Search results for: network and energy consumption

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 178

Authors: Deniz Bozoglu, Deniz Deger, Kemal Ulutas, Sahin Yakut

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In recent years, silica aerogels have attracted great attention due to their outstanding properties, and their wide variety of potential applications such as microelectronics, nuclear and high-energy physics, optics and acoustics, superconductivity, space-physics. Hydrophobic silica aerogels were successfully synthesized in one-step by surface modification at ambient pressure. FT-IR result confirmed that Si-OH groups were successfully converted into hydrophobic and non-polar Si-CH3 groups by surface modification using trimethylchloro silane (TMCS) as co-precursor. Using Alpha-A High-Resolution Dielectric, Conductivity and Impedance Analyzer, AC conductivity of samples were examined at temperature range 293-423 K and measured over frequency range between 1-106 Hz. The characteristic relaxation time decreases with increasing temperature. The AC conductivity follows σ_AC (ω)=σ_t-σ_DC=Aω^s relation at frequencies higher than 10 Hz, and the dominant conduction mechanism is found to obey the Correlated Barrier Hopping (CBH) mechanism. At frequencies lower than 10 Hz, the electrical conduction is found to be in accordance with DC conduction mechanism. The activation energies obtained from AC conductivity results and it was observed two relaxation regions.

Keywords: aerogel, synthesis, dielectric constant, dielectric loss, relaxation time

Procedia PDF Downloads 163

Authors: Niladri Sekhar Barma, Satish Dhandole

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Damage identification in the context of safety, nowadays, has become a fundamental research interest area in the field of mechanical, civil, and aerospace engineering structures. The following research is aimed to identify damage in a mechanical beam structure and quantify the severity or extent of damage in terms of loss of stiffness, and obtain an updated analytical Finite Element (FE) model. An FE model is used for analysis, and the location of damage for single and multiple damage cases is identified numerically using the modal strain energy method and mode shape curvature method. Experimental data has been acquired with the help of an accelerometer. Fast Fourier Transform (FFT) algorithm is applied to the measured signal, and subsequently, post-processing is done in MEscopeVes software. The two sets of data, the numerical FE model and experimental results, are compared to locate the damage accurately. The extent of the damage is identified via modal frequencies using a mixed numerical-experimental technique. Mode shape comparison is performed by Modal Assurance Criteria (MAC). The analytical FE model is adjusted by the direct method of model updating. The same study has been extended to some real-life structures such as plate and GARTEUR structures.

Keywords: damage identification, damage quantification, damage detection using modal analysis, structural damage identification

Procedia PDF Downloads 78

Authors: Marike Venter de Villiers, Jessica Ramoshaba

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In recent years, the fashion industry has been associated with the exploitation of both people and resources. This is largely due to the emergence of the fast fashion concept, which entails rapid and continual style changes where clothes quickly lose their appeal, become out-of-fashion, and are then disposed of. This cycle often entails appalling working conditions in sweatshops with low wages, child labor, and a significant amount of textile waste that ends up in landfills. Although the awareness of the negative implications of ‘mindless fashion production and consumption’ is growing, fast fashion remains to be a popular choice among the youth. This is especially prevalent in South Africa, a poverty-stricken country where a vast number of young adults are unemployed and living in poverty. Despite being in poverty, the celebrity conscious culture and fashion products frequently portrayed on the growing intrusive social media platforms in South Africa pressurizes the consumers to purchase fashion and luxury products. Young adults are therefore more vulnerable to the temptation to purchase fast fashion products. A possible solution to the detrimental effects that the fast fashion industry has on the environment is the revival of the secondhand clothing trend. Although the popularity of secondhand clothing has gained momentum among selected consumer segments, the adoption rate of such remains slow. The main purpose of this study was to explore consumers’ perceptions of the secondhand clothing trend and to gain insight into factors that inhibit the adoption of secondhand clothing. This study also aimed to investigate whether consumers are aware of the negative implications of the fast fashion industry and their likelihood to shift their clothing purchases to that of secondhand clothing. By means of a quantitative study, fifty young females were asked to complete a semi-structured questionnaire. The researcher approached females between the ages of 18 and 35 in a face-to-face setting. The results indicated that although they had an awareness of the negative consequences of fast fashion, they lacked detailed insight into the pertinent effects of fast fashion on the environment. Further, a number of factors inhibit their decision to buy from secondhand stores: firstly, the accessibility to the latest trends was not always available in secondhand stores; secondly, the convenience of shopping from a chain store outweighs the inconvenience of searching for and finding a secondhand store; and lastly, they perceived secondhand clothing to pose a hygiene risk. The findings of this study provide fashion marketers, and secondhand clothing stores, with insight into how they can incorporate the secondhand clothing trend into their strategies and marketing campaigns in an attempt to make the fashion industry more sustainable.

Keywords: eco-friendly fashion, fast fashion, secondhand clothing, eco-friendly fashion

Procedia PDF Downloads 106

Authors: M. Ntšolo, D. Kalumba, N. Lefu, G. Letlatsa

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Rock mass damage due to shear tectonic activity has been investigated largely in geoscience where fluid transport is of major interest. However, little has been studied on the effect of shear zones on rock mass behavior and its impact on stability of rock slopes. At Letšeng Diamonds open pit mine in Lesotho, the shear zone composed of sheared kimberlite material, calcite and altered basalt is forming part of the haul ramp into the main pit cut 3. The alarming rate at which the shear zone is deteriorating has triggered concerns about both local and global stability of pit the walls. This study presents the numerical modelling of the open pit slope affected by shear zone at Letšeng Diamond Mine (LDM). Analysis of the slope involved development of the slope model by using a two-dimensional finite element code RS2. Interfaces between shear zone and host rock were represented by special joint elements incorporated in the finite element code. The analysis of structural geological mapping data provided a good platform to understand the joint network. Major joints including shear zone were incorporated into the model for simulation. This approach proved successful by demonstrating that continuum modelling can be used to evaluate evolution of stresses, strain, plastic yielding and failure mechanisms that are consistent with field observations. Structural control due to geological shear zone structure proved to be important in its location, size and orientation. Furthermore, the model analyzed slope deformation and sliding possibility along shear zone interfaces. This type of approach can predict shear zone deformation and failure mechanism, hence mitigation strategies can be deployed for safety of human lives and property within mine pits.

Keywords: numerical modeling, open pit mine, shear zone, slope stability

Procedia PDF Downloads 265

Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Dina H. Gabr, Mona A. El Bannan

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With growing worldwide concern for global warming, green finance has become the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the United Nations Sustainable Development Goals, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits. This paper provides a comprehensive review of the concepts and definitions of green finance and the importance of 'green' impact investments today. The core challenge in combating climate change is reducing and controlling Greenhouse gas emissions; therefore, this study explores the solutions green finance provides putting emphasis on the use of renewable energy, which is necessary for enhancing the transition to the green economy. With increasing attention to the concept of green finance, multiple forms of green investments and financial tools have come to fruition; the most prominent are green bonds. The rise of green bonds, a debt market to finance climate solutions, provide a promising mechanism for sustainable finance. Following the review, this paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.

Keywords: climate change, GHG emissions, green bonds, green finance, sustainable finance

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Authors: Susanna Vanhamäki, Gabor Schneider, Kati Manskinen

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‘Bioeconomy’ is a complex concept that cuts across many sectors and covers several policy areas. To achieve an overall understanding and support a successful bioeconomy, a cross-sectorial approach is necessary. In practice, due to the concept’s wide scope and varying international approaches, fully understanding bioeconomy is challenging on policy level. This paper provides a background of the topic through an analysis of bioeconomy strategies in the Baltic Sea region. Expert interviews and a small survey were conducted to discover the current and intended focuses of these countries’ bioeconomy sectors. The research shows that supporting sustainability is one of the keys in developing the future bioeconomy. The results highlighted that the bioeconomy has to be sustainable and based on circular economy principles. Currently, traditional bioeconomy sectors like food, wood, fish & waters as well as fuel & energy, which are in the core of national bioeconomy strategies, are best known and are considered more relevant than other bioeconomy industries. However, there is increasing potential for novel sectors, such as textiles and pharmaceuticals. The present research indicates that the opportunities presented by these bioeconomy sectors should be recognised and promoted. Education, research and innovation can play key roles in developing transformative and sustainable improvements in primary production and renewable resources. Furthermore, cooperation between businesses and educators is important.

Keywords: bioeconomy, circular economy, policy, strategy

Procedia PDF Downloads 145

Authors: Nikica Mihaljević

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Published in 2023, "Tre ciotole. Rituali per un anno di crisi" is a collection of short stories completely disconnected from one another in regard to topics and the representation of characters. However, these short stories complete and somehow continue each other in a particular way. The book happens to be Murgia's last book, as the author died a few months later after the book's publication and it appears as a kind of summary of all her previous literary works. Namely, in her previous publications, Murgia already stressed certain characters' particularities, such as solitude and alienation from others, which are at the center of attention in this literary work, too. What all the stories present in "Tre ciotole" have in common is the dealing with characters' identity and self-awareness through the challenges they confront and the way the characters live their emotions in relation to the surrounding space. Although the challenges seem similar, the spatial element around the characters is different, but it confirms each time that characters' emotions, and, consequently, their self-awareness, can be formed and built only through their connection and relation to the surrounding space. In that way, the reader creates an imaginary network of complex relations among characters in all the short stories, which gives him/her the opportunity to search for a way to break out of the usual patterns that tend to be repeated while characters focus on building self-awareness. The aim of the paper is to determine and analyze the role of spatial elements in the creation of characters' emotions and in the process of self-awareness. As the spatial element changes or gets transformed and/or substituted, in the same way, we notice the arise of the unconscious desire for self-harm in the characters, which damages their self-awareness. Namely, the characters face a crisis that they cannot control by inventing other types of crises that can be controlled. That happens to be their way of acting in order to find the way out of the identity crisis. Consequently, we expect that the results of the analysis point out the similarities in the short stories in characters' depiction as well as to show the extent to which the characters' identities depend on the surrounding space in each short story. In this way, the results will highlight the importance of spatial elements in characters' identity formation in Michela Murgia's short stories and also summarize the importance of the whole Murgia's literary opus.

Keywords: Italian literature, short stories, environment, spatial element, emotions, characters

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Authors: Nicolas Giraudo, Peter Thissen

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In this paper we bring up new aspects of the metal proton exchange reaction (MPER, also called early stage hydration): (1) its dependence of the number of protons consumed by the preferential exchanged cations on the pH value applied at the water/wollastonite interface and (2) strong anisotropic characteristics detected in atomic force microscopy (AFM) and low energy ion scattering spectroscopy measurements (LEIS). First we apply density functional theory (DFT) calculations to compare the kinetics of the reaction on different wollastonite surfaces, and combine it with ab initio thermodynamics to set up a model describing (1) the release of Ca in exchange with H coming from the water/wollastonite interface, (2) the dependence of the MPER on the chemical potential of protons. In the second part of the paper we carried out in-situ AFM and inductive coupled plasma atomic emission spectroscopy (ICP-OES) measurements in order to evaluate the predicted values. While a good agreement is found in the basic and neutral regime (pH values from 14-4), an increasing mismatch appears in the acidic regime (pH value lower 4). This is finally explained by non-equilibrium etching, dominating over the MPER in the very acidic regime.

Keywords: anisotropy, calcium silicate, cement, density functional theory, hydration

Procedia PDF Downloads 254

Authors: Shruti Sakarkar, Jega Jegatheesan, Srinivasan Madapusi

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Photocatalytic membranes have shown great potential for the removal of an organic and inorganic pollutant from wastewater as it combines the degradation and antibacterial properties from photocatalysis and physical separation by the membrane in a single unit. Incorporation of the semiconductor in membrane structure results in enhancing the performance and the properties of the membrane. In this study porous ultrafiltration polyvinylidene fluoride (PVDF) membranes with entrapped TiO₂ nanoparticle were prepared by phase inversion method and further used for the degradation of reactive orange 16 (RO16). Prepared photocatalytic membranes were characterized by the scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), contact angle, and atomic force microscope (AFM). The addition of TiO₂ nanopartparticles improves the strength and thermal stability of the membrane. In particular hydrophilicity and permeability increases with the increase of TiO₂ nanoparticles into the membrane. The photocatalytic membrane achieves 80-85% degrdation of RO16. The impact of different parameters such as pH, concentration of photocatalyst, dye concentration and effect of H₂O₂ were analysed. The best conditions for dye degradation were an initial dye concentration of 50 mg/L, with a membrane containing TiO₂ loading of 2wt%. It was observed that in the presence of H₂O₂, degradation increases with increasing H₂O₂ concentration and reached up to 95-98%. The high quality permeates obtained from the photocatalytic membrane can be reused.

Keywords: photocatalytic membrane, TiO₂, PVDF, nanoparticles

Procedia PDF Downloads 130

Authors: Debasis Sarkar

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Development of a Smart City would depend upon the development of its infrastructure in a smart way. Primarily based on the ideology of the fourth industrial revolution a Smart City project should have Smart governance, smart health care, smart building, smart transportation, smart mobility, smart energy, smart technology and smart citizen. Considering the Indian scenario of current state of cities in India, it has become very essential to decide the specific parameters which would govern the development of a Smart City project. It has been observed that there are significant parameters beyond Information and Communication Technology (ICT), which govern the development of a Smart City project. This paper is an attempt to identify the Critical Success Factors (CSF) which are significantly responsible for the development of a Smart City project in Western India. Responses to questionnaire survey were analyzed on basis of Likert scale. They were further critically evaluated with help of Factor Comparison Method (FCM) and Analytical Hierarchy Process (AHP). The project authorities need to incorporate Building Information Modeling (BIM) to make the smart city project more collaborative. To make the project more sustainable, use of flyash in the concrete used, reduced usage of cement and steel, use of alternate fuels like biodiesel is recommended.

Keywords: analytical hierarchical process, building information modeling, critical success factors, factor comparison method

Procedia PDF Downloads 220

Authors: Yiğit Gürler, Berkay Türkcan İmrağ, Taylan Güçkıran, İbrahim Şimşek, Alper Taşdemirci

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Paper honeycombs, which is a sandwich structure, consists of two liner faces and one paper honeycomb core. These materials are widely used in the packaging industry due to their low cost, low weight, good energy absorption capabilities and easy recycling properties. However, to provide maximum protection to the products in cases such as the drop of the packaged products, the mechanical behavior of these materials should be well known at the packaging design stage. In this study, the necessary input parameters for the modeling study were obtained by performing compression tests in the through-thickness and in-plane directions of paper-based honeycomb sandwich structures. With the obtained parameters, homogeneous and micro-mechanical numerical models were developed in the Ls-Dyna environment. The material card used for the homogeneous model is MAT_MODIFIED_HONEYCOMB, and the material card used for the micromechanical model is MAT_PIECEWISE_LINEAR_PLASTICITY. As a result, the effectiveness of homogeneous and micromechanical modeling approaches for paper-based honeycomb sandwich structure was investigated using force-displacement curves. Densification points and peak points on these curves will be compared.

Keywords: environmental packaging, mechanical characterization, Ls-Dyna, sandwich structure

Procedia PDF Downloads 157

Authors: Hakan Gungunes, Ismail A. Auwal, Abdulhadi Baykal, Sagar E. Shirsath

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Barium hexaferrite, BaFe₁₂O₁₉, substituted by Bi³⁺ and La³⁺ (BaBiₓLaₓFe₁₂₋₂ₓO₁₉ where 0.0 ≤ x ≤ 0.5) were prepared by solid state synthesis route. The effect of substituted Bi³⁺ and La³⁺ ions on the structure, morphology, magnetic and cation distributions of barium hexaferrite were investigated by X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FT-IR) and Mössbauer spectroscopy. XRD powder patterns were refined by the Rietveld analysis method which confirmed the formation of single phase magneto-plumbite structure and the substitution of La³⁺ and Bi³⁺ ions into the lattice of barium ferrite. These results show that both La³⁺ and Bi³⁺ ions completely enter into barium hexaferrite lattice without disturbing the hexagonal ferrite structure. The EDX spectra confirmed the presence of all the constituents in expected elemental percentage. From 57Fe Mössbauer spectroscopy data, the variation in line width, isomer shift, quadrupole splitting and hyperfine magnetic field values on Bi and La substitutions have been determined. Cation distribution in the presently investigated hexaferrite system was estimated using the relative area of Mössbauer spectroscopy.

Keywords: hexaferrite, mössbauer, cation distribution, solid state synthesis

Procedia PDF Downloads 330

Authors: Dipti Yadav, Latha Rangan, Pinakeswar Mahanta

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Recent fuel-development strategies to reduce oil dependency, mitigate greenhouse gas emissions, and utilize domestic resources have generated interest in the search for alternative sources of fuel supplies. Bioenergy production from lignocellulosic biomass has a great potential. Cellulose, hemicellulose and Lignin are main constituent of woods or agrowaste. In all the industries there are always left over or waste products mainly lignin, due to the heterogeneous nature of wood and pulp fibers and the heterogeneity that exists between individual fibers, no method is currently available for the quantitative isolation of native or residual lignin without the risk of structural changes during the isolation. The potential benefits from finding alternative uses of lignin are extensive, and with a double effect. Lignin can be used to replace fossil-based raw materials in a wide range of products, from plastics to individual chemical products, activated carbon, motor fuels and carbon fibers. Furthermore, if there is a market for lignin for such value-added products, the mills will also have an additional economic incentive to take measures for higher energy efficiency. In this study residual lignin were isolated from areca nut shells by acid hydrolysis and were analyzed and characterized by Fourier Transform Infrared (FTIR), LCMS and complexity of its structure investigated by NMR.

Keywords: Areca nut, Lignin, wood, bioenergy

Procedia PDF Downloads 447

Authors: Mapatsakon Sarapat, Mongkol Ketwongsa, Somchat Sonasang, Preecha Yupapin

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The designed and performed preliminary tests on a space-time control circuit using a two-level system circuit with a 4-5 cm diameter microstrip for realistic teleportation have been demonstrated. It begins by calculating the parameters that allow a circuit that uses the alternative current (AC) at a specified frequency as the input signal. A method that causes electrons to move along the circuit perimeter starting at the speed of light, which found satisfaction based on the wave-particle duality. It is able to establish the supersonic speed (faster than light) for the electron cloud in the middle of the circuit, creating a timeline and propulsive force as well. The timeline is formed by the stretching and shrinking time cancellation in the relativistic regime, in which the absolute time has vanished. In fact, both black holes and white holes are created from time signals at the beginning, where the speed of electrons travels close to the speed of light. They entangle together like a capsule until they reach the point where they collapse and cancel each other out, which is controlled by the frequency of the circuit. Therefore, we can apply this method to large-scale circuits such as potassium, from which the same method can be applied to form the system to teleport living things. In fact, the black hole is a hibernation system environment that allows living things to live and travel to the destination of teleportation, which can be controlled from position and time relative to the speed of light. When the capsule reaches its destination, it increases the frequency of the black holes and white holes canceling each other out to a balanced environment. Therefore, life can safely teleport to the destination. Therefore, there must be the same system at the origin and destination, which could be a network. Moreover, it can also be applied to space travel as well. The design system will be tested on a small system using a microstrip circuit system that we can create in the laboratory on a limited budget that can be used in both wired and wireless systems.

Keywords: quantum teleportation, black-white hole, time, timeline, relativistic electronics

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Authors: Wang Haining, Zhang Hong

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In China, rapid urbanization needs more and more buildings constructed for the growing population in cities. With the help of the methodology which contains investigation, contrastive analysis, design based on component with BIM and experiment before real construction, this research based on mobile light structure system, trying to the sustainable problems partly in present China by systematic study. The system cannot replace the permanent heavy structure completely. So the goal is the improvement of the whole building system by the addition of light structure. This house system uses modularized envelopes and standardized connections, which are pre-fabricated and assembled in factories and transported like containers. Aluminum is used as the structural material in this system, and inorganic thermal insulation material used in the envelope, which have high fireproof properties. The relationship between manufactory and construction of the system is progressive hierarchy. They exist as First Industrial, Second Industrial, Third Industrial and Site Assembly Stage. It could maximize the land usage capacity by fully exploit the area where normal permanent architecture can't take advantage of. Not only the building system itself especially the thermal isolated materials used and active solar photovoltaic system equipped can save energy, but also the way of product development is sustainable.

Keywords: aluminum house, light Structure, rapid assembly, repeat construction

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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Link-to-column connection in eccentrically braced frames (EBF) has been a critical problem since the link flange connected to the column fractured prior to the required link rotation. Even though the problem in link-to-column connection still exist, the use of an eccentrically braced frame (EBF) is increasing day by day as EBF have high elastic stiffness, stable inelastic response under repeated lateral loading, and excellent ductility and energy dissipation capacity. In order to address this problem, a reduced web and flange link section is proposed and evaluated in this study. Reducing the web with holes makes the link to control the failure at the edge of holes introduced. Reducing the flange allows the link to control the location at which the plastic hinge is formed. Thus, the failure supposed to occur in the link flange connected at the connection move to the web and to the reduced link flange. Nonlinear FE analysis and experimental investigations have been done on the developed links, and the result shows that the link satisfies the plastic rotation limit recommended in AICS-360-10. Design equations that define the behavior of the proposed link have been recommended, and the equations were verified through the experimental and FE analysis results.

Keywords: EBFs, earthquake disaster, link-to-column connection, reduced link section

Procedia PDF Downloads 343

Authors: Wizna, Helmi Muis, Hafil Abbas

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An experiment was conducted to improve the nutrient value of sago pith (Metroxylon sago Rottb) supplemented with Zn, Sulfur and urea through fermentation by using cellulolytic bacteria (Bacillus amyloliquefaciens) as inoculums. The experiment was determination of the optimum dose combination (dosage of Zn, S and urea) for sago pith fermentation based on nutrient quality and quantity of these fermented products. The study was conducted in experimental method, using the completely randomized design in factorial with 3 treatments consist of: factor A (Dose of urea: A1 = 2.0%, A2 = 3.0%), factor B (Dose of S: B1 = 0.2%, B2 = 0.4%) and factor C (Dose of Zn: C1 = 0.0025%, C2 = 0.005%). Results of study showed that optimum condition for fermentation process of sago pith with B. amyloliquefaciens caused a change of nutrient content was obtained at urea (3%), S (0,2%), and Zn (0,0025%). This fermentation process was able to increase amino acid average, reduce crude fiber content by 67% and increase crude protein by 433%, which made the nutritional value of the product based on dry matter was 18.22% crude protein, 12.42% crude fiber, 2525 Kcal/kg metabolic energy and 65.73% nitrogen retention.

Keywords: fermentation, sago pith, sulfur, Zn, urea, Bacillus amyloliquefaciens

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Authors: Ching-Yi Yiu, Hui-Chen Hsu

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Objectives: Head and neck cancer (HNC) is a big global health problem in the world. Despite the development of diagnosis and treatment, the overall survival of HNC is still low. The well recognition of the interaction of the host immune system and cancer cells has led to realizing the processes of tumor initiation, progression and metastasis. Many systemic inflammatory responses have been shown to play a crucial role in cancer progression. The pre and post-treatment nutritional and immunological status of HNC patients is a reliable prognostic indicator of tumor outcomes and survivors. Methods: Between July 2020 to June 2022, We have enrolled 60 HNC patients, including 59 males and 1 female, in Chi Mei Medical Center, Liouying, Taiwan. The age distribution was from 37 to 81 years old (y/o), with a mean age of 57.6 y/o. We evaluated the pre-and post-treatment nutritional and immunological status of these HNC patients with body weight, body weight loss, body mass index (BMI), whole blood count including hemoglobin (Hb), lymphocyte, neutrophil and platelet counts, biochemistry including prealbumin, albumin, c-reactive protein (CRP), with the time period of before treatment, post-treatment 3 and 6 months. We calculated the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) to assess how these biomarkers influence the outcomes of HNC patients. Results: We have carcinoma of the hypopharynx in 21 cases with 35％, carcinoma of the larynx in 9 cases, carcinoma of the tonsil and tongue every 6 cases, carcinoma soft palate and tongue base every 5 cases, carcinoma of buccal mucosa, retromolar trigone and mouth floor every 2 cases, carcinoma of the hard palate and low lip each 1 case. There were stage I 15 cases, stage II 13 cases, stage III 6 cases, stage IVA 10 cases, and stage IVB 16 cases. All patients have received surgery, chemoradiation therapy or combined therapy. We have wound infection in 6 cases, 2 cases of pharyngocutaneous fistula, flap necrosis in 2 cases, and mortality in 6 cases. In the wound infection group, the average BMI is 20.4 kg/m2; the average Hb is 12.9 g/dL, the average albumin is 3.5 g/dL, the average NLR is 6.78, and the average PLR is 243.5. In the PC fistula and flap necrosis group, the average BMI is 21.65 kg/m2; the average Hb is 11.7 g/dL, the average albumin is 3.15 g/dL, average NLR is 13.28, average PLR is 418.84. In the mortality group, the average BMI is 22.3 kg/m2; the average Hb is 13.58 g/dL, the average albumin is 3.77 g/dL, the average NLR is 6.06, and the average PLR is 275.5. Conclusion: HNC is a big challenging public health problem worldwide, especially in the high prevalence of betel nut consumption area Taiwan. Besides the definite risk factors of smoking, drinking and betel nut related, the other biomarkers may play significant prognosticators in the HNC outcomes. We concluded that the average BMI is less than 22 kg/m2, the average Hb is low than 12.0 g/dL, the average albumin is low than 3.3 g/dL, the average NLR is low than 3, and the average PLR is more than 170, the surgical complications and mortality will be increased, and the prognosis is poor in HNC patients.

Keywords: nutritional, immunological, neutrophil-to-lymphocyte ratio, paltelet-to-lymphocyte ratio.

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Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Abdelbary Prince, Said Moussa, Hyungkyu Kim, Eman Gouda, Jin Han

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We compared the dynamic alterations of mitochondrial proteome of control, ischemia-reperfusion (IR) and ischemic preconditioned (IPC) rabbit hearts. Using 2-DE, we identified 29 mitochondrial proteins that were differentially expressed in the IR heart compared with the control and IPC hearts. For two of the spots, the expression patterns were confirmed by Western blotting analysis. These proteins included succinate dehydrogenase complex, Acyl-CoA dehydrogenase, carnitine acetyltransferase, dihydrolipoamide dehydrogenase, Atpase, ATP synthase, dihydrolipoamide succinyltransferase, ubiquinol-cytochrome c reductase, translation elongation factor, acyl-CoA dehydrogenase, actin alpha, succinyl-CoA Ligase, dihydrolipoamide S-succinyltransferase, citrate synthase, acetyl-Coenzyme A dehydrogenase, creatine kinase, isocitrate dehydrogenase, pyruvate dehydrogenase, prohibitin, NADH dehydrogenase (ubiquinone) Fe-S protein, enoyl Coenzyme A hydratase, superoxide dismutase [Mn], and 24-kDa subunit of complex I. Interestingly, most of these proteins are associated with the mitochondrial respiratory chain, antioxidant enzyme system, and energy metabolism. The results provide clues as to the cardioprotective mechanism of ischemic preconditioning at the protein level and may serve as potential biomarkers for detection of ischemia-induced cardiac injury.

Keywords: ischemic preconditioning, mitochondria, proteome, cardioprotection

Procedia PDF Downloads 321

Authors: Manju Lata Sharma

Abstract:

Damage to cells caused by free radicals is believed to play a central role in the ageing process and in disease progression. Withania somnifera is widely used in ayurvedic medicine, and it is one of the ingredients in many formulations to increase energy, improve overall health and longevity and prevent disease. Withania somnifera possesses antioxidative properties. The antioxdant activity of Withania somnifera consisting of an equimolar concentration of active principles of sitoindoside VII-X and withaferin A. The antioxidant effect of Withania somnifera extract was investigated on lipid peroxidation (LPO), superoxide dismutase (SOD) and catalase (CAT) activity in mice. Aim: To study the antioxidant activity of an extract of Withania somnifera leaf against a mice model of chronic stress. Healthy swiss albino mice (3-4 months old) selected from an inbred colony were divided in to 6 groups. Biochemical estimation revealed that stress induced a significant change in SOD, LPO, CAT AND GPX. These stress induced perturbations were attenuated Withania somnifera (50 and 100 mg/kg BW). Result: Withania somnifera tended to normalize the augmented SOD and LPO activities and enhanced the activities of CAT and GPX. The result indicates that treatment with an alcoholic extract of Withania somnifera produced a significant decrease in LPO ,and an increase in both SOD and CAT in brain mice. This indicates that Withania somnifera extract possesses free radical scavenging activity .

Keywords: Withania somnifera, antioxidant, lipid peroxidation, brain

Procedia PDF Downloads 339

Authors: Alexey Abilov

Abstract:

The article highlights the experience of training master's and doctoral students at Satbayev University by preparing their course works for disciplines "Principles of Sustainable Architecture", "Energy Efficiency in Urban planning", "Urban planning analysis, "Social foundations of Architecture". The purpose of these works is the acquisition by students of practical skills necessary in their future professional activities, which are achieved through comprehensive assessment of individual sections of the Almaty urban environment. The methodology of student’s researches carried out under the guidance of the author of this publication is based on an expert assessment of the territory through its full-scale survey, analysis of project documents and statistical data, as well as on a social assessment of the territory based on the results of a questionnaire survey of residents. A comprehensive qualitative and quantitative assessment of the selected sites according to the criteria of the quality of the living environment also allows to formulate specific recommendations for designers who carry out a pre-project analysis of the city territory in the process of preparing draft master plans and detailed planning projects.

Keywords: urban environment, expert/social assessment of the territory, questionnaire survey, comprehensive approach

Procedia PDF Downloads 36

Authors: Samvel H. Sargsyan

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Together with the study of electron-optical properties of nanostructures and proceeding from experiment-based data, the study of the mechanical properties of nanostructures has become quite actual. For the study of the mechanical properties of fullerene, carbon nanotubes, graphene and other nanostructures one of the crucial issues is the construction of their adequate mathematical models. Among all mathematical models of graphene or carbon nano-tubes, this so-called discrete-continuous model is specifically important. It substitutes the interactions between atoms by elastic beams or springs. The present paper demonstrates the construction of the discrete-continual beam model for carbon nanotubes or graphene, where the micropolar beam model based on the theory of moment elasticity is accepted. With the account of the energy balance principle, the elastic moment constants for the beam model, expressed by the physical and geometrical parameters of carbon nanotube or graphene, are determined. By switching from discrete-continual beam model to the continual, the models of micropolar elastic cylindrical shell and micropolar elastic plate are confirmed as continual models for carbon nanotube and graphene respectively.

Keywords: carbon nanotube, discrete-continual, elastic, graphene, micropolar, plate, shell

Procedia PDF Downloads 122

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 90

Authors: Aidan N. Smallwood, Celestine R. Weegenaar, Jack N. Evans

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The intensive care unit (ICU) is a particularly resource heavy environment, in terms of staff, drugs and equipment required. Whilst many areas of the hospital are attempting to cut down on plastic use and minimise their impact on the environment, this has proven challenging within the confines of intensive care. Concurrently, as globalization has progressed over recent decades, there has been a tendency towards centralised manufacturing with international distribution networks for products, often covering large distances. In this study, we have modelled the standard consumption of plastic single-use items over the course of the first 24-hours of an average individual patient’s stay in a 12 bed ICU in the United Kingdom (UK). We have identified the country of manufacture and calculated the minimum possible distance travelled by each item from factory to patient. We have assumed direct transport via the shortest possible straight line from country of origin to the UK and have not accounted for transport within either country. Assuming an intubated patient with invasive haemodynamic monitoring and central venous access, there are a total of 52 distincts, largely plastic, disposable products which would reasonably be required in the first 24-hours after admission. Each product type has only been counted once to account for multiple items being shipped as one package. Travel distances from origin were summed to give the total distance combined for all 52 products. The minimum possible total distance travelled from country of origin to the UK for all types of product was 273,353 km, equivalent to 6.82 circumnavigations of the globe, or 71% of the way to the moon. The mean distance travelled was 5,256 km, approximately the distance from London to Mecca. With individual packaging for each item, the total weight of consumed products was 4.121 kg. The CO2 produced shipping these items by air freight would equate to 30.1 kg, however doing the same by sea would produce 0.2 kg CO2. Extrapolating these results to the 211,932 UK annual ICU admissions (2018-2019), even with the underestimates of distance and weight of our assumptions, air freight would account for 6586 tons CO2 emitted annually, approximately 130 times that of sea freight. Given the drive towards cost saving within the UK health service, and the decline of the local manufacturing industry, buying from intercontinental manufacturers is inevitable However, transporting all consumables by sea where feasible would be environmentally beneficial, as well as being less costly than air freight. At present, the NHS supply chain purchases from medical device companies, and there is no freely available information as to the transport mode used to deliver the product to the UK. This must be made available to purchasers in order to give a fuller picture of life cycle impact and allow for informed decision making in this regard.

Keywords: CO2, intensive care, plastic, transport

Procedia PDF Downloads 131

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) wherein the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation and Control design team. This paper discusses the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), steady state, transient state

Procedia PDF Downloads 223

Authors: Parisa Afshin, Terje Grønning

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Norway, similar to many other countries, has set the focus of its policies in creating new strong and highly innovative sectors in recent years, as the oil and gas sector profitability is declining. Biotechnology sector in Norway has a great potential, especially in marine-biotech and cancer medicine. However, Norway being a periphery faces especial challenges in the path of creating internationally well-known biotech sector and an international knowledge hub. The aim of this article is to analyze the progress of the Norwegian biotechnology industry, its pathway to build up an innovation network and conduct collaborative innovation based on its initial conditions and its own advantage and disadvantages. The findings have important implications not only for politicians and academic in understanding the infrastructure of biotechnology sector in the country, but it has important lessons for other periphery countries or regions aiming in creating strong biotechnology sector and catching up with the strong internationally-recognized regions. Data and methodology: To achieve the main goal of this study, information has been collected via secondary resources such as web pages and annual reports published by the officials and mass media along with interviews were used. The data were collected with the goal to shed light on a brief history and current status of Norway biotechnology sector, as well as geographic distribution of biotech industry, followed by the role of academic and industry collaboration and public policies in Norway biotech. As knowledge is the key input in innovation, knowledge perspective of the system such as knowledge flow in the sector regarding the national and regional innovation system has been studied. Primary results: The internationalization has been an important element in development of periphery regions' innovativeness enabling them to overcome their weakness while putting more weight on the importance of regional policies. Following such findings, suggestions on policy decision and international collaboration, regarding national and regional system of innovation, has been offered as means of promoting strong innovative sector.

Keywords: biotechnology sector, knowledge-based industry, national innovation system, regional innovation system

Procedia PDF Downloads 191

Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

Procedia PDF Downloads 222