Search results for: thermal cycling machine

Authors: G. Yakubova, A. Kavetskiy, S. A. Prior, H. A. Torbert

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In-situ soil carbon determination over large soil surface areas (several hectares) is required in regard to carbon sequestration and carbon credit issues. This capability is important for optimizing modern agricultural practices and enhancing soil science knowledge. Collecting and processing representative field soil cores for traditional laboratory chemical analysis is labor-intensive and time-consuming. The neutron-stimulated gamma analysis method can be used for in-situ measurements of primary elements in agricultural soils (e.g., Si, Al, O, C, Fe, and H). This non-destructive method can assess several elements in large soil volumes with no need for sample preparation. Neutron-gamma soil elemental analysis utilizes gamma rays issued from different neutron-nuclei interactions. This process has become possible due to the availability of commercial portable pulse neutron generators, high-efficiency gamma detectors, reliable electronics, and measurement/data processing software complimented by advances in state-of-the-art nuclear physics methods. In Pulsed Fast Thermal Neutron Analysis (PFTNA), soil irradiation is accomplished using a pulsed neutron flux, and gamma spectra acquisition occurs both during and between pulses. This method allows the inelastic neutron scattering (INS) gamma spectrum to be separated from the thermal neutron capture (TNC) spectrum. Based on PFTNA, a mobile system for field-scale soil elemental determinations (primarily carbon) was developed and constructed. Our scanning methodology acquires data that can be directly used for creating soil elemental distribution maps (based on ArcGIS software) in a reasonable timeframe (~20-30 hectares per working day). Created maps are suitable for both agricultural purposes and carbon sequestration estimates. The measurement system design, spectra acquisition process, strategy for acquiring field-scale carbon content data, and mapping of agricultural fields will be discussed.

Keywords: neutron gamma analysis, soil elemental content, carbon sequestration, carbon credit, soil gamma spectroscopy, portable neutron generators, ArcMap mapping

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Authors: Elionai Moura, José A. Cunha, César Analide

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This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

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Authors: Tobias Schmithuesen, Johannes Henrich Schleifenbaum

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The additive manufacturing process laser powder bed fusion offers many advantages over conventional manufacturing processes. For example, almost any complex part can be produced, such as topologically optimized lightweight parts, which would be inconceivable with conventional manufacturing processes. A major challenge posed by the LPBF process, however, is, in most cases, the need to use and remove support structures on critically inclined part surfaces (α < 45 ° regarding substrate plate). These are mainly used for dimensionally accurate mapping of part contours and to reduce distortion by absorbing process-related internal stresses. Furthermore, they serve to transfer the process heat to the substrate plate and are, therefore, indispensable for the LPBF process. A major challenge for the economical use of the LPBF process in industrial process chains is currently still the high manual effort involved in removing support structures. According to the state of the art (SoA), the parts are usually treated by simple hand tools (e.g., pliers, chisels) or by machining (e.g., milling, turning). New automatable approaches are the removal of support structures by means of wet chemical ablation and thermal deburring. According to the state of the art, the support structures are essentially adapted to the LPBF process and not to potential post-processing steps. The aim of this study is the determination of support structure designs that are adapted to the mentioned post-processing approaches. In the first step, the essential boundary conditions for complete removal by means of the respective approaches are identified. Afterward, a representative demonstrator part with various macroscopic support structure designs will be LPBF-manufactured and tested with regard to a complete powder and support removability. Finally, based on the results, potentially suitable support structure designs for the respective approaches will be derived. The investigations are carried out on the example of the aluminum alloy AlSi10Mg.

Keywords: additive manufacturing, laser powder bed fusion, laser beam melting, selective laser melting, post processing, tool-free, wet chemical ablation, thermal deburring, aluminum alloy, AlSi10Mg

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Authors: Assad Maalouf, Lunjin Lu, James Lynott

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We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

Procedia PDF Downloads 176

Authors: Eliott Guérin, Remi Daudin, Georges Kalepsi, Alexis Lenain, Sebastien Gravier, Benoit Ter-Ovanessian, Damien Fabregue, Jean-Jacques Blandin

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Due to interesting compromise between mechanical and corrosion properties, Zr-based BMGs are attractive for biomedical applications. However, the enhancement of their glass forming ability (GFA) is often achieved by addition of toxic elements like Ni or Be, which is of course a problem for such applications. Consequently, the development of Ni-free Be-free Zr-based BMGs is of great interest. We have developed a Zr-based (Ni and Be-free) amorphous metallic alloy with an elastic limit twice the one of Ti-6Al-4V. The Zr56Co28Al16 composition exhibits a yield strength close to 2 GPa and low Young’s modulus (close to 90 GPa) [1-2]. In this work, we investigated Niobium (Nb) addition through substitution of Zr up to 8 at%. Cobalt substitution has already been reported [3], but we chose Zr substitution to preserve the glass forming ability. In this case, we show that the glass forming ability for 5 mm diameters rods is maintained up to 3 at% of Nb substitution using suction casting in cooper moulds. Concerning the thermal stability, we measure a strong compositional dependence on the glass transition (Tg). Using DSC analysis (heating rate 20 K/min), we show that the Tg rises from 752 K for 0 at% of Nb to 759 K for 3 at% of Nb. Yet, the thermal range between Tg and the crystallisation temperature (Tx) remains almost unchanged from 33 K to 35 K. Uniaxial compression tests on 2 mm diameter pillars and 3 points bending (3PB) tests on 1 mm thick plates are performed to study the Nb addition on the mechanical properties and the plastic behaviour. With these tests, an optimal Nb concentration is found, improving both plasticity and fatigue resistance. Through interpretations of DSC measurements, an attempt is made to correlate the modifications of the mechanical properties with the structural changes. The optimized chemical, structural and mechanical properties through Nb addition are encouraging to develop the potential of this BMG alloy for biomedical applications. For this purpose, we performed polarisation, immersion and cytotoxicity tests. The figure illustrates the polarisation response of Zr56Co28Al16, Zr54Co28Al16Nb2 and TA6V as a reference after 2h of open circuit potential. The results show that the substitution of Zr by a small amount of Nb significantly improves the corrosion resistance of the alloy.

Keywords: metallic glasses, amorphous metal, medical, mechanical resistance, biocompatibility

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Authors: Mechri hanane, Azzaz Mohammed

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Polycrystalline CuFe thin film was prepared by thermal evaporation process (Physical vapor deposition), using the nanocrystalline CuFe powder obtained by mechanical alloying After 24 h of milling elemental powders. The microscopic study of nanocrystalline powder and the thin film of Cu70Fe30 binary alloy were examined using transmission electron microscopy (TEM) and scanning electron microscope (SEM). The cross-sectional TEM images showed that the obtained CuFe layer was polycrystalline film of about 20 nm thick and composed of grains of different size ranging from 4 nm to 18 nm.

Keywords: nanomaterials, thin films, TEM, SEM

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Authors: Thanaa Abdel Moghny, Mohamed Keshawy, Mahmoud Fathy, Abdul-Raheim M. Abdul-Raheim, Khalid I. Kabel, Ahmed F. El-Kafrawy, Mahmoud Ahmed Mousa, Ahmed E. Awadallah

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Ecological pollution is of great concern for human health and the environment. Numerous organic and inorganic pollutants usually discharged into the water caused carcinogenic or toxic effect for human and different life form. In this respect, this work aims to treat water contaminated by organic and inorganic waste using sorbent based on polystyrene. Therefore, two different series of adsorbent material were prepared; the first one included the preparation of polymeric sorbent from the reaction of styrene acrylate ester and alkyl acrylate. The second series involved syntheses of composite ion exchange resins of waste polystyrene and   amorphous carbon thin film (WPS/ACTF) by solvent evaporation using micro emulsion polymerization. The produced ACTF/WPS nanocomposite was sulfonated to produce cation exchange resins ACTF/WPSS nanocomposite. The sorbents of the first series were characterized using FTIR, ¹H NMR, and gel permeation chromatography. The thermal properties of the cross-linked sorbents were investigated using thermogravimetric analysis, and the morphology was characterized by scanning electron microscope (SEM). The removal of organic pollutant was determined through absorption tests in a various organic solvent. The chemical and crystalline structure of nanocomposite of second series has been proven by studies of FTIR spectrum, X-rays, thermal analysis, SEM and TEM analysis to study morphology of resins and ACTF that assembled with polystyrene chain. It is found that the composite resins ACTF/WPSS are thermally stable and show higher chemical stability than ion exchange WPSS resins. The composite resin was evaluated for calcium hardness removal. The result is evident that the ACTF/WPSS composite has more prominent inorganic pollutant removal than WPSS resin. So, we recommend the using of nanocomposite resin as new potential applications for water treatment process.

Keywords: nanocomposite, sorbent materials, waste water, waste polystyrene

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Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

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Compressed Natural Gas (CNG) mainly consists of Methane CH₄ and has a low carbon to hydrogen ratio relative to other hydrocarbons. As a result, it has the potential to reduce CO₂ emissions by more than 20% relative to conventional fuels like diesel or gasoline Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels whether they are gaseous or liquid, its main component, CH₄, burns at a slower rate than conventional fuels A higher pressure and a leaner cylinder environment will overemphasize slow burn characteristic of CH₄. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJIs, which contain small orifices that connect the prechamber to the main chamber, scavenging is one of the main factors that reduce TJI performance. Specifically, providing the right mixture of fuel and air has been identified as a key challenge. The reason for this is the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem that combustion residual gases such as CO₂, CO and NOx from the previous combustion cycle dilute the pre- chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By applying air to the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of combustion. This paper investigates the 3D-simulated combustion characteristics of a Direct Injected (DI-CNG) fuelled SI en- gine with a pre-chamber equipped with an air channel by using AVL FIRE software. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 Revolutions Per Minute (RPM), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as the baseline. After validating simulation data, baseline engine conditions were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the simulated (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and spark plug. In conclusion, the active pre-chamber with an air channel demon-strated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: turbulent jet ignition, active air control turbulent jet ignition, pre-chamber ignition system, active and passive pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions

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Authors: R. Benelmir, M. El Kadri, A. Donnot, D. Descieux

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HVAC represents a significant part of energy needs in buildings. Integrating renewable energy in cooling processes contributes to reducing primary energy consumption. Sorption refrigeration allows cold production through the use of solar/biomass/geothermal energy or even valuation of waste heat. This work presents an analysis of an experimental bench incorporating an adsorption chiller driven by hybrid energy resources associating solar thermal collectors with a cogeneration gas engine and a geothermal heat pump.

Keywords: solar cooling, cogeneration, geothermal heat pump, hybrid energy resources

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Authors: T. Davitashvili

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In this paper, some results of numerical simulation of the air flow dynamics in the troposphere over the Caucasus Mountains taking place in conditions of nonstationarity of large-scale undisturbed background flow are presented. Main features of the atmospheric currents changeability while air masses are transferred from the Black Sea to the land’s surface had been investigated. In addition, the effects of thermal and advective-dynamic factors of atmosphere on the changes of the West Georgian climate have been studied. It was shown that non-proportional warming of the Black Sea and Colkhi lowland provokes the intensive strengthening of circulation and effect of climate cooling in the western Georgia.

Keywords: regional climate, numerical simulation, local circulation, orographic effect

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Authors: Ammaarah Gamieldien

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Depression is a very common and serious mental illness that has a significant impact on both the social and economic aspects of sufferers worldwide. This study aimed to investigate the association between body mass index (BMI), blood pressure, and lipid profiles with mental health symptoms in university students. Secondary objectives included the associations between the variables (BMI, blood pressure, and lipids) with themselves, as they are key factors in cardiometabolic disease. Sixty-three (63) students participated in the study. Thirty-two (32) were assigned to the control group (minimal-mild depressive symptoms), while 31 were assigned to the depressive group (moderate to severe depressive symptoms). Montgomery-Asberg Depression Rating Scale (MADRS) and Beck Depression Inventory (BDI) were used to assess depressive scores. Anthropometric measurements such as weight (kg), height (m), waist circumference (WC), and hip circumference were measured. Body mass index (BMI) and ratios such as waist-to-hip ratio (WHR) and waist-to-height ratio (WtHR) were also calculated. Blood pressure was measured using an automated AfriMedics blood pressure machine, while lipids were measured using a CardioChek plus analyzer machine. Statistics were analyzed via the SPSS statistics program. There were no significant associations between anthropometric measurements and depressive scores (p > 0.05). There were no significant correlations between lipid profiles and depression when running a Spearman’s rho correlation (P > 0.05). However, total cholesterol and LDL-C were negatively associated with depression, and triglycerides were positively associated with depression after running a point-biserial correlation (P < 0.05). Overall, there were no significant associations between blood pressure measurements and depression (P > 0.05). However, there was a significant moderate positive correlation between systolic blood pressure and MADRS scores in males (P < 0.05). Depressive scores positively and strongly correlated to how long it takes participants to fall asleep. There were also significant associations with regard to the secondary objectives. This study indicates the importance of determining the prevalence of depression among university students in South Africa. If the prevalence and factors associated with depression are addressed, depressive symptoms in university students may be improved.

Keywords: depression, blood pressure, body mass index, lipid profiles, mental health symptoms

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Authors: Stefanie Ficht, Lukas Schübel, Magdalena Kleybolte, Markus Eblenkamp, Jana Steger, Dirk Wilhelm, Petra Mela

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Although 3D printing as transformative technology has become of increasing interest in the medical field and the demand for biodegradable polymers has developed to a considerable extent, there are only a few additively manufactured, biodegradable implants on the market. Additionally, the sterilization of such implants and its side effects on degradation have still not been sufficiently studied. Within this work, thermosensitive poly p-dioxanone (PPDO) samples were printed with fused filament fabrication (FFF) and investigated. Subsequently, H₂O₂ plasma and gamma radiation were used as low-temperature sterilization techniques and compared among each other and the control group (no sterilization). In order to assess the effect of different sterilization on the degradation behavior of PPDO, the samples were immersed in phosphate-buffered solution (PBS) over 28 days, and surface morphology, thermal properties, molecular weight, inherent viscosity, and mechanical properties were examined at regular time intervals. The study demonstrates that PPDO was printed with great success and that thermal properties, molecular weight (Mw), and inherent viscosity (IV) were not significantly affected by the printing process itself. H₂O₂ plasma sterilization did not significantly harm the thermosensitive polymer, while gamma radiation lowered IV and Mw statistically significantly compared to the control group (p < 0.001). During immersion in PBS, a decrease in Mw and mechanical strength occurred for all samples. However, gamma sterilized samples were affected to a much higher extent compared to the two other sample groups both in final values and timeline. This was confirmed by scanning electron microscopy showing no changes of surface morphology of (non-sterilized) control samples, first microcracks appearing on plasma sterilized samples after two weeks while being present on gamma sterilized samples already immediately after radiation to then further deteriorate over immersion duration. To conclude, we demonstrated that FFF and H₂O₂ plasma sterilization are well suited for processing thermosensitive, biodegradable polymers used for the development of innovative short-term medical applications.

Keywords: additive manufacturing, sterilization, biodegradable, thermosensitive, medical application

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Authors: Sewon Kim, Changyeop Lee

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A noble low NOx combustion technology, based on partial oxidation combustion concept in a fuel rich combustion zone, is successfully applied in this research. The burner is designed such that a portion of fuel is heated and pre-vaporized in the furnace then injected into a fuel rich combustion zone so that a partial oxidation reaction occurs. The effects of equivalence ratio, thermal load, and fuel distribution ratio on the emissions of NOx and CO are experimentally investigated. This newly developed combustion technology is successfully applied to industrial furnace, and showed extremely low NOx emission levels.

Keywords: low NOx, combustion, burner, fuel rich

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Authors: Nora Arbaoui, Rachid Tadili

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The substantial increase of areas cultivated under glasshouses compels the use of other natural heating and cooling procedures to make a profit as well as avoid both exorbitant fuel consumption and CO₂ emissions. This experimental study is designed to examine the functioning of a solar heating system that will increase positive consequences in terms of both quantity and quality while successfully enhancing greenhouse microclimate during wintertime. Those configurations have been tested in a miniaturized greenhouse simply after having optimized the operating parameters. These were noteworthy results when compared to an unheated witness greenhouse.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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Authors: Mouna Essaadi, Mohamed Khafallah, Abdallah Saad, Hamid Chaikhy

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This paper presents a comparative analysis between conventional direct torque control (C_DTC), Modified direct torque control (M_DTC) and twelve sectors direct torque control (12_DTC).Those different strategies are compared by simulation in term of torque, flux and stator current performances. Finally, a summary of the comparative analysis is presented.

Keywords: C_DTC, M_DTC, 12_DTC, torque dynamic, stator current, flux, performances

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Authors: Geremew Geidare Kailo, Igor Gáspár, András Koris, Ivana Pajčin, Flóra Vitális, Vanja Vlajkov

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Three-dimension (3D) printing, a very popular additive manufacturing technology, has recently undergone rapid growth and replaced the use of conventional technology from prototyping to producing end-user parts and products. The 3D Printing technology involves a digital manufacturing machine that produces three-dimensional objects according to designs created by the user via 3D modeling or computer-aided design/manufacturing (CAD/CAM) software. The most popular 3D printing system is Fused Deposition Modeling (FDM) or also called Fused Filament Fabrication (FFF). A 3D-printed object is considered food safe if it can have direct contact with the food without any toxic effects, even after cleaning, storing, and reusing the object. This work analyzes the processing timeline of the filament (material for 3D printing) from unboxing to the extrusion through the nozzle. It is an important task to analyze the growth of bacteria on the 3D printed surface and in gaps between the layers. By default, the 3D-printed object is not food safe after longer usage and direct contact with food (even though they use food-safe filaments), but there are solutions for this problem. The aim of this work was to evaluate the 3D-printed object from different perspectives of food safety. Firstly, testing antimicrobial 3D printing filaments from a food safety aspect since the 3D Printed object in the food industry may have direct contact with the food. Therefore, the main purpose of the work is to reduce the microbial load on the surface of a 3D-printed part. Coating with epoxy resin was investigated, too, to see its effect on mechanical strength, thermal resistance, surface smoothness and food safety (cleanability). Another aim of this study was to test new temperature-resistant filaments and the effect of high temperature on 3D printed materials to see if they can be cleaned with boiling or similar hi-temp treatment. This work proved that all three mentioned methods could improve the food safety of the 3D printed object, but the size of this effect variates. The best result we got was with coating with epoxy resin, and the object was cleanable like any other injection molded plastic object with a smooth surface. Very good results we got by boiling the objects, and it is good to see that nowadays, more and more special filaments have a food-safe certificate and can withstand boiling temperatures too. Using antibacterial filaments reduced bacterial colonies to 1/5, but the biggest advantage of this method is that it doesn’t require any post-processing. The object is ready out of the 3D printer. Acknowledgements: The research was supported by the Hungarian and Serbian bilateral scientific and technological cooperation project funded by the Hungarian National Office for Research, Development and Innovation (NKFI, 2019-2.1.11-TÉT-2020-00249) and the Ministry of Education, Science and Technological Development of the Republic of Serbia. The authors acknowledge the Hungarian University of Agriculture and Life Sciences’s Doctoral School of Food Science for the support in this study

Keywords: food safety, 3D printing, filaments, microbial, temperature

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Authors: Enhui Wang, Qingzhu Ou, Yan Tang, Xiaodong Guo

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As one of most popular polyanionic compounds in lithium-ion cathode materials, Li3V2(PO4)3 has always suffered from the low rate capability especially during 3~4.8V, which is considered to be related with the ion diffusion resistance and structural transformation during the Li+ de/intercalation. Here, as the change of cut-off voltages, cycling numbers and current densities, the process of SEI interfacial film’s formation-growing- destruction-repair on the surface of the cathode, the structural transformation during the charge and discharge, the de/intercalation kinetics reflected by the electrochemical impedance and the diffusion coefficient, have been investigated in detail. Current density, cycle numbers and cut-off voltage impacting on interfacial film and structure was studied specifically. Firstly, the matching between electrolyte and material was investigated, it turned out that the batteries with high voltage electrolyte showed the best electrochemical performance and high voltage electrolyte would be the best electrolyte. Secondly, AC impedance technology was used to study the changes of interface impedance and lithium ion diffusion coefficient, the results showed that current density, cycle numbers and cut-off voltage influenced the interfacial film together and the one who changed the interfacial properties most was the key factor. Scanning electron microscopy (SEM) analysis confirmed that the attenuation of discharge specific capacity was associated with the destruction and repair process of the SEI film. Thirdly, the X-ray diffraction was used to study the changes of structure, which was also impacted by current density, cycle numbers and cut-off voltage. The results indicated that the cell volume of Li3V2 (PO4 )3 increased as the current density increased; cycle numbers merely influenced the structure of material; the cell volume decreased first and moved back gradually after two Li-ion had been deintercalated as the charging cut-off voltage increased, and increased as the intercalation number of Li-ion increased during the discharging process. Then, the results which studied the changes of interface impedance and lithium ion diffusion coefficient turned out that the interface impedance and lithium ion diffusion coefficient increased when the cut-off voltage passed the voltage platforms and decreased when the cut-off voltage was between voltage platforms. Finally, three-electrode system was first adopted to test the activation energy of the system, the results indicated that the activation energy of the three-electrode system (22.385 KJ /mol) was much smaller than that of two-electrode system (40.064 KJ /mol).

Keywords: cut-off voltage, de/intercalation kinetics, solid electrolyte interphase film, structural transformation

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Authors: Anuschka Curran, Sandra Barnard

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Coral reefs are of the most diverse and productive ecosystems on the planet, but due to the impact of climate change, these infrastructures are dying off primarily through coral bleaching. Coral bleaching can be described as the process by which zooxanthellae (algal endosymbionts) are expelled from the gastrodermal cavity of the respective coral host, causing increased coral whitening. The general consensus is that mass coral bleaching is due to the dysfunction of photosynthetic processes in the zooxanthellae as a result of the combined action of elevated temperature and light-stress. The question then is, do zooxanthellae have the potential to play a key role in the future of coral reef restoration through genetic engineering? The aim of this study is firstly to review the different zooxanthellae taxa and their traits with respect to environmental stress, and secondly, to review the information available on the protective mechanisms present in zooxanthellae cells when experiencing temperature fluctuations, specifically concentrating on heat shock proteins and the antioxidant stress response of zooxanthellae. The eight clades (A-H) previously recognized were redefined into seven genera. Different zooxanthellae taxa exhibit different traits, such as their photosynthetic stress responses to light and temperature. Zooxanthellae have the ability to determine the amount and type of heat shock proteins (hsps) present during a heat response. The zooxanthellae can regulate both the host’s respective hsps as well as their own. Hsps, generally found in genotype C3 zooxanthellae, such as Hsp70 and Hsp90, contribute to the thermal stress response of the respective coral host. Antioxidant activity found both within exposed coral tissue, and the zooxanthellae cells can prevent coral hosts from expelling their endosymbionts. The up-regulation of gene expression, which may mitigate thermal stress induction of any of the physiological aspects discussed, can ensure stable coral-zooxanthellae symbiosis in the future. It presents a viable alternative strategy to preserve reefs amidst climate change. In conclusion, despite their unusual molecular design, genetic engineering poses as a useful tool in understanding and manipulating variables and systems within zooxanthellae and therefore presents a solution that can ensure stable coral-zooxanthellae symbiosis in the future.

Keywords: antioxidant enzymes, genetic engineering, heat-shock proteins, Symbiodinium

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Authors: Lopez J., Mehrvar M., Quinones E., Suarez A., Romero C.

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Membrane Distillation is an emerging technology that uses thermal and membrane steps for the desalination process to get drinking water. In this study, silver nanoparticles (AgNP) were deposited by dip-coating process over Polyvinylidene Fluoride, Fiberglass hydrophilic, and Polytetrafluoroethylene hydrophobic commercial membranes as substrate. Membranes were characterized and used in a Vacuum Membrane Distillation cell under Ultraviolet light with sea salt feed solution. The presence of AgNP increases the absorption of energy on the membrane, which improves the transmembrane flux.

Keywords: silver nanoparticles, membrane distillation, desalination technologies, heat deliver

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Authors: E. Karami, M. Bohloul, P. Najmadi

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The superconducting system is a suitable system for quantum computers. Quantum entanglement is a fundamental phenomenon that is key to the power of quantum computers. Quantum entanglement has been studied in different superconducting systems. In this paper, we are investigating a superconducting two-qubit system as a macroscopic system. These systems include two coupled Quantronium circuits. We calculate quantum entanglement and thermalization for system evolution and compare them. We observe, thermalization and entanglement have different behavior, and equilibrium thermal state has maximum entanglement.

Keywords: macroscopic system, quantum entanglement, thermalization, superconducting system

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Authors: Janet Modu, Jean-Francois Georgin, Laurent Briancon, Eric Antoinet

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The current practice during the repowering phase of wind turbines is deconstruction of existing foundations and construction of new foundations to accept larger wind loads or once the foundations have reached the end of their service lives. The ongoing research project FUI25 FEDRE (Fondations d’Eoliennes Durables et REpowering) therefore serves to propose scalable wind turbine foundation designs to allow reuse of the existing foundations. To undertake this research, numerical models and laboratory-scale models are currently being utilized and implemented in the GEOMAS laboratory at INSA Lyon following instrumentation of a reference wind turbine situated in the Northern part of France. Sensors placed within both the foundation and the underlying soil monitor the evolution of stresses from the foundation’s early age to stresses during service. The results from the instrumentation form the basis of validation for both the laboratory and numerical works conducted throughout the project duration. The study currently focuses on the effect of coupled mechanisms (Thermal-Hydro-Mechanical-Chemical) that induce stress during the early age of the reinforced concrete foundation, and scale factor considerations in the replication of the reference wind turbine foundation at laboratory-scale. Using THMC 3D models on COMSOL Multi-physics software, the numerical analysis performed on both the laboratory-scale and the full-scale foundations simulate the thermal deformation, hydration, shrinkage (desiccation and autogenous) and creep so as to predict the initial damage caused by internal processes during concrete setting and hardening. Results show a prominent effect of early age properties on the damage potential in full-scale wind turbine foundations. However, a prediction of the damage potential at laboratory scale shows significant differences in early age stresses in comparison to the full-scale model depending on the spatial position in the foundation. In addition to the well-known size effect phenomenon, these differences may contribute to inaccuracies encountered when predicting ultimate deformations of the on-site foundation using laboratory scale models.

Keywords: cement hydration, early age behavior, reinforced concrete, shrinkage, THMC 3D models, wind turbines

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

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Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

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Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

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The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: Gülşah Çelik Gül, Figen Kurtuluş

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Cesium molybdates with general formula CsMIII(MoO4)2, where MIII = Bi, Dy, Pr, Er, exhibit rich polymorphism, and crystallize in a layered structure. These properties cause intensive studies on cesium molybdates. CsBi(MoO4)2 was synthesized by microwave method by using cerium sulphate, bismuth oxide and molybdenum (VI) oxide in an appropriate molar ratio. Characterizations were done by x-ray diffraction (XRD), fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS), thermo gravimetric/differantial thermal analysis (TG/DTA).

Keywords: cesium bismuth dimolybdate, microwave synthesis, powder x-ray diffraction, rare earth dimolybdates

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Authors: Azizi Cherifa, O. Benzaoui

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The thermal aspects in the design of power circuits often deserve as much attention as pure electric components aspects as the operating temperature has a direct influence on their static and dynamic characteristics. MOSFET is fundamental in the circuits, it is the most widely used device in the current production of semiconductor components using their honorable performance. The aim of this contribution is devoted to the effect of the temperature on the properties of MOSFETs. The study enables us to calculate the drain current as function of bias in both linear and saturated modes. The effect of temperature is evaluated using a numerical simulation, using the laws of mobility and saturation velocity of carriers as a function of temperature.

Keywords: temperature, MOSFET, mobility, transistor

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Authors: Tamara Grujic, Mirjana Bonkovic

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Measurements and quantitative analysis of kinematic parameters of human hand movements have an important role in different areas such as hand function rehabilitation, modeling of multi-digits robotic hands, and the development of machine-man interfaces. In this paper the assessment and evaluation of the reach-to-grasp movement by using computerized and robot-assisted method is described. Experiment involved the measurements of hand positions of seven healthy subjects during grasping three objects of different shapes and sizes. Results showed that three dominant phases of reach-to-grasp movements could be clearly identified.

Keywords: human hand, kinematics, measurement and analysis, reach-to-grasp movement

Procedia PDF Downloads 457