statistics arises two different kind of problems: 1. The results of the updating depend on the engineer previous experience; 2. The updating of the prior PDF can be performed only if the structure has been tested, and quantitative data that can be statistically manipulated have been collected; performing tests is always an expensive and time consuming operation; furthermore, if the considered structure is an ancient building, destructive tests could compromise its cultural value and therefore should be avoided. In order to solve those problems, an interesting research path is represented by investigating Artificial Intelligence (AI) techniques that can be useful for the automation of the modeling of variables and for the updating of material parameters without performing destructive tests. Among the others, one that raises particular attention in relation to the object of this study is constituted by Case-Based Reasoning (CBR). In this application, cases will be represented by existing buildings where material tests have already been carried out and an updated PDFs for the material mechanical parameters has been computed through a Bayesian analysis. Then each case will be composed by a qualitative description of the material under assessment and the posterior PDFs that describe its material properties. The problem that will be solved is the definition of PDFs for material parameters involved in the reliability assessment of the considered structure. A CBR system represent a good candi¬date in automating the modelling of variables because: 1. Engineers already draw an estimation of the material properties based on the experience collected during the assessment of similar structures, or based on similar cases collected in literature or in data-bases; 2. Material tests carried out on structure can be easily collected from laboratory database or from literature; 3. The system will provide the user of a reliable probabilistic description of the variables involved in the assessment that will also serve as a tool in support of the engineer’s qualitative judgments. Automated modeling of variables can help in spreading probabilistic reliability assessment of existing buildings in the common engineering practice, and target at the best intervention and further tests on the structure; CBR represents a technique which may help to achieve this.

Keywords: reliability assessment of existing buildings, Bayesian analysis, case-based reasoning, historical structures

Procedia PDF Downloads 337

Authors: Malek Mahmoudi, Jonas Keruckas, Dmytro Volyniuk, Jurate Simokaitiene, Juozas V. Grazulevicius

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Host materials have been discovered as one of the most appealing methods for harvesting triplet states in organic materials for application in organic light-emitting diodes (OLEDs). The ideal host-guest system for emission in thermally delayed fluorescence OLEDs with 20% guest concentration for efficient energy transfer has been demonstrated in the present investigation. In this work, 3,3'-bis[9-(4-fluorophenyl) carbazole] (bFPC) has been used as the host, which induces balanced charge carrier transport for high-efficiency OLEDs.For providing a complete characterization of the synthesized compound, photophysical, photoelectrical, charge-transporting, and electrochemical properties of the compound have been examined. Excited-state lifetimes and singlet-triplet energy gaps were measured for characterization of photophysical properties, while thermogravimetric analysis, as well as differential scanning calorimetry measurements, were performed for probing of electrochemical and thermal properties of the compound. The electrochemical properties of this compound were investigated by cyclic voltammetry (CV) method, and ionization potential (IPCV) value of 5.68 eV was observed. UV–Vis absorption and photoluminescence spectrum of a solution of the compound in toluene (10-5 M) showed maxima at 302 and 405 nm, respectively. Photoelectron emission spectrometry was used for the characterization of charge-injection properties of the studied compound in solid. The ionization potential of this material was found to be 5.78 eV, and time-of-flight measurement was used for testing charge-transporting properties and hole mobility estimated using this technique in a vacuum-deposited layer reached 4×10-4 cm2 V-1s-1. Since the compound with high charge mobilities was tested as a host in an organic light-emitting diode. The device was fabricated by successive deposition onto a pre-cleaned indium tin oxide (ITO) coated glass substrate under a vacuum of 10-6 Torr and consisting of an indium-tin-oxide anode, hole injection and transporting layer(MoO3, NPB), emitting layer with bFPC as a host and 4CzIPN (2,4,5,6-tetra(9-carbazolyl)isophthalonitrile) which is a new highly efficient green thermally activated delayed fluorescence (TADF) material as an emitter, an electron transporting layer(TPBi) and lithium fluoride layer topped with aluminum layer as a cathode exhibited the highest maximum current efficiency and power efficiency of 33.9 cd/A and 23.5 lm/W, respectively and the electroluminescence spectrum showed only a peak at 512nm. Furthermore, the new bicarbazole-based compound was tested as a host in thermally activated delayed fluorescence organic light-emitting diodes are reaching luminance of 25300 cd m-2 and external quantum efficiency of 10.1%. Interestingly, the turn-on voltage was low enough (3.8 V), and such a device can be used for highly efficient light sources.

Keywords: thermally-activated delayed fluorescence, host material, ionization energy, charge mobility, electroluminescence

Procedia PDF Downloads 141

Authors: Yazan S. Khaled, Shazana Shamsuddin, Jim Tiernan, Mike McPherson, Thomas Hughes, Paul Millner, David G. Jayne

Abstract:

Introduction: There is a need for real-time imaging of colorectal cancer (CRC) to allow tailored surgery to the disease stage. Fluorescence guided laparoscopic imaging of primary colorectal cancer and the draining lymphatics would potentially bring stratified surgery into clinical practice and realign future CRC management to the needs of patients. Fluorescent nanoparticles can offer many advantages in terms of intra-operative imaging and therapy (theranostic) in comparison with traditional soluble reagents. Nanoparticles can be functionalised with diverse reagents and then targeted to the correct tissue using an antibody or Affimer (artificial binding protein). We aimed to develop and test fluorescent silica nanoparticles and targeted against CRC using an anti-carcinoembryonic antigen (CEA) Affimer (Aff). Methods: Anti-CEA and control Myoglobin Affimer binders were subcloned into the expressing vector pET11 followed by transformation into BL21 Star™ (DE3) E.coli. The expression of Affimer binders was induced using 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG). Cells were harvested, lysed and purified using nickle chelating affinity chromatography. The photosensitiser Foslip (soluble analogue of 5,10,15,20-Tetra(m-hydroxyphenyl) chlorin) was incorporated into the core of silica nanoparticles using water-in-oil microemulsion technique. Anti-CEA or control Affs were conjugated to silica nanoparticles surface using sulfosuccinimidyl-4-(N-maleimidomethyl) cyclohexane-1-carboxylate (sulfo SMCC) chemical linker. Binding of CEA-Aff or control nanoparticles to colorectal cancer cells (LoVo, LS174T and HC116) was quantified in vitro using confocal microscopy. Results: The molecular weights of the obtained band of Affimers were ~12.5KDa while the diameter of functionalised silica nanoparticles was ~80nm. CEA-Affimer targeted nanoparticles demonstrated 9.4, 5.8 and 2.5 fold greater fluorescence than control in, LoVo, LS174T and HCT116 cells respectively (p < 0.002) for the single slice analysis. A similar pattern of successful CEA-targeted fluorescence was observed in the maximum image projection analysis, with CEA-targeted nanoparticles demonstrating 4.1, 2.9 and 2.4 fold greater fluorescence than control particles in LoVo, LS174T, and HCT116 cells respectively (p < 0.0002). There was no significant difference in fluorescence for CEA-Affimer vs. CEA-Antibody targeted nanoparticles. Conclusion: We are the first to demonstrate that Foslip-doped silica nanoparticles conjugated to anti-CEA Affimers via SMCC allowed tumour cell-specific fluorescent targeting in vitro, and had shown sufficient promise to justify testing in an animal model of colorectal cancer. CEA-Affimer appears to be a suitable targeting molecule to replace CEA-Antibody. Targeted silica nanoparticles loaded with Foslip photosensitiser is now being optimised to drive photodynamic killing, via reactive oxygen generation.

Keywords: colorectal cancer, silica nanoparticles, Affimers, antibodies, imaging

Procedia PDF Downloads 240

Authors: Haftay Abraha Tadesse

Abstract:

Background: Staphylococcus is a genus of worldwide distributed bacteria correlated to several infectious of different sites in humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. Objective: The objective of this study was to determine the isolates, antimicrobial susceptibility patterns and Public Health Significance of Staphylococcus aureus in raw meat from butchery and abattoir houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from April to October 2019. Socio-demographic data and Public Health Significance were collected using a predesigned questionnaire. The raw meat samples were collected aseptically in the butchery and abattoir houses and transported using an ice box to Mekelle University, College of Veterinary Sciences, for isolating and identification of Staphylococcus aureus. Antimicrobial susceptibility tests were determined by the disc diffusion method. Data obtained were cleaned and entered into STATA 22.0 and a logistic regression model with odds ratio was calculated to assess the association of risk factors with bacterial contamination. A P-value < 0.05 was considered statistically significant. Results: In the present study, 88 out of 250 (35.2%) were found to be contaminated with Staphylococcus aureus. Among the raw meat specimens, the positivity rate of Staphylococcus aureus was 37.6% (n=47) and (32.8% (n=41), butchery and abattoir houses, respectively. Among the associated risks, factories not using gloves reduces risk was found to (AOR=0.222; 95% CI: 0.104-0.473), Strict Separation b/n clean & dirty (AOR= 1.37; 95% CI: 0.66-2.86) and poor habit of hand washing (AOR=1.08; 95%CI: 0.35 3.35) was found to be statistically significant and have associated with Staphylococcus aureus contamination. All isolates of thirty-seven of Staphylococcus aureus were checked and displayed (100%) sensitive to doxycycline, trimethoprim, gentamicin, sulphamethoxazole, amikacin, CN, Co trimoxazole and nitrofurantoi. Whereas the showed resistance to cefotaxime (100%), ampicillin (87.5%), Penicillin (75%), B (75%), and nalidixic acid (50%) from butchery houses. On the other hand, all isolates of Staphylococcus aureus isolate 100% (n= 10) showed sensitive chloramphenicol, gentamicin and nitrofurantoin, whereas they showed 100% resistance of Penicillin, B, AMX, ceftriaxone, ampicillin and cefotaxime from abattoirs houses. The overall multi-drug resistance pattern for Staphylococcus aureus was 90% and 100% of butchery and abattoir houses, respectively. Conclusion: 35.3% Staphylococcus aureus isolated were recovered from the raw meat samples collected from the butchery and abattoirs houses. More has to be done in the development of hand washing behavior and availability of safe water in the butchery houses to reduce the burden of bacterial contamination. The results of the present finding highlight the need to implement protective measures against the levels of food contamination and alternative drug options. The development of antimicrobial resistance is nearly always a result of repeated therapeutic and/or indiscriminate use of them. Regular antimicrobial sensitivity testing helps to select effective antibiotics and to reduce the problems of drug resistance development towards commonly used antibiotics.

Keywords: abattoir house, AMR, butchery house, S. aureus

Procedia PDF Downloads 98

Authors: Jong H. Kim, Kathleen L. Chan, Luisa W. Cheng

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Control of fungal pathogens, such as foodborne mycotoxin producers, is problematic as effective antimycotic agents are often very limited. Mycotoxin contamination significantly interferes with the safe production of foods or crops worldwide. Moreover, expansion of fungal resistance to commercial drugs or fungicides is a global human health concern. Therefore, there is a persistent need to enhance the efficacy of commercial antimycotic agents or to develop new intervention strategies. Disruption of the cellular antioxidant system should be an effective method for pathogen control. Such disruption can be achieved with safe, redox-active compounds. Natural phenolic derivatives are potent redox cyclers that inhibit fungal growth through destabilization of the cellular antioxidant system. The goal of this study is to identify novel, redox-active compounds that disrupt the fungal antioxidant system. The identified compounds could also function as sensitizing agents to conventional antimycotics (i.e., chemosensitization) to improve antifungal efficacy. Various benzo derivatives were tested against fungal pathogens. Gene deletion mutants of the yeast Saccharomyces cerevisiae were used as model systems for identifying molecular targets of benzo analogs. The efficacy of identified compounds as potent antifungal agents or as chemosensitizing agents to commercial drugs or fungicides was examined with methods outlined by the Clinical Laboratory Standards Institute or the European Committee on Antimicrobial Susceptibility Testing. Selected benzo derivatives possessed potent antifungal or antimycotoxigenic activity. Molecular analyses by using S. cerevisiae mutants indicated antifungal activity of benzo derivatives was through disruption of cellular antioxidant or cell wall integrity system. Certain benzo analogs screened overcame tolerance of Aspergillus signaling mutants, namely mitogen-activated protein kinase mutants, to fludioxonil fungicide. Synergistic antifungal chemosensitization greatly lowered minimum inhibitory or fungicidal concentrations of test compounds, including inhibitors of mitochondrial respiration. Of note, salicylaldehyde is a potent antimycotic volatile that has some practical application as a fumigant. Altogether, benzo derivatives targeting cellular antioxidant system of fungi (along with cell wall integrity system) effectively suppress fungal growth. Candidate compounds possess the antifungal, antimycotoxigenic or chemosensitizing capacity to augment the efficacy of commercial antifungals. Therefore, chemogenetic approaches can lead to the development of novel antifungal intervention strategies, which enhance the efficacy of established microbe intervention practices and overcome drug/fungicide resistance. Chemosensitization further reduces costs and alleviates negative side effects associated with current antifungal treatments.

Keywords: antifungals, antioxidant system, benzo derivatives, chemosensitization

Procedia PDF Downloads 262

Authors: Ayesha Mushtaq

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Asthma is a pulmonary disease in which blockade of the airway takes place due to inflammation as a response to certain allergens. Breathing troubles, cough, and dyspnea are one of the few symptoms. Several studies have indicated a significant effect on asthma due to changes in dietary routines. Certain food items, such as oily foods and other materials, are known to cause an increase in the symptoms of asthma. Low dietary intake of fruits and vegetables may be important in relation to asthma prevalence. The objective of this study is to assess and compare the nutritional status of asthmatic and non-asthmatic patients. The significance of this study lies in the factor that it will help nutritionists to arrange a feasible dietary routine for asthmatic patients. This research was conducted at the Pulmonology Department of the Pakistan Institute of Medical Science Islamabad. About thirty hundred thirty-four million people are affected by asthma worldwide. Pakistan is on the verge of being an uplifted urban population and asthma cases are increasingly high these days. Several studies suggest an increase in the Asthmatic patient population due to improper diet. This is a cross-sectional study aimed at assessing the nutritious standing of Asthmatic and non-asthmatic patients. This research took place at the Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan. The research included asthmatic and non-asthmatic patients coming to the pulmonology department clinic at the Pakistan Institute of Medical Sciences (PIMS). These patients were aged between 20-60 years. A questionnaire was developed for these patients to estimate their dietary plans in these patients. The methodology included four sections. The first section was the Socio-Demographic profile, which included age, gender, monthly income and occupation. The next section was anthropometric measurements which included the weight, height and body mass index (BMI) of an individual. The next section, section three, was about the biochemical attributes, such as for biochemical profiling, pulmonary function testing (PFT) was performed. In the next section, Dietary habits were assessed by a food frequency questionnaire (FFQ) through food habits and consumption pattern was assessed. The next section life style data, in which the person's level of physical activity, sleep and smoking habits were assessed. The next section was statistical analysis. All the data obtained from the study were statistically analyzed and assessed. Most of the asthma Patients were females, with weight more than normal or even obese. Body Mass Index (BMI) was higher in asthma Patients than those in non-Asthmatic ones. When the nutritional Values were assessed, we came to know that these patients were low on certain nutrients and their diet included more junk and oily food than healthy vegetables and fruits. Beverages intake was also included in the same assessment. It is evident from this study that nutritional status has a contributory effect on asthma. So, patients on the verge of developing asthma or those who have developed asthma should focus on their diet, maintain good eating habits and take healthy diets, including fruits and vegetables rather than oily foods. Proper sleep may also contribute to the control of asthma.

Keywords: BMI, nutrition, PAL, diet

Procedia PDF Downloads 77

Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

Procedia PDF Downloads 139