Search results for: human machine interface

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Ali Ashtiani, Cesar Carrasco

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Accurate determination of thermo-mechanical responses of jointed concrete pavement slabs is essential to implement an effective mechanistic design. Temperature-induced curling of concrete slabs can produce premature top-down cracking in rigid pavements. Curling of concrete slabs can result from daily temperature variation through the slab thickness. The slab curling can also result from temperature gradients due hot weather construction, drying shrinkage and creep that are permanently built into the slabs. The existence of permanent curling implies that concrete slabs are not flat at zero temperature gradient. In this case, slabs may not be in full contact with the underlying base layer when subjecting to traffic. Built-in curling can be a major factor producing loss of slab support. The magnitude of stresses induced in slabs is influenced by the stiffness of the underlying foundation layers and the contact condition along the slab-foundation interface. An approach for finite element modeling of the effect of loss of slab support due to built-in curling is presented in this paper. A series of parametric studies is carried out for a pavement system loaded with a combination of traffic and thermal loads, considering different built-in curling and different foundation rigidities. The results explain the effect of loss of support in the magnitude of stresses produced in concrete slabs. The results of parametric study can also be used to evaluate whether the governing equations that are used to idealize the behavior of jointed concrete pavements and the effect of loss of support have been accurately selected and implemented in the finite element model.

Keywords: built-in curling, finite element modeling, loss of slab support, rigid pavement

Procedia PDF Downloads 137

Authors: Milan Podlena, Stepan Hysek, Jiri Prochazka, Martin Bohm, Jan Bomba

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Corner joints are the weakest part of windows, where the members are connected together. Since the dimensions of the windows started become bigger, the strength requirements for corner joints started to increase as well. Therefore, the aim of this study was to test the samples of corner joints of wooden windows. Moisture content of test specimens was stabilized in the climate chamber. After conditioning, test specimens were loaded in the laboratory conditions onto an universal testing machine and the failure load was measured. Data was recalculated by using goniometric, bending moment and stiffness equation to the stiffness coefficients and the bending moments were investigated. The results showed difference that was observed for the mortise with tenon joint and the dowel joint. This difference was explained by a varied adhesive bond area, which is related to the dimensions of dowels (diameter and length) as well. The bending moments and stiffness ware (except of type of corner joint) also affected by type of used adhesive, type of dowels and wood species.

Keywords: corner joint, wooden window, bending moment, stiffness

Procedia PDF Downloads 202

Authors: Francisco Miroslav Ulloa-Stanojlovic, Gina Polo, Ricardo Augusto Dias

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In Brazil, there is a high incidence of rabies in herbivores of economic interest (HEI) transmitted by the common vampire bat Desmodus rotundus, the presence of human rabies cases and the huge economic losses in the world's largest cattle industry, it is important to assist the National Program for Control of Rabies in herbivores in Brazil, that aims to reduce the incidence of rabies in HEI populations, mainly through epidemiological surveillance, vaccination of herbivores and control of vampire-bat roosts. Material and Methods: A spatiotemporal retrospective Kulldorff's spatial scan statistic based on a Poisson model and Monte Carlo simulation and an Anselin's Local Moran's I statistic were used to uncover spatial clustering of HEI rabies from 2000 – 2014. Results: Were identify three important clusters with significant year-to-year variation (Figure 1). In 2000, was identified one area of clustering in the North region, specifically in the State of Tocantins. Between the year 2000 and 2004, a cluster centered in the Midwest and Southeast region including the States of Goiás, Minas Gerais, Rio de Janeiro, Espirito Santo and São Paulo was prominent. And finally between 2000 and 2005 was found an important cluster in the North, Midwest and South region. Conclusions: The HEI rabies is endemic in the country, in addition, appears to be significant differences among the States according to their surveillance services, that may be difficulting the control of the disease, also other factors could be influencing in the maintenance of this problem like the lack of information of vampire-bat roosts identification, and limited human resources for realization of field monitoring. A review of the program control by the authorities it’s necessary.

Keywords: Brazil, Desmodus rotundus, herbivores, rabies

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Authors: Safa Boudhaouia, Mohamed Amen Gahbiche, Eliane Giraud, Wacef Ben Salem, Philippe Dal Santo

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Multi-point forming (MPF) and asymmetric incremental forming (ISF) are two flexible processes for sheet metal manufacturing. To take advantages of these two techniques, a hybrid process has been developed: The Multipoint Incremental Forming (MPIF). This process accumulates at once the advantages of each of these last mentioned forming techniques, which makes it a very interesting and particularly an efficient process for single, small, and medium series production. In this paper, an experimental and a numerical investigation of this technique are presented. To highlight the flexibility of this process and its capacity to manufacture standard and complex shapes, several pieces were produced by using MPIF. The forming experiments are performed on a 3-axis CNC machine. Moreover, a numerical model of the MPIF process has been implemented in ABAQUS and the analysis showed a good agreement with experimental results in terms of deformed shape. Furthermore, the use of an elastomeric interpolator allows avoiding classical local defaults like dimples, which are generally caused by the asymmetric contact and also improves the distribution of residual strain. Future works will apply this approach to other alloys used in aeronautic or automotive applications.

Keywords: incremental forming, numerical simulation, MPIF, multipoint forming

Procedia PDF Downloads 338

Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Chun-Liang Wu, Kai-Ping Shaw, Cheng-Ping Yu, Wu-Chien Chien, Hsiao-Ting Chen, Shao-Huang Wu

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Objective: This study analyzed three criminal judicial cases. We applied the patterned injuries of the rider to demonstrate the facts of each accident, reconstruct the scenes, and pursue the truth. Methods: Case analysis, a method that collects evidence and reasons the results in judicial procedures, then the importance of the pattern of injury as evidence will be compared and evaluated. The patterned injuries analysis method is to compare the collision situation between an object and human body injuries to determine whether the characteristics can reproduce the unique pattern of injury. Result: Case 1: Two motorcycles, A and B, head-on collided; rider A dead, and rider B was accused. During the prosecutor’s investigation, the defendant learned that rider A had an 80 mm open wound on his neck. During the court trial, the defendant requested copies of the case file and found out that rider A had a large contusion on his chest wall, and the cause of death was traumatic hemothorax and abdominal wall contusion. The defendant compared all the evidence at the scene and determined that the injury was obviously not caused by the collision of the body or the motorcycle of rider B but that rider was out of control and injured himself when he crossed the double yellow line. In this case, the defendant was innocent in the High Court judgment in April 2022. Case 2: Motorcycles C and D head-on crashed, and rider C died of massive abdominal bleeding. The prosecutor decided that rider C was driving under the influence (DUI), but rider D was negligent and sued rider D. The defendant requested the copies’ file and found the special phenomenon that the front wheel of motorcycle C was turned left. The defendant’s injuries were a left facial bone fracture, a left femur fracture, and other injuries on the left side. The injuries were of human-vehicle separation and human-vehicle collision, which proved that rider C suddenly turned left when the two motorcycles approached, knocked down motorcycle D, and the defendant flew forward. Case 3: Motorcycle E and F’s rear end collided, the front rider E was sentenced to 3 months, and the rear rider F sued rider E for more than 7 million N.T. The defendant found in the copies’ file that the injury of rider F was the left tibial platform fracture, etc., and then proved that rider F made the collision with his left knee, causing motorcycle E to fall out of control. This evidence was accepted by the court and is still on trial. Conclusion: The application of patterned injuries in the reconstruction of a motorcycle accident could discover the truth and provide the basis for judicial justice. The cases and methods could be the reference for the policy of preventing traffic accident casualties.

Keywords: judicial evidence, patterned injuries analysis, accident reconstruction, fatal motorcycle injuries

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Authors: Louay Safi

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The notion of secular society that evolved over the last two centuries was initially intended to free the public sphere from religious imposition, before it assumed the form a comprehensive ideology whose aim is to prevent any overt religious expression from the public space. The negative view of religious expression, and the desire by political elites to purge the public space from all forms of religious expressions were first experienced in the Middle East in the last decades of the twentieth century in relation to Islam, before it manifests itself in the twentieth century Europe. Arab regimes were encouraged by European democracies to marginalize all forms of religious expressions in the public as part of the secularization process that was deemed necessary for modernization and progress. The prohibition of Islamic symbols and outlawing the headscarf was first undertaken to Middle Eastern republics, such as Turkey in 1930s and Syria in 1970s, before it is implemented recently in France. Secularization has been perceived by European powers as the central aspect of social and political liberalization, and was given priority over democratization and human rights, so much so that European elites were willing to entrust the task of nurturing liberal democracy to Arab autocrats and dictators. Not only did the strategy of empowering autocratic regimes to effect liberal democratic culture failed, but it contributed to the rise of Islamist extremism and produced failed states in Syria and Iraq that undermine both national and global peace and stability. The paper adopts the distinction made by John Rawls between political and comprehensive liberalism to argue that the modernization via secularization in Muslim societies is counterproductive and has subverted early successful efforts at democratization and reform in the Middle East. Using case studies that illustrate the role of the secularization strategy in Syria, Iran, and Egypt in undermining democratic and reformist movements in those countries, the paper calls for adopting a different approach rooted in liberal and democratic values rather than cultural practices and lifestyle. The paper shows that Islamic values as articulated by reform movements support a democratic and pluralist political order, and emphasizes the need to legitimize and support social forces that advocate democracy and human rights. Such an alternative strategy allows for internal competition among social groups for popular support, and therefore enhances the chances that those with inclusive and forward-looking political principles and policies would create a democratic and pluralist political order more conducive to meaningful national and global cooperation, and respectful of human dignity.

Keywords: democracy, Islamic values, political liberalism, secularization

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Authors: Alexis Akinyemi, Laurene Houtin

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Measures of employee motivation at work are often based on the theory of self-determined motivation, which implies that human resources departments and managers seek to motivate employees in the most self-determined way possible and use strategies to achieve this goal. In practice, they often tend to assess employee motivation and then adapt management to the most important source of motivation for their employees, for example by financially rewarding an employee who is extrinsically motivated, and by rewarding an intrinsically motivated employee with congratulations and recognition. Thus, the use of motivation measures contradicts theoretical positioning: theory does not provide for the promotion of extrinsically motivated behaviour. In addition, a corpus of social psychology linked to fundamental needs makes it possible to personally address a person’s different sources of motivation (need for cognition, need for uniqueness, need for effects and need for closure). By developing a composite measure of motivation based on these needs, we provide human resources professionals, and in particular occupational psychologists, with a tool that complements the assessment of self-determined motivation, making it possible to precisely address the objective of adapting work not to the self-determination of behaviours, but to the motivational traits of employees. To develop such a model, we gathered the French versions of the cognitive needs scales (need for cognition, need for uniqueness, need for effects, need for closure) and conducted a study with 645 employees of several French companies. On the basis of the data collected, we conducted a confirmatory factor analysis to validate the model, studied the correlations between the various needs, and highlighted the different reference groups that could be used to use these needs as a basis for interviews with employees (career, recruitment, etc.). The results showed a coherent model and the expected links between the different needs. Taken together, these results make it possible to propose a valid and theoretically adjusted tool to managers who wish to adapt their management to their employees’ current motivations, whether or not these motivations are self-determined.

Keywords: motivation, personality, work commitment, cognitive needs

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Authors: Jae-Yong Park, Gwancheol Seo, Young-Ho Kim

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Microvoids, sometimes called Kikendall voids, generally form in the interfaces between Sn-based solders and Cu and degrade the mechanical and electrical properties of the solder joints. The microvoid formation is known as the rapid interdiffusion between Sn and Cu and impurity content in the Cu. Cu electroplating from the acid solutions has been widely used by microelectronic packaging industry for both printed circuit board (PCB) and integrated circuit (IC) applications. The quality of electroplated Cu that can be optimized by the electroplating conditions is critical for the solder joint reliability. In this paper, the influence of electroplating conditions on the microvoid growth in the interfaces between Sn-3.0Ag-0.5Cu (SAC) solder and Cu layer was investigated during isothermal aging. The Cu layers were electroplated by controlling the additive of electroplating bath and current density to induce various microvoid densities. The electroplating bath consisted of sulfate, sulfuric acid, and additives and the current density of 5-15 mA/cm2 for each bath was used. After aging at 180 °C for up to 250 h, typical bi-layer of Cu6Sn5 and Cu3Sn intermetallic compounds (IMCs) was gradually growth at the SAC/Cu interface and microvoid density in the Cu3Sn showed disparities in the electroplating conditions. As the current density increased, the microvoid formation was accelerated in all electroplating baths. The higher current density induced, the higher impurity content in the electroplated Cu. When the polyethylene glycol (PEG) and Cl- ion were mixed in an electroplating bath, the microvoid formation was the highest compared to other electroplating baths. On the other hand, the overall IMC thickness was similar in all samples irrespective of the electroplating conditions. Impurity content in electroplated Cu influenced the microvoid growth, but the IMC growth was not affected by the impurity content. In conclusion, the electroplated conditions are properly optimized to avoid the excessive microvoid formation that results in brittle fracture of solder joint under high strain rate loading.

Keywords: electroplating, additive, microvoid, intermetallic compound

Procedia PDF Downloads 240

Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

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Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

Procedia PDF Downloads 126

Authors: Sabina Żołędowska, Tadeusz Ossowski, Robert Bogdanowicz, Jacek Ryl, Paweł Rostkowski, Michał Kruczkowski, Michał Sobaszek, Zofia Cebula, Grzegorz Skowierzak, Paweł Jakóbczyk, Lilit Hovhannisyan, Paweł Ślepski, Iwona Kaczmarczyk, Mattia Pierpaoli, Bartłomiej Dec, Dawid Nidzworski

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The circular economy of water presents a pressing environmental challenge in our society. Water contains various harmful substances, such as drugs, antibiotics, hormones, and dioxides, which can pose silent threats. Water pollution has severe consequences for aquatic ecosystems. It disrupts the balance of ecosystems by harming aquatic plants, animals, and microorganisms. Water pollution poses significant risks to human health. Exposure to toxic chemicals through contaminated water can have long-term health effects, such as cancer, developmental disorders, and hormonal imbalances. However, effective remediation systems can be implemented to remove these contaminants using electrocatalytic processes, which offer an environmentally friendly alternative to other treatment methods, and one of them is the innovative iCLARE system. The project's primary focus revolves around a few main topics: Reactor design and construction, selection of a specific type of reticulated vitreous carbon foams (RVC), analytical studies of harmful contaminants parameters and AI implementation. This high-performance electrochemical reactor will be build based on a novel type of electrode material. The proposed approach utilizes the application of reticulated vitreous carbon foams (RVC) with deposited modified metal oxides (MMO) and diamond thin films. The following setup is characterized by high surface area development and satisfactory mechanical and electrochemical properties, designed for high electrocatalytic process efficiency. The consortium validated electrode modification methods that are the base of the iCLARE product and established the procedures for the detection of chemicals detection: - deposition of metal oxides WO3 and V2O5-deposition of boron-doped diamond/nanowalls structures by CVD process. The chosen electrodes (porous Ferroterm electrodes) were stress tested for various parameters that might occur inside the iCLARE machine–corosis, the long-term structure of the electrode surface during electrochemical processes, and energetic efficacy using cyclic polarization and electrochemical impedance spectroscopy (before and after electrolysis) and dynamic electrochemical impedance spectroscopy (DEIS). This tool allows real-time monitoring of the changes at the electrode/electrolyte interphase. On the other hand, the toxicity of iCLARE chemicals and products of electrolysis are evaluated before and after the treatment using MARA examination (IBMM) and HPLC-MS-MS (NILU), giving us information about the harmfulness of using electrode material and the efficiency of iClare system in the disposal of pollutants. Implementation of data into the system that uses artificial intelligence and the possibility of practical application is in progress (SensDx).

Keywords: waste water treatement, RVC, electrocatalysis, paracetamol

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Authors: Patricia Shirley Almeida Prado, Liz Brito, Selma Paixão Argollo, Gracie Moreira, Leticia Matos Sobrinho

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Diffuse idiopathic skeletal hyperostosis (DISH) is a degenerative bone disease also known as Forestier´s disease and ankylosing hyperostosis of the spine is characterized by a tendency toward ossification of half the anterior longitudinal spinal ligament without intervertebral disc disease. DISH is not considered to be osteoarthritis, although the two conditions commonly occur together. Diagnostic criteria include fusion of at least four vertebrae by bony bridges arising from the anterolateral aspect of the vertebral bodies. These vertebral bodies have a 'dripping candle wax' appearance, also can be seen periosteal new bone formation on the anterior surface of the vertebral bodies and there is no ankylosis at zygoapophyseal facet joint. Clinically, patients with DISH tend to be asymptomatic some patients mention moderate pain and stiffness in upper back. This disease is more common in man, uncommon in patients younger than 50 years and rare in patients under 40 years old. In modern populations, DISH is found in association with obesity, (type II) diabetes; abnormal vitamin A metabolism and also associated with higher levels of serum uric acid. There is also some association between the increase of risk of stroke or other cerebrovascular disease. The DISH condition can be confused with Heterotopic Ossification, what is the bone formation in the soft tissues as the result of trauma, wounding, surgery, burnings, prolonged immobility and some central nervous system disorder. All these conditions have been described extensively as myositis ossificans which can be confused with the fibrodysplasia (myositis) ossificans progressive. As in the DISH symptomatology it can be asymptomatic or extensive enough to impair joint function. A third confusion osteoarthritis disease that can bring confusion are the enthesopathies that occur in the entire skeleton being common on the ischial tuberosities, iliac crests, patellae, and calcaneus. Ankylosis of the sacroiliac joint by bony bridges may also be found. CASE 1: this case is skeletal remains presenting skull, some vertebrae and scapulae. This case remains unidentified and due to lack of bone remains. Sex, age and ancestry profile was compromised, however the DISH pathognomonic findings and diagnostic helps to estimate sex and age characteristics. Moreover to presenting DISH these skeletal remains also showed some bone alterations and non-metrics as fusion of the first vertebrae with occipital bone, maxillae and palatine torus and scapular foramen on the right scapulae. CASE 2: this skeleton remains shows an extensive bone heterotopic ossification on the great trochanter area of left femur, right fibula showed a healed fracture in its body however in its inteosseous crest there is an extensive bone growth, also in the Ilium at the region of inferior gluteal line can be observed some pronounced bone growth and the skull presented a pronounced mandibular, maxillary and palatine torus. Despite all these pronounced heterotopic ossification the whole skeleton presents moderate bone overgrowth that is not linked with aging, since the skeleton belongs to a young unidentified individual. The appropriate osteopathological diagnosis support the human identification process through medical reports and also assist with epidemiological data that can strengthen vulnerable anthropological estimates.

Keywords: bone disease, DISH, human identification, human remains

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Authors: Sandhya Rao

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Kevin Lynch’s Theory on Imeageability, let on explore a city in terms of five elements, Nodes, Paths, Edges, landmarks and Districts. What happens when we try to record the same data in an Indian context? What happens when we apply the same theory of Imageability to a complex shifting urban pattern of the Indian cities and how can we as Urban Designers demonstrate our role in the image building ordeal of these cities? The organizational patterns formed through mental images, of an Indian city is often diverse and intangible. It is also multi layered and temporary in terms of the spirit of the place. The pattern of images formed is loaded with associative meaning and intrinsically linked with the history and socio-cultural dominance of the place. The embedded memory of a place in one’s mind often plays an even more important role while formulating these images. Thus while deriving an image of a city one is often confused or finds the result chaotic. The images formed due to its complexity are further difficult to represent using a single medium. Under such a scenario it’s difficult to derive an output of an image constructed as well as make design interventions to enhance the legibility of a place. However, there can be a combination of tools and methods that allows one to record the key elements of a place through time, space and one’s user interface with the place. There has to be a clear understanding of the participant groups of a place and their time and period of engagement with the place as well. How we can translate the result obtained into a design intervention at the end, is the main of the research. Could a multi-faceted cognitive mapping be an answer to this or could it be a very transient mapping method which can change over time, place and person. How does the context influence the process of image building in one’s mind? These are the key questions that this research will aim to answer.

Keywords: imageability, organizational patterns, legibility, cognitive mapping

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Authors: Joseph Chen, N. Hundal

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Conventional machining is a form of subtractive manufacturing, in which a collection of material-working processes utilizing power-driven machine tools are used to remove undesired material to achieve a desired geometry. This paper presents an approach for comparison between turning center and vertical machining center by optimization of cutting parameters at cylindrical workpieces leading to minimum surface roughness by using taguchi methodology. Aluminum alloy was taken to conduct experiments due to its unique high strength-weight ratio that is maintained at elevated temperatures and their exceptional corrosion resistance. During testing, the effects of the cutting parameters on the surface roughness were investigated. Additionally, by using taguchi methodology for each of the cutting parameters (spindle speed, depth of cut, insert diameter, and feed rate) minimum surface roughness for the process of turn-milling was determined according to the cutting parameters. A confirmation experiment demonstrates the effectiveness of taguchi method.

Keywords: surface roughness, Taguchi parameter design, turning center, turn-milling operations, vertical machining center

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Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

Procedia PDF Downloads 52

Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson, and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence-based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation-prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: aggregation, amyloids, thermophilic proteins, amino acid residues, machine learning techniques

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Authors: Sedat Yayla, Mehmet Oruc, Shakhwan Yaseen

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Cavitation phenomena might rigorously impair machine parts such as pumps, propellers and impellers or devices as the pressure in the fluid declines under the liquid's saturation pressure. To evaluate the influence of cavitation, in this research two-dimensional computational fluid dynamics (CFD) venturi models with variety of inlet pressure values, throat lengths and vapor fluid contents were applied. In this research three different vapor contents (0%, 5% 10%), four inlet pressures (2, 4, 6, 8 and 10 atm) and two venturi models were employed at different throat lengths ( 5, 10, 15 and 20 mm) for discovering the impact of each parameter on the cavitation number. It is uncovered that there is a positive correlation between pressure inlet and vapor fluid content and cavitation number. Furthermore, it is unveiled that velocity remains almost constant at the inlet pressures of 6, 8,10atm, nevertheless increasing the length of throat results in the substantial escalation in the velocity of the throat at inlet pressures of 2 and 4 atm. Furthermore, velocity and cavitation number were negatively correlated. The results of the cavitation number varied between 0.092 and 0.495 depending upon the velocity values of the throat.

Keywords: cavitation number, computational fluid dynamics, mixture of fluid, two-phase flow, velocity of throat

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Authors: Masoud Safdari, Jacob Fish

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Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

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Authors: Pradeep Singh, Shrish Verma

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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. The earlier we predict the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven data sets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.

Keywords: software metrics, fault prediction, cross project, within project.

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Authors: Ozoemelam Ikechukwu Lazarus, Nizamuddin B. Zainuddin, Abdul Kafi

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Numerous studies have been carried out on Green Logistics Management Practices (GLMPs) across the globe. The study on the practices and performance of green chain practices in Africa in particular has not gained enough scholarly attention. Again, the majority of supply chain sustainability research being conducted focus on environmental sustainability. Logistics has been a major cause of supply chain resource waste and environmental damage. Many sectors of the economy that engage in logistical operations significantly rely on vehicles, which emit pollutants into the environment. Due to urbanization and industrialization, the logistical operations of manufacturing companies represent a serious hazard to the society and human life, making the sector one of the fastest expanding in the world today. Logistics companies are faced with numerous difficulties when attempting to implement logistics practices along their supply chains. In Nigeria, manufacturing companies aspire to implement reverse logistics in response to stakeholders’ requirements to reduce negative environmental consequences. However, implementing this is impeded by a criteria framework, and necessitates the careful analysis of how such criteria interact with each other in the presence of uncertainty. This study integrates most of the green logistics management practices (GLMPs) into the Nigerian firms to improve generalizability, and credibility. It examines the effect of Green Logistics Management Practices on environmental performance, social performance, market performance, and financial performance in the logistics industries. It seeks to identify the critical success factors in order to develop a model that incorporates different factors from the perspectives of the technology, organization, human and environment to inform the adoption and use of technologies for logistics supply chain social sustainability in Nigeria. It uses exploratory research approach to collect and analyse the data.

Keywords: logistics, managemernt, suatainability, environment, operations

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Authors: Guram Adamashvili

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Surface plasmon polariton is a surface optical wave which undergoes a strong enhancement and spatial confinement of its wave amplitude near an interface of two-dimensional layered structures. Phosphorene (single-layer black phosphorus) and other two-dimensional anisotropic phosphorene-like materials are recognized as promising materials for potential future applications of surface plasmon polariton. A theory of an optical breather of self-induced transparency for surface plasmon polariton propagating in monolayer or few-layer phosphorene is developed. A theory of an optical soliton of self-induced transparency for surface plasmon polariton propagating in monolayer or few-layer phosphorene have been investigated earlier Starting from the optical nonlinear wave equation for surface TM-modes interacting with a two-dimensional layer of atomic systems or semiconductor quantum dots and a phosphorene monolayer (or other two-dimensional anisotropic material), we have obtained the evolution equations for the electric field of the breather. In this case, one finds that the evolution of these pulses become described by the damped Bloch-Maxwell equations. For surface plasmon polariton fields, breathers are found to occur. Explicit relations of the dependence of breathers on the local media, phosphorene anisotropic conductivity, transition layer properties and transverse structures of the SPP, are obtained and will be given. It is shown that the phosphorene conductivity reduces exponentially the amplitude of the surface breather of SIT in the process of propagation. The direction of propagation corresponding to the maximum and minimum damping of the amplitude are assigned along the armchair and zigzag directions of black phosphorus nano-film, respectively. The most rapid damping of the intensity occurs when the polarization of breather is along the armchair direction.

Keywords: breathers, nonlinear waves, solitons, surface plasmon polaritons

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Authors: Viviana Manzulli, Luigina Serrecchia, Adelia Donatiello, Valeria Rondinone, Sabine Zange, Alina Tscherne, Antonio Parisi, Antonio Fasanella

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Anthrax is a zoonotic disease that affects a wide range of animal species (primarily ruminant herbivores), and can be transmitted to humans through consumption or handling of contaminated animal products. The etiological agent B.anthracis is able to survive in unfavorable environmental conditions by forming endospore which remain viable in the soil for many decades. Furthermore, B.anthracis is considered as one of the most feared agents to be potentially misused as a biological weapon and the importance of the disease and its treatment in humans has been underscored before the bioterrorism events in the United States in 2001. Due to the often fatal outcome of human cases, antimicrobial susceptibility testing plays especially in the management of anthrax infections an important role. In Italy, animal anthrax is endemic (predominantly found in the southern regions and on islands) and is characterized by sporadic outbreaks occurring mainly during summer. Between 2012 and 2017 single human cases of cutaneous anthrax occurred. In this study, 90 diverse strains of B.anthracis, isolated in Italy from 2001 to 2017, were screened to their susceptibility to sixteen clinically relevant antimicrobial agents by using the broth microdilution method. B.anthracis strains selected for this study belong to the strain collection stored at the Anthrax Reference Institute of Italy located inside the Istituto Zooprofilattico Sperimentale of Puglia and Basilicata. The strains were isolated at different time points and places from various matrices (human, animal and environmental). All strains are a representative of over fifty distinct MLVA 31 genotypes. The following antibiotics were used for testing: gentamicin, ceftriaxone, streptomycin, penicillin G, clindamycin, chloramphenicol, vancomycin, linezolid, cefotaxime, tetracycline, erythromycin, rifampin, amoxicillin, ciprofloxacin, doxycycline and trimethoprim. A standard concentration of each antibiotic was prepared in a specific diluent, which were then twofold serial diluted. Therefore, each wells contained: bacterial suspension of 1–5x104 CFU/mL in Mueller-Hinton Broth (MHB), the antibiotic to be tested at known concentration and resazurin, an indicator of cell growth. After incubation overnight at 37°C, the wells were screened for color changes caused by the resazurin: a change from purple to pink/colorless indicated cell growth. The lowest concentration of antibiotic that prevented growth represented the minimal inhibitory concentration (MIC). This study suggests that B.anthracis remains susceptible in vitro to many antibiotics, in addition to doxycycline (MICs ≤ 0,03 µg/ml), ciprofloxacin (MICs ≤ 0,03 µg/ml) and penicillin G (MICs ≤ 0,06 µg/ml), recommend by CDC for the treatment of human cases and for prophylactic use after exposure to the spores. In fact, the good activity of gentamicin (MICs ≤ 0,25 µg/ml), streptomycin (MICs ≤ 1 µg/ml), clindamycin (MICs ≤ 0,125 µg/ml), chloramphenicol(MICs ≤ 4 µg/ml), vancomycin (MICs ≤ 2 µg/ml), linezolid (MICs ≤ 2 µg/ml), tetracycline (MICs ≤ 0,125 µg/ml), erythromycin (MICs ≤ 0,25 µg/ml), rifampin (MICs ≤ 0,25 µg/ml), amoxicillin (MICs ≤ 0,06 µg/ml), towards all tested B.anthracis strains demonstrates an appropriate alternative choice for prophylaxis and/or treatment. All tested B.anthracis strains showed intermediate susceptibility to the cephalosporins (MICs ≥ 16 µg/ml) and resistance to trimethoprim (MICs ≥ 128 µg/ml).

Keywords: Bacillus anthracis, antibiotic susceptibility, treatment, minimum inhibitory concentration

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Authors: D. Deepak, N. Yagnesh Sharma

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Abrasive Water Jet (AWJ) machining is a relatively new nontraditional machine tool used in machining of fiber reinforced composite. The quality of machined surface depends on jet exit kinetic energy which depends on various operating and material parameters. In the present work the effect abrasive parameters such as its size, concentration and type on jet kinetic energy is investigated using computational fluid dynamics (CFD). In addition, the effect of these parameters on wall shear stress developed inside the nozzle is also investigated. It is found that for the same operating parameters, increase in the abrasive volume fraction (concentration) results in significant decrease in the wall shear stress as well as the jet exit kinetic energy. Increase in the abrasive particle size results in marginal decrease in the jet exit kinetic energy. Numerical simulation also indicates that garnet abrasives produce better jet exit kinetic energy than aluminium oxide and silicon carbide.

Keywords: abrasive water jet machining, jet kinetic energy, operating pressure, wall shear stress, Garnet abrasive

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Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

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This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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Authors: Abbas Pourreza

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MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.

Keywords: breast cancer, HER2 positive, miRNA, TNBC

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Jing Jin

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The incorporation of artificial intelligence (AI) and machine learning (ML) in aircraft manufacturing and aerospace supply chains leads to the generation of a substantial amount of data among various tiers of suppliers and OEMs. Identifying the high-quality information challenges decision-makers. The application of AI/ML models necessitates access to 'high-quality' information to yield desired outputs. However, the process of information sharing introduces complexities, including distortion through various communication channels and biases introduced by both human and AI entities. This phenomenon significantly influences the quality of information, impacting decision-makers engaged in configuring supply chain systems. Traditionally, distorted information is categorized as 'low-quality'; however, this study challenges this perception, positing that distorted information, contributing to stakeholder goals, can be deemed high-quality within supply chains. The main aim of this study is to identify and evaluate the dimensions of information quality crucial to the UK aerospace supply chain. Guided by a central research question, "What information quality dimensions are considered when defining information quality in the UK aerospace supply chain?" the study delves into the intricate dynamics of information quality in the aerospace industry. Additionally, the research explores the nuanced impact of information distortion on stakeholders' decision-making processes, addressing the question, "How does the information distortion phenomenon influence stakeholders’ decisions regarding information quality in the UK aerospace supply chain system?" This study employs deductive methodologies rooted in positivism, utilizing a cross-sectional approach and a mono-quantitative method -a questionnaire survey. Data is systematically collected from diverse tiers of supply chain stakeholders, encompassing end-customers, OEMs, Tier 0.5, Tier 1, and Tier 2 suppliers. Employing robust statistical data analysis methods, including mean values, mode values, standard deviation, one-way analysis of variance (ANOVA), and Pearson’s correlation analysis, the study interprets and extracts meaningful insights from the gathered data. Initial analyses challenge conventional notions, revealing that information distortion positively influences the definition of information quality, disrupting the established perception of distorted information as inherently low-quality. Further exploration through correlation analysis unveils the varied perspectives of different stakeholder tiers on the impact of information distortion on specific information quality dimensions. For instance, Tier 2 suppliers demonstrate strong positive correlations between information distortion and dimensions like access security, accuracy, interpretability, and timeliness. Conversely, Tier 1 suppliers emphasise strong negative influences on the security of accessing information and negligible impact on information timeliness. Tier 0.5 suppliers showcase very strong positive correlations with dimensions like conciseness and completeness, while OEMs exhibit limited interest in considering information distortion within the supply chain. Introducing social network analysis (SNA) provides a structural understanding of the relationships between information distortion and quality dimensions. The moderately high density of ‘information distortion-by-information quality’ underscores the interconnected nature of these factors. In conclusion, this study offers a nuanced exploration of information quality dimensions in the UK aerospace supply chain, highlighting the significance of individual perspectives across different tiers. The positive influence of information distortion challenges prevailing assumptions, fostering a more nuanced understanding of information's role in the Industry 4.0 landscape.

Keywords: information distortion, information quality, supply chain configuration, UK aerospace industry

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Authors: Pradeep Lamichhane

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Plasma-assisted nitrogen fixation is a process by which atomic nitrogen generated by plasma is converted into ammonia (NH₃) or related nitrogenous compounds. Nitrogen fixation is essential to plant because fixed inorganic nitrogen compounds are required to them for the biosynthesis of all nitrogen-containing organic compounds, such as amino acids and proteins, nucleoside triphosphates and nucleic acid. Most of our atmosphere is composed of nitrogen; however, the plant cannot absorb it directly from the air ambient. As a portion of the nitrogen cycle, nitrogen fixation fundamental for agriculture and the manufacture of fertilizer. In this study, plasma-assisted nitrogen fixation was performed by exposing a non-thermal atmospheric pressure nitrogen plasma generated a sinusoidal power supply (with an applied voltage of 10 kV and frequency of 33 kHz) on a water surface. Besides this, UV excitation of water molecules at the water interface was also done in order to disassociate water. Hydrogen and hydroxyl radical obtained from this UV photolysis electrochemically combine with nitrogen atom obtained from plasma. As a result of this, nitrogen fixation on plasma-activated water (PAW) significantly enhanced. The amount of nitrogen-based products like NOₓ and ammonia (NH₃) synthesized by this combined process of UV and plasma are 1.4 and 2.8 times higher than those obtained by plasma alone. In every 48 hours, 20 ml of plasma-activated water (pH≈3.15) for 10 minutes with moderate concentrations of NOₓ, NH₃ and hydrogen peroxide (H₂O₂) was irrigated on each corn plant (Zea Mays). It was found that the PAW has shown a significant impact on seeds germination rate and improved seedling growth. The result obtained from this experiment suggested that crop yield could increase in a short duration. In the future, this experiment could open boundless opportunities in plasma agriculture to mobilize nitrogen because nitrite, nitrate, and ammonia are more suitable for plant uptake.

Keywords: plasma-assisted nitrogen fixation, nitrogen plasma, UV excitation of water, ammonia synthesis

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