Search results for: thermal processing

Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Thanusha D. Abeywickrama, Inoka C. Perera, Genji Kurisu

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Tuberculosis, considered being as the ninth leading cause of death worldwide, cause from a single infectious agent M. tuberculosis and the drug resistance nature of this bacterium is a continuing threat to the world. Therefore TB preventing treatment is expanding, where this study designed to analyze the regulatory mechanism of GntR transcriptional regulator gene Rv0792c, which lie between several genes codes for some hypothetical proteins, a monooxygenase and an oxidoreductase. The gene encoding Rv0792c was cloned into pET28a and expressed protein was purified to near homogeneity by Nickel affinity chromatography. It was previously reported that the protein binds within the intergenic region (BS region) between Rv0792c gene and monooxygenase (Rv0793). This resulted in binding of three protein molecules with the BS region suggesting tight control of monooxygenase as well as its own gene. Since monooxygenase plays a key role in metabolism, this gene may have a global regulatory role. The natural ligand for this regulator is still under investigation. In relation to the Rv0792 protein structure, a Circular Dichroism (CD) spectrum was carried out to determine its secondary structure elements. Percentage-wise, 17.4% Helix, 21.8% Antiparallel, 5.1% Parallel, 12.3% turn and 43.5% other were revealed from CD spectrum data under room temperature. Differential Scanning Calorimetry (DSC) was conducted to assess the thermal stability of Rv0792, which the melting temperature of protein is 57.2 ± 0.6 °C. The graph of heat capacity (Cp) versus temperature for the best fit was obtained for non-two-state model, which concludes the folding of Rv0792 protein occurs through stable intermediates. Peak area (∆HCal ) and Peak shape (∆HVant ) was calculated from the graph and ∆HCal / ∆HVant was close to 0.5, suggesting dimeric nature of the protein.

Keywords: CD spectrum, DSC analysis, GntR transcriptional regulator, protein structure

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Authors: Zhiguo Yang, Xiangan Yue, Minglu Shao, Yue Yang, Rongjie Yan

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It is difficult to realize deep profile control because of the small pore-throats and easy water channeling in low-permeability heterogeneous reservoir, and the traditional polymer microspheres have the contradiction between injection and plugging. In order to solve this contradiction, the controllable self-aggregating colloidal particles (CSA) containing amide groups on the surface of microspheres was prepared based on emulsion polymerization of styrene and acrylamide. The dispersed solution of CSA colloidal particles, whose particle size is much smaller than the diameter of pore-throats, was injected into the reservoir. When the microspheres migrated to the deep part of reservoir, , these CSA colloidal particles could automatically self-aggregate into large particle clusters under the action of the shielding agent and the control agent, so as to realize the plugging of the water channels. In this paper, the morphology, temperature resistance and self-aggregation properties of CSA microspheres were studied by transmission electron microscopy (TEM) and bottle test. The results showed that CSA microspheres exhibited heterogeneous core-shell structure, good dispersion, and outstanding thermal stability. The microspheres remain regular and uniform spheres at 100℃ after aging for 35 days. With the increase of the concentration of the cations, the self-aggregation time of CSA was gradually shortened, and the influence of bivalent cations was greater than that of monovalent cations. Core flooding experiments showed that CSA polymer microspheres have good injection properties, CSA particle clusters can effective plug the water channels and migrate to the deep part of the reservoir for profile control.

Keywords: heterogeneous reservoir, deep profile control, emulsion polymerization, colloidal particles, plugging characteristic

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Abbas Mohamed Abbas, Raafat El-Shafie Fat-Helbary, Karrar Omar El Fergawy, Ahmed Hamed Sayed

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The exploration in archaeological area requires non-invasive methods, and hence the Ground Penetrating Radar (GPR) technique is a proper candidate for this task. GPR investigation is widely applied for searching for hidden ancient targets. So, in this paper GPR technique has been used in archaeological investigation. The aim of this study was to obtain information about the subsurface and associated structures beneath two selected sites at the western bank of the River Nile at Aswan city. These sites have archaeological structures of different ages starting from 6thand 12th Dynasties to the Greco-Roman period. The first site is called Nag’ El Gulab, the study area was 30 x 16 m with separating distance 2m between each profile, while the second site is Nag’ El Qoba, the survey method was not in grid but in lines pattern with different lengths. All of these sites were surveyed by GPR model SIR-3000 with antenna 200 MHz. Beside the processing of each profile individually, the time-slice maps have been conducted Nag’ El Gulab site, to view the amplitude changes in a series of horizontal time slices within the ground. The obtained results show anomalies may interpret as presence of associated tombs structures. The probable tombs structures similar in their depth level to the opened tombs in the studied areas.

Keywords: ground penetrating radar, archeology, Nag’ El Gulab, Nag’ El Qoba

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Authors: Foo Shen Hwang, Thomas Confrey, Stephen Scully, Barry Flannery

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Thermal characterization plays an important role in battery pack design. Lithium-ion batteries have to be maintained between 15-35 °C to operate optimally. Heat is generated (Q) internally within the batteries during both the charging and discharging phases. This can be quantified using several standard methods. The most common method of calculating the batteries heat generation is through the addition of both the joule heating effects and the entropic changes across the battery. In addition, such values can be derived by identifying the open-circuit voltage (OCV), nominal voltage (V), operating current (I), battery temperature (T) and the rate of change of the open-circuit voltage in relation to temperature (dOCV/dT). This paper focuses on experimental characterization and comparative modelling of the heat generation rate (Q) across several current discharge rates (0.5C, 1C, and 1.5C) of a 18650 cell. The analysis is conducted utilizing several non-linear mathematical functions methods, including polynomial, exponential, and power models. Parameter fitting is carried out over the respective function orders; polynomial (n = 3~7), exponential (n = 2) and power function. The generated parameter fitting functions are then used as heat source functions in a 3-D computational fluid dynamics (CFD) solver under natural convection conditions. Generated temperature profiles are analyzed for errors based on experimental discharge tests, conducted at standard room temperature (25°C). Initial experimental results display low deviation between both experimental and CFD temperature plots. As such, the heat generation function formulated could be easier utilized for larger battery applications than other methods available.

Keywords: computational fluid dynamics, curve fitting, lithium-ion battery, voltage drop

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Authors: Maiss Razem

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The construction sector is considered a major consumer of materials that undergoes processes of extraction, processing, transportation, and maintaining when used in buildings. Several metrics have been devised to capture the environmental impact of the materials consumed during construction using lifecycle thinking. Rarely has the materiality of this sector been explored qualitatively and systemically. This paper aims to explore socio-cultural forces that drive the use of certain materials in the Jordanian construction industry, using practice theory as a heuristic method of analysis, more specifically Shove et al. three-element model. By conducting semi-structured interviews with architects, the results unravel contextually embedded routines when determining qualities of three materialities highlighted herein; stone, glass and spatial openness. The study highlights the inadequacy of only using efficiency as a quantitative metric of sustainable materials and argues for the need to link material consumption with socio-economic, cultural, and aesthetic driving forces. The operationalization of practice theory by tracing materials’ lifetimes as they integrate with competencies and meanings captures dynamic engagements through the analyzed routines of actors in the construction practice. This study can offer policymakers better-nuanced representation to green this sector beyond efficiency rhetoric and quantitative metrics.

Keywords: architects' practices, construction materials, Jordan, practice theory

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Authors: Sreejani Barua, P. P. Srivastav

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Formulation of new functional food products for diabetes patients and obsessed people is a challenge for food industries till date. Starch is a certainly happening, ecological, reasonable and profusely obtainable polysaccharide in plant material. In the present scenario, there is a great interest in modifying starch functional properties without destroying its granular structure using different modification techniques. Resistant starch (RS) contains almost zero calories and can control blood glucose level to prevent diabetes. The current study focused on modification of mung bean starch which is a good source of legumes carbohydrate for the production of functional food. Heat moisture treatment (HMT) of mung starch was conducted at moisture content of 10-30%, temperature of 80-120 °C and time of 8-24 h.The content of resistant starch after modification was significantly increased from native starches containing RS 7.6%. The design combinations of HMT had been completed through Central Composite Rotatable Design (CCRD). The effects of HMT process variables on the yield of resistant starch was studied through Rapid Surface Methodology (RSM). The highest increase of resistant starch was found up to 34.39% when treated the native starch with 30% m.c at 120 °C temperature for 24 h.The functional properties of both native and modified mung bean starches showed that there was a reduction in the swelling power and swelling volume of HMT starches. However, the solubility of the HMT starches was higher than that of untreated native starch and also observed change in structural (scanning electron microscopy), X-Ray diffraction (XRD) pattern, blue value and thermal (differential scanning calorimetry) properties. Therefore, replacing native mung bean starch with heat-moisture treated mung bean starch leads to the development of new products with higher resistant starch levels and functional properties.

Keywords: Mung bean starch, heat moisture treatment, functional properties, resistant starch

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Authors: Safa Gharbi, Hayfa Zgaya, Nesrine Zoghlami, Slim Hammadi, Cyril De Barbarin, Laurent Vinatier, Christiane Coupier

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Increasing productivity and quality of service, improving the working comfort and ensuring the efficiency of all processes are important challenges for every warehouse. The order picking is recognized to be the most important and costly activity of all the process in warehouses. This paper presents a new approach using Augmented Reality (AR) in the field of logistics. It aims to create a Head-Up Display (HUD) interface with a Warehouse Management System (WMS), using AR glasses. Integrating AR technology allows the optimization of order picking by reducing time of picking process, increasing the efficiency and delivering quickly. The picker will be able to access immediately to all the information needed for his tasks. All the information is displayed when needed in the field of vision (FOV) of the operator, without any action requested from him. These research works are part of the industrial project RASL (Réalité Augmentée au Service de la Logistique) which gathers two major partners: the LAGIS (Laboratory of Automatics, Computer Engineering and Signal Processing in Lille-France) and Genrix Group, European leader in warehouses logistics, who provided his software for implementation, and his logistics expertise.

Keywords: Augmented Reality (AR), logistics and optimization, Warehouse Management System (WMS), Head-Up Display (HUD)

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Authors: Stanley Dula, Oluwatosini A. Ijabadeniyi

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Biofilm formation is a major source of materials and foodstuffs contamination, contributing to occurrence of pathogenic and spoilage microbes in food processing resulting in food spoilage, transmission of diseases and significant food hygiene and safety issues. This study elucidates biofilm formation of E. coli O157:H7 and L. monocytogenes ATCC 7644 grown under food related environmental stress conditions of varying pH (5.0;7.0; and 8.5) and temperature (15, 25 and 37 ℃). Both strains showed confluent biofilm formation at 25 ℃ and 37 ℃, at pH 8.5 after 5 days. E. coli showed curli fimbriae production at various temperatures, while L. monocytogenes did not show pronounced expression. Swarm, swimming and twitching plate assays were used to determine strain motilities. Characterization of cell hydrophobicity was done using the microbial adhesion to hydrocarbons (MATH) assay using n-hexadecane. Both strains showed hydrophilic characteristics as they fell within a < 20 % interval. FT-IR revealed COOH at 1622 cm-1, and a strong absorption band at 3650 cm-1 – 3200 cm-1 indicating the presence of both -OH and -NH groups. Both strains were hydrophilic and could form biofilm at different combinations of temperature and pH. EPS produced in both species proved to be an acidic hetero-polysaccharide.

Keywords: biofilm, pathogens, hydrophobicity, motility

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Abbasali Abouei Mehrizi, Hao Wang

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The thin film region is so important in heat transfer process due to its low thermal resistance. On the other hand, the dynamic contact angle is crucial boundary condition in numerical simulations. While different modeling contains different assumption of the microscopic contact angle, none of them has experimental evidence for their assumption, and the contact line movement mechanism still remains vague. The experimental investigation in complete wetting is more popular than partial wetting, especially in nanoscale resolution when there is sharp variation in thin film profile in partial wetting. In the present study, an experimental investigation of water film morphology near the triple phase contact line during the condensation is performed. The state-of-the-art tapping-mode atomic force microscopy (TM-AFM) was used to get the high-resolution film profile goes down to 2 nm from the contact line. The droplet was put in saturated chamber. The pristine silicon wafer was used as a smooth substrate. The substrate was heated by PI film heater. So the chamber would be over saturated by droplet evaporation. By turning off the heater, water vapor gradually started condensing on the droplet and the droplet advanced. The advancing speed was less than 20 nm/s. The dominant results indicate that in contrast to nonvolatile liquid, the film profile goes down straightly to the surface till 2 nm from the substrate. However, small bending has been observed below 20 nm, occasionally. So, it can be claimed that for the low condensation rate the microscopic contact angle equals to the optically detectable macroscopic contact angle. This result can be used to simplify the heat transfer modeling in partial wetting. The experimental result of the equality of microscopic and macroscopic contact angle can be used as a solid evidence for using this boundary condition in numerical simulation.

Keywords: advancing, condensation, microscopic contact angle, partial wetting

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Authors: Xavier Lorang, Ahmadali Tahmasebimoradi, Chetra Mang, Sylvain Girard

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The additive manufacturing processes (e.g. selective laser melting) allow us to produce lattice structures which have less weight, higher impact absorption capacity, and better thermal exchange property compared to the classical structures. Unfortunately, geometric imperfections (defects) in the lattice structures are by-products results of the manufacturing process. These imperfections decrease the lifetime and the strength of the lattice structures and alternate their mechanical responses. The objective of the paper is to present a simulation strategy which allows us to take into account the effect of the geometric imperfections on the mechanical response of the lattice structure. In the first part, an identification method of geometric imperfection parameters of the lattice structure based on point clouds is presented. These point clouds are based on tomography measurements. The point clouds are fed into the platform LATANA (LATtice ANAlysis) developed by IRT-SystemX to characterize the geometric imperfections. This is done by projecting the point clouds of each microbeam along the beam axis onto a 2D surface. Then, by fitting an ellipse to the 2D projections of the points, the geometric imperfections are characterized by introducing three parameters of an ellipse; semi-major/minor axes and angle of rotation. With regard to the calculated parameters of the microbeam geometric imperfections, a statistical analysis is carried out to determine a probability density law based on a statistical hypothesis. The microbeam samples are randomly drawn from the density law and are used to generate lattice structures. In the second part, a finite element model for the lattice structure with the simplified geometric imperfections (ellipse parameters) is presented. This numerical model is used to simulate the generated lattice structures. The propagation of the uncertainties of geometric imperfections is shown through the distribution of the computed mechanical responses of the lattice structures.

Keywords: additive manufacturing, finite element model, geometric imperfections, lattice structures, propagation of uncertainty

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Authors: D. Miroud, H. Mokaddem, M. Tata, N. Foucha

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The body of PDC (polycrystalline diamond compact) drill bit can be manufactured from two different materials, steel and tungsten carbide matrix. Commonly the steel body is produced by machining, thermal spraying a bonding layer and hardfacing of Ni-based matrix reinforced with fused eutectic tungsten carbide (WC/W2C). The matrix body bit is manufactured by infiltrating tungsten carbide particles, with a Copper binary or ternary alloy. By erosion-corrosion mechanisms, the PDC drill bits matrix undergoes severe damage, occurring particularly around the PDC inserts and near injection nozzles. In this study, we investigated the possibility to repair the damaged matrix regions by hardfacing technic. Ni-based hardfacing alloy reinforced with fused eutectic tungsten carbide is deposited on infiltrated WC-W-Ni substrate by oxyacetylene welding (OAW). The microstructure at the hardfacing / matrix interface is characterized by SEM- EDS, XRD and micro hardness Hv0.1. The hardfacing conditions greatly affect the dilution phenomenon and the distribution of carbides at the interface, without formation of transition zone. During OAW welding deposition, interdiffusion of atoms occurs: Cu and Sn diffuse from infiltrated matrix substrate into hardfacing and simultaneously Cr and Si alloy elements from hardfacing diffuse towards the substrate. The dilution zone consists of a nickel-rich phase with a heterogeneous distribution of eutectic spherical (Ni-based hardfacing alloy) and irregular (matrix) WC/W2C carbides and a secondary phase rich in Cr-W-Si. Hardfacing conditions cause the dissolution of banding around both spherical and irregular carbides. The micro-hardness of interface is significantly improved by the presence of secondary phase in the inter-dendritic structure.

Keywords: dilution, dissolution, hardfacing, infiltrated matrix, PDC drill bits

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Authors: Olaniyi Awe, Adelana R. Adetunji, Abraham Adeleke

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Mining of alluvial gold ore by artisanal miners has been going on for decades at Itagunmodi, Southwestern Nigeria. In order to optimize the traditional panning gravity separation method commonly used in the area, a mineral particle size analysis study is critical. This study analyzed alluvial gold ore samples collected at identified five different locations in the area with a view to determine the ore particle size distributions. 500g measured of as-received alluvial gold ore sample was introduced into the uppermost sieve of an electrical sieve shaker consisting of sieves arranged in the order of decreasing nominal apertures of 5600μm, 3350μm, 2800μm, 355μm, 250μm, 125μm and 90μm, and operated for 20 minutes. The amount of material retained on each sieve was measured and tabulated for analysis. A screen analysis graph using the Gaudin Schuman method was drawn for each of the screen tests on the alluvial samples. The study showed that the percentages of fine particle size -125+90 μm fraction were 45.00%, 36.00%, 39.60%, 43.00% and 36.80% for the selected samples. These primary ore characteristic results provide reference data for the alluvial gold ore processing method selection, process performance measurement and optimization.

Keywords: alluvial gold ore, sieve shaker, particle size, Gaudin Schumann

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Yousif Mohamed Y. Abdallah

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This is an experimental study deals with detection, measurement and analysis of the periodic physiological organ motion during external beam radiotherapy; to improve the accuracy of the radiation field placement, and to reduce the exposure of healthy tissue during radiation treatments. The importance of this study is to detect the maximum path of the mobile structures during radiotherapy delivery, to define the planning target volume (PTV) and irradiated volume during both inspiration and expiration period and to verify the target volume. In addition to its role to highlight the importance of the application of Intense Guided Radiotherapy (IGRT) methods in the field of radiotherapy. The results showed (body contour was equally (3.17 + 0.23 mm), for left lung displacement reading (2.56 + 0.99 mm) and right lung is (2.42 + 0.77 mm) which the radiation oncologist to take suitable countermeasures in case of significant errors. In addition, the use of the image registration technique for automatic position control is predicted potential motion. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, individualized assessment of tumor mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a single CT scan with a margin of 10 mm is clearly inappropriate.

Keywords: respiratory motion, external beam radiotherapy, image processing, lung

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Authors: Aoqi Zhang, Changgil Lee Lee, Seunghee Park

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A non-contact nondestructive technique using laser-induced ultrasonic wave generation method was applied to visualize corrosion damage at aluminum alloy plate structures. The ultrasonic waves were generated by a Nd:YAG pulse laser, and a galvanometer-based laser scanner was used to scan specific area at a target structure. At the same time, wave responses were measured at a piezoelectric sensor which was attached on the target structure. The visualization of structural damage was achieved by calculating logarithmic values of root mean square (RMS). Damage-sensitive feature was defined as the scattering characteristics of the waves that encounter corrosion damage. The corroded damage was artificially formed by hydrochloric acid. To observe the effect of the location where the corrosion was formed, the both sides of the plate were scanned with same scanning area. Also, the effect on the depth of the corrosion was considered as well as the effect on the size of the corrosion. The results indicated that the damages were successfully visualized for almost cases, whether the damages were formed at the front or back side. However, the damage could not be clearly detected because the depth of the corrosion was shallow. In the future works, it needs to develop signal processing algorithm to more clearly visualize the damage by improving signal-to-noise ratio.

Keywords: non-destructive testing, corrosion, pulsed laser scanning, ultrasonic waves, plate structure

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Authors: Girmaye Abebe, Brook Lemma

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Adsorption of phosphorus (P as PO43-) in filter cake was studied to assess the media's capability in removing phosphorous from wastewaters. The composition of the filter cake that was generated from alum manufacturing process as waste residue has high amount of silicate from the complete silicate analysis of the experiment. Series of batches adsorption experiments were carried out to evaluate parameters that influence the adsorption capacity of PO43-. The factors studied include the effect of contact time, adsorbent dose, thermal pretreatment of the adsorbent, neutralization of the adsorbent, initial PO43- concentration, pH of the solution and effect of co-existing anions. Results showed that adsorption of PO43- is fairly rapid in first 5 min and after that it increases slowly to reach the equilibrium in about 1 h. The treatment efficiency of PO43- was increased with adsorbent extent. About 90% removal efficiency was increased within 1 h at an optimum adsorbent dose of 10 g/L for initial PO43- concentration of 10 mg/L. The amount of PO43- adsorbed increased with increasing initial PO43- concentration. Heat treatment and surface neutralization of the adsorbent did not improve the PO43- removal capacity and efficiency. The percentage of PO43- removal remains nearly constant within the pH range of 3-8. The adsorption data at ambient pH were well fitted to the Langmuir Isotherm and Dubinin–Radushkevick (D–R) isotherm model with a capacity of 25.84 and 157.55 mg/g of the adsorbent respectively. The adsorption kinetic was found to follow a pseudo-second-order rate equation with an average rate constant of 3.76 g.min−1.mg−1. The presence of bicarbonate or carbonate at higher concentrations (10–1000 mg/L) decreased the PO43- removal efficiency slightly while other anions (Cl-, SO42-, and NO3-) have no significant effect within the concentration range tested. The overall result shows that the filter cake is an efficient PO43- removing adsorbent against many parameters.

Keywords: wastewater, filter cake, adsorption capacity, phosphate (PO43-)

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: S. V. Vasilenkov, O. N. Demina

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Chernobyl NPP accident is the biggest in history of nuclear energetic. Bryansk region of Russia was exposed by the most intensive radiation pollution. For that, we made some researches in order to find the methods of soil rehabilitation on territories, polluted by radionuclides with the means of Cesium 137 leaching by watering. For experiments we took the soil from the upper more polluted 10 cm layer of different species. Cesium 137 leaching was made by different methods in washing columns. Washout of Cesium was made by periodical cycles in terms of 4-6 days. In experiments with easy argillaceous soil with start specific radioactivity 4158 bk/kg through 17 cycles the effective reducing was achieved and contained 1512 bk/kg. Besides, results of researches showed, that in the first 6-10 cycles we can see reducing of washing rate but after application of intensificators: ultrasound water processing, aerification, application of fertilizers (KCl), lime, freezing, we can see increasing of Cesium 137 leaching. The experimental investigations in washout of Cesium (Cs) – 137 from the soil were carried out in the field and laboratorial conditions during its freezing and melting. The experiments showed, that washout of Cesium (Cs) – 137 from the soil is rather high after freezing, than non-frozen soil is. And it conforms to washout of Cesium, made under the influence of the intensificaters. This fact allows to recommend chip and easy to construct technically arrangement for regulation of the snow-melt runoff for rehabilitation of the radioactive impoundment.

Keywords: pollution, radiation, Cesium 137 leaching, agriculture

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Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Fernanda Conforto de Oliveira

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The International Monetary Fund (IMF) has a central role in global financial governance as the world’s leading crisis lender. Its practice of conditional lending – conditioning loans on the implementation of economic policy adjustments – is the primary lever by which the institution interacts with and influences the policy choices of member countries and has been a key topic of interest to scholars and public opinion. However, empirical evidence about the economic and (geo)political determinants of IMF lending behavior remains inconclusive, and no model that explains IMF policies has been identified. This research moves beyond panel analysis to focus on financial negotiations for the first IMF programs in Argentina and Brazil in the early post-war period. It seeks to understand why negotiations achieved distinct objectives: Argentinean officials cooperated and complied with IMF policies, whereas their Brazilian counterparts hesitated. Using qualitative and automated text analysis, this paper analyses the hypothesis about whether a differential IMF treatment could help to explain these distinct outcomes. This paper contributes to historical studies on IMF-Latin America relations and the broader literature in international policy economy about IMF policies.

Keywords: international monetary fund, international history, financial history, Latin American economic history, natural language processing, sentiment analysis

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Authors: Ow Tze Weng, Suhaila Isaak, Yusmeeraz Yusof

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The trend of health care screening devices in the world is increasingly towards the favor of portability and wearability, especially in the most common electrocardiogram (ECG) monitoring system. This is because these wearable screening devices are not restricting the patient’s freedom and daily activities. While the demand of low power and low cost biomedical system on chip (SoC) is increasing in exponential way, the front end ECG sensors are still suffering from flicker noise for low frequency cardiac signal acquisition, 50 Hz power line electromagnetic interference, and the large unstable input offsets due to the electrode-skin interface is not attached properly. In this paper, a high performance CMOS amplifier for ECG sensors that suitable for low power wearable cardiac screening is proposed. The amplifier adopts the highly stable folded cascode topology and later being implemented into RC feedback circuit for low frequency DC offset cancellation. By using 0.13 µm CMOS technology from Silterra, the simulation results show that this front end circuit can achieve a very low input referred noise of 1 pV/√Hz and high common mode rejection ratio (CMRR) of 174.05 dB. It also gives voltage gain of 75.45 dB with good power supply rejection ratio (PSSR) of 92.12 dB. The total power consumption is only 3 µW and thus suitable to be implemented with further signal processing and classification back end for low power biomedical SoC.

Keywords: CMOS, ECG, amplifier, low power

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Authors: Ayoub Azizi-Shotorkhoft, Tahereh Mohammadabadi, Hosein Motamedi, Morteza Chaji, Hasan Fazaeli

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This study was conducted to investigate nutritive value of wheat straw processed with termite gut symbiotic bacteria with lignocellulosic-degrading potential including Bacillus licheniformis, Ochrobactrum intermedium and Microbacterium paludicola in vitro. These bacteria were isolated by culturing termite guts contents in different culture media containing different lignin and lignocellulosic materials that had been prepared from water-extracted sawdust and wheat straw. Results showed that incubating wheat straw with all of three isolated bacteria increased (P<0.05) acid-precipitable polymeric lignin (APPL) compared to control, and highest amount of APPL observed following treatment with B. licheniformis. Highest and lowest (P<0.05) in vitro gas production and ruminal organic matter digestibility were obtained when treating wheat straw with B. licheniformis and control, respectively. However, other fermentation parameters such as b (i.e., gas production from the insoluble fermentable fractions at 144h), c (i.e., rate of gas production during incubation), ruminal dry matter digestibility, metabolizable energy, partitioning factor, pH and ammonia nitrogen concentration were similar between experimental treatments (P>0.05). It is concluded that processing wheat straw with isolated bacteria improved its nutritive value as ruminants feed.

Keywords: termite gut bacteria, wheat straw, nutritive value, ruminant

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Authors: Adriana Stefan, Cristina-Elisabeta Pelin, George Pelin, Maria Daniela Stelescu, Elena Manaila

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Elastomeric composites have been known for a long time, but, to our knowledge, space and the aeronautic community has been directing a special attention to them only in the last decade. The required properties of advanced elastomeric materials used in space applications (such as O-rings) are sealing, abrasion, low-temperature flexibility, the long-term compression set properties, impact resistance and low-temperature thermal stability in different environments, such as ionized radiations. Basically, the elastomeric nanocomposites are composed of a rubber matrix and a wide and varied range of nanofillers, added with the aim of improving the physico-mechanical and elasticity modulus properties of the materials as well as their stability in different environments. The paper presents a partial synthesis of the research regarding the use of silicon carbide in nanometric form and/or organophylized montmorillonite as fillers in butyl rubber matrix. The need of composite materials arose from the fact that stand-alone polymers are ineffective in providing all the superior properties required by different applications. These drawbacks can be diminished or even eliminated by incorporating a new range of additives into the organic matrix, fillers that have important roles in modifying properties of various polymers. A composite material can provide superior and unique mechanical and physical properties because it combines the most desirable properties of its constituents while suppressing their least desirable properties. The commercial importance of polymers and the continuous increase of their use results in the continuous demand for improvement in their properties to meet the necessary conditions. To study the performance of the elastomeric nanocomposites were mechanically tested, it will be tested the qualities of tensile at low temperatures and RT and the behavior at the compression at cryogenic to room temperatures and under different environments. The morphology of specimens will be investigated by optical and scanning electronic microscopy.

Keywords: elastomeric nanocomposites, O-rings, space applications, mechanical properties

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Authors: Oladejo Olagoke Peter, Adagunodo T. A., Ogunkoya C. O.

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The research investigated the arrangement of some geological features under Ilesa employing aeromagnetic data. The obtained data was subjected to various data filtering and processing techniques, which are Total Horizontal Derivative (THD), Depth Continuation and Analytical Signal Amplitude using Geosoft Oasis Montaj 6.4.2 software. The Reduced to the Equator –Total Magnetic Intensity (TRE-TMI) outcomes reveal significant magnetic anomalies, with high magnitude (55.1 to 155 nT) predominantly at the Northwest half of the area. Intermediate magnetic susceptibility, ranging between 6.0 to 55.1 nT, dominates the eastern part, separated by depressions and uplifts. The southern part of the area exhibits a magnetic field of low intensity, ranging from -76.6 to 6.0 nT. The lineaments exhibit varying lengths ranging from 2.5 and 16.0 km. Analyzing the Rose Diagram and the analytical signal amplitude indicates structural styles mainly of E-W and NE-SW orientations, particularly evident in the western, SW and NE regions with an amplitude of 0.0318nT/m. The identified faults in the area demonstrate orientations of NNW-SSE, NNE-SSW and WNW-ESE, situated at depths ranging from 500 to 750 m. Considering the divergence magnetic susceptibility, structural style or orientation of the lineaments, identified fault and their depth, these lithological features could serve as a valuable foundation for assessing ground motion, particularly in the presence of sufficient seismic energy.

Keywords: lineament, aeromagnetic, anomaly, fault, magnetic

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Authors: Yanmeng Liu

Abstract:

This article analyzes and compares the linguistic differences between machine translation and manual translation, through a case study of the book Gone with the Wind. As an important carrier of human feeling and thinking, the literature translation poses a huge difficulty for machine translation, and it is supposed to expose distinct translation features apart from manual translation. In order to display linguistic features objectively, tentative uses of computerized and statistical evidence to the systematic investigation of large scale translation corpora by using quantitative methods have been deployed. This study compiles bilingual corpus with four versions of Chinese translations of the book Gone with the Wind, namely, Piao by Chunhai Fan, Piao by Huairen Huang, translations by Google Translation and Baidu Translation. After processing the corpus with the software of Stanford Segmenter, Stanford Postagger, and AntConc, etc., the study analyzes linguistic data and answers the following questions: 1. How does the machine translation differ from manual translation linguistically? 2. Why do these deviances happen? This paper combines translation study with the knowledge of corpus linguistics, and concretes divergent linguistic dimensions in translated text analysis, in order to present linguistic deviances in manual and machine translation. Consequently, this study provides a more accurate and more fine-grained understanding of machine translation products, and it also proposes several suggestions for machine translation development in the future.

Keywords: corpus-based analysis, linguistic deviances, machine translation, statistical evidence

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