Search results for: diffuse large B-cell lymphoma

Authors: Iva Blazkova, Amitava Moulick, Vedran Milosavljevic, Pavel Kopel, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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Doxorubicin is one of the most commonly used and the most effective chemotherapeutic drugs. This antracycline drug isolated from the bacteria Streptomyces peuceticus var. caesius is sold under the trade name Adriamycin (hydroxydaunomycin, hydroxydaunorubicin). Doxorubicin is used in single therapy to treat hematological malignancies (blood cancers, leukaemia, lymphoma), many types of carcinoma (solid tumors) and soft tissue sarcomas. It has many serious side effects like nausea and vomiting, hair lost, myelosupression, oral mucositis, skin reactions and redness, but the most serious one is the cardiotoxicity. Because of the risk of heart attack and congestive heart failure, the total dose administered to patients has to be accurately monitored. With the aim to lower the side effects and to targeted delivery of doxorubicin into the tumor tissue, the different nanoparticles are studied. The drug can be bound on a surface of nanoparticle, encapsulated in the inner cavity, or incorporated into the structure of nanoparticle. Among others, carbon nanoparticles (graphene, carbon nanotubes, fullerenes) are highly studied. Besides the number of inorganic nanoparticles, a great potential exhibit also organic ones mainly lipid-based and polymeric nanoparticle. The aim of this work was to perform a toxicity study of free doxorubicin compared to doxorubicin conjugated with various nanotransporters. The effect of liposomes, fullerenes, graphene, and carbon nanotubes on the toxicity was analyzed. As a first step, the binding efficacy of between doxorubicin and the nanotransporter was determined. The highest efficacy was detected in case of liposomes (85% of applied drug was encapsulated) followed by graphene, carbon nanotubes and fullerenes. For the toxicological studies, the chicken embryos incubated under controlled conditions (37.5 °C, 45% rH, rotation every 2 hours) were used. In 7th developmental day of chicken embryos doxorubicin or doxorubicin-nanotransporter complex was applied on the chorioallantoic membrane of the eggs and the viability was analyzed every day till the 17th developmental day. Then the embryos were extracted from the shell and the distribution of doxorubicin in the body was analyzed by measurement of organs extracts using laser induce fluorescence detection. The chicken embryo mortality caused by free doxorubicin (30%) was significantly lowered by using the conjugation with nanomaterials. The highest accumulation of doxorubicin and doxorubicin nanotransporter complexes was observed in the liver tissue

Keywords: doxorubicin, chicken embryos, nanotransporters, toxicity

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Authors: Chetneti Srisa-an

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In Knowledge and Data Engineering field, relational database is the best repository to store data in a real world. It has been using around the world more than eight decades. Normalization is the most important process for the analysis and design of relational databases. It aims at creating a set of relational tables with minimum data redundancy that preserve consistency and facilitate correct insertion, deletion, and modification. Normalization is a major task in the design of relational databases. Despite its importance, very few algorithms have been developed to be used in the design of commercial automatic normalization tools. It is also rare technique to do it automatically rather manually. Moreover, for a large and complex database as of now, it make even harder to do it manually. This paper presents a new complete automated relational database normalization method. It produces the directed graph and spanning tree, first. It then proceeds with generating the 2NF, 3NF and also BCNF normal forms. The benefit of this new algorithm is that it can cope with a large set of complex function dependencies.

Keywords: relational database, functional dependency, automatic normalization, primary key, spanning tree

Procedia PDF Downloads 332

Authors: Min Gao

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In the past year, the advent of large language models (LLMs) has brought about a revolution in the language service industry, making it possible to efficiently produce more satisfactory and higher-quality translations. This is groundbreaking news for commercial companies involved in language services since much of a translator's work can now be completed by machines. However, it may be bad news for universities that provide translation training programs. They need to confront the challenges posed by AI in education by reconsidering issues such as the reform of traditional teaching methods, the translation ethics of students, and the new demands of the job market for their graduates. This article is an exploratory study of these issues based on the author's experiences in translation teaching. The research combines methods in the form of questionnaires and interviews. The findings include: (1) students may lose their motivation to learn in the AI era, but this can be compensated for by encouragement from the lecturer; (2) Translation ethics are not a serious problem in schools, considering the strict policies and regulations in place; (3) The role of translators has evolved in the new era, necessitating a reform of the traditional teaching methods.

Keywords: job market of translation, large language model, translation ethics, translation training

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Authors: Bhairi Lakshminarayana, Surajit Sarker, Ch. Subrahmanyam

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The present study reports the development of noble metal free nano catalysts for low-temperature CO oxidation and water gas shift reaction. Mn-substituted CeO2 solid solution catalysts were synthesized by co-precipitation, combustion and hydrothermal methods. The formation of solid solution was confirmed by XRD with Rietveld refinement and the percentage of carbon and nitrogen doping was ensured by CHNS analyzer. Raman spectroscopic confirmed the oxygen vacancies. The surface area, pore volume and pore size distribution confirmed by N2 physisorption analysis, whereas, UV-visible diffuse reflectance spectroscopy and XPS data confirmed the oxidation state of the Mn ion. The particle size and morphology (spherical shape) of the material was confirmed using FESEM and HRTEM analysis. Ce0.8Mn0.2O2-δ was calcined at 400 °C, 600 °C and 800 °C. Raman spectroscopy confirmed that the catalyst calcined at 400 °C has the best redox properties. The activity of the designed catalysts for CO oxidation (0.2 vol%), carried out with GHSV of 21,000 h-1 and it has been observed that co-precipitation favored the best active catalyst towards CO oxidation and water gas shift reaction, due to the high surface area, improved reducibility, oxygen mobility and highest quantity of surface oxygen species. The activation energy of low temperature CO oxidation on Ce0.8Mn0.2O2- δ (combustion) was 5.5 kcal.K-1.mole-1. The designed catalysts were tested for water gas shift reaction. The present study demonstrates that Mn ion substituted ceria at 400 °C calcination temperature prepared by co-precipitation method promise to revive a green sustainable energy production approach.

Keywords: Ce0.8Mn0.2O2-ð, CO oxidation, physicochemical characterization, water gas shift reaction (WGS)

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Authors: Sabiu Abdullahi Yau

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Nigeria is a high fertility country that experiences eye-popping population growth, with no end in sight. However, there is evidence that its large population inhibits government’s efforts in meeting the basic needs of the people. Moreover, past and present governments of Nigeria have been committing huge amount of financial resources to meet the basic infrastructural requirements capable of propelling growth and development. Despite the country’s large population and abundant natural resources, poverty, unemployment, rural-urban migration, deforestation and inadequate infrastructural facilities have been persistently on the increase resulting in consistent failure of government policies to impact positively on the economy. This paper, however, identifies and critically analyses the major development challenges caused by population growth in Nigeria using secondary data. The paper concludes that for the Nigeria’s economy to develop, all the identified challenges posed by rapid population growth must be promptly and squarely addressed.

Keywords: economic development, population, growth, Nigeria

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, unsupervised training, text retrieval

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Authors: Zineb Abidi, Marc-Arthur Diaye

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There exists a large empirical literature concerning the relationship between corporate social responsibility (CSR) and corporate financial performance. This literature, however, applies mainly to large corporations and/or listed firms. To the best of our knowledge, the question of whether meeting CSR requirements impacts the financial performance of small and medium-sized unlisted SMEs has not so far been analyzed. This paper aims to analyze, for the first time, the effect of CSR on the financial performance of SMEs. Using an original database including 5,257 French SMEs, we show that adopting CSR practices has a positive but weak effect on a firm’s financial performance. To develop this further, we analyzed CSR practices interactions assessing the best combination of CSR components that positively influence SME financial performance. Our results show that French SMEs benefit more from their pro-social behavior when they choose a combination of CSR components best adapted to their individual characteristics.

Keywords: corporate social responsibility, financial performance, unlisted firms, SMEs

Procedia PDF Downloads 148

Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Diwei Lin, Amanda Jh. Tan

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We present a very rare case of de novo large cell neuroendocrine carcinoma of the prostate (LCNEC) in an 84-year-old male on a background of high-grade, muscle-invasive transitional cell carcinoma of the bladder. While NE tumours account for 1% to 5% of all cases of prostate cancer and scattered NE cells can be found in 10% to 100% of prostate adenocarcinomas, pure LCNEC of the prostate is extremely rare. Most LCNEC of the prostate is thought to originate by clonal progression under the selection pressure of therapy and refractory to long-term hormonal treatment for adenocarcinoma of the prostate. De novo LCNEC is only described in case reports and is thought to develop via direct malignant transformation. Limited data in the English literature makes it difficult to accurately predict the prognosis of LCNEC of the prostate. However, current evidence suggesting that increasing NE differentiation in prostate adenocarcinoma is associated with a higher stage, high-grade disease, and a worse prognosis.

Keywords: large cell neuroendocrine cancer, prostate cancer, refractory cancer, medical and health sciences

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Authors: Yousif M. Yousif Abdallah, Mohamed E. Gar-Elnabi, Abdoelrahman H. A. Bakary, Alaa M. H. Eltoum, Abdelazeem K. M. Ali

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The study was established to measure the amount of radiation outside the treatment field in external beam radiation therapy using day method of dose calculation, the data was collected from 89 patients of cervical carcinoma in order to determine if the dose outside side the irradiation treatment field for spleen, liver, both kidneys, small bowel, large colon, skin within the acceptable limit or not. The cervical field included mainly 4 organs which are bladder, rectum part of small bowel and hip joint these organ received mean dose of (4781.987±281.321), (4736.91±331.8), (4647.64±387.1) and (4745.91±321.11) respectively. The mean dose received by outfield organs was (77.69±15.24cGy) to large colon, (93.079±12.31cGy) to right kidney (80.688±12.644cGy) to skin, (155.86±17.69cGy) to small bowel. This was more significant value noted.

Keywords: radiation dose, cervical carcinoma, day’s methods, radiation medicine

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Authors: Jianjun Wu, Fanhui Guo, Yixin Zhang

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In this study, gasification-coke were produced by blending the middlings (MC), and coking coal (CC) and a large proportion of long flame coal (Shenfu coal, SC), the effects of blending ratio were investigated. Mineral evolution and crystalline order obtained by XRD methods were reproduced within reasonable accuracy. Structure characteristics of partially gasification-coke such as surface area and porosity were determined using the N₂ adsorption and mercury porosimetry. Experimental data of gasification-coke was dominated by the TGA results provided trend, reactivity differences between gasification-cokes are discussed in terms of structure characteristic, crystallinity, and alkali index (AI). The first-order reaction equation was suitable for the gasification reaction kinetics of CO₂ atmosphere which was represented by the volumetric reaction model with linear correlation coefficient above 0.985. The differences in the microporous structure of gasification-coke and catalysis caused by the minerals in parent coals were supposed to be the main factors which affect its reactivity. The addition of MC made the samples enriched with a large amount of ash causing a higher surface area and a lower crystalline order to gasification-coke which was beneficial to gasification reaction. The higher SiO₂ and Al₂O₃ contents, causing a decreasing AI value and increasing activation energy, which reduced the gasification reaction activity. It was found that the increasing amount of MC got a better performance on the coke gasification reactivity by blending > 30% SC with this coking process.

Keywords: low-rank coal, middlings, structure characteristic, mineral evolution, alkali index, gasification-coke, gasification kinetics

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Authors: Arun Perumbilavil Anand

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In the recent years, Kerala is witnessing a large inflow of migrants from different parts of the country. Though initially, the migrants were largely from the districts of Tamil Nadu and mostly of seasonal nature, but at a later period, the state started getting migrants from the far-off states like UP, Assam, Bengal, etc. Higher wages for unskilled labour, large opportunities for employment, the reluctance on the part of Kerala workers to do menial and hard physical work, and the shortage of local labour, paradoxically despite the high unemployment rate in the state, led to the massive influx of migrant labourers. This study takes a multi-dimensional overview of migrant labour in Kerala by encompassing factors such as channels of migration, nature of employment contracts entered into and the corresponding wages and benefits obtained by them. The study also analysed the circumstances that led to the large influx of migrants from different states of India. It further makes an attempt to examine the varying dimensions of living and working environment, and also the health conditions of migrants. The study is based on the empirical findings obtained as a result of the primary interviews conducted with migrants in the districts of Palakkad, Malappuram, and Ernakulam. The study concludes by noting that Kerala will inevitably have to depend on migrant labour and is likely to experience heavy in-migration of labour in future, provided that if the existing socioeconomic and demographic situations persist. Since, this is inevitable, the best way before the state is to prepare well in advance to receive and accommodate such migrant labour to lead a comfortable life in a hassle free environment, so that it would definitely play a vital role in further strengthening and sustaining the growth trajectory of not only Kerala’s economy but also the states of origin.

Keywords: Kerala, labour, migration, migrant workers

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Authors: M. Naveed Iqbal, Sheza Fatima, Noman Shabbir

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In the presence of energy crisis in Pakistan, off-grid remote areas are not on priority list. The use of new large scale coal fired power plants will also make this situation worst. Therefore, the greatest challenge in our society is to explore new ways to power off grid remote areas with renewable energy sources. It is time for a sustainable energy policy which puts consumers, the environment, human health, and peace first. The renewable energy is one of the biggest growing sectors of the energy industry. Therefore, the large scale use of micro grid is thus described here with modeling, simulation, planning and operating of the micro grid. The goal of this research paper is to go into detail of a library of major components of micro grid. The introduction will go through the detail view of micro grid definition. Then, the simulation of Micro Grid in MATLAB/ Simulink including the Photo Voltaic Cell will be described with the detailed modeling. The simulation with the design and modeling will be introduced too.

Keywords: micro grids, distribution generation, PV, off-grid operations

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: Oleg Oborin

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This paper is dedicated to the development of the model, which can be used to evaluate the effectiveness of long-term corporate strategies and identify the best strategies. The theoretical model of the relatively homogenous product market (such as iron and steel industry, mobile services or road transport) has been developed. In the model, the market consists of a large number of companies with different internal characteristics and objectives. The companies can perform mergers and acquisitions in order to increase their market share. The model allows the simulation of long-time dynamics of the market (for a period longer than 20 years). Therefore, a large number of simulations on random input data was conducted in the framework of the model. After that, the results of the model were compared with the dynamics of real markets, such as the US steel industry from the beginning of the XX century to the present day, and the market of mobile services in Germany for the period between 1990 and 2015.

Keywords: Economic Modelling, Long-Time Strategy, Mergers and Acquisitions, Simulation

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Authors: Edward Ridyard, Vinary Varadarajan

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Background and Aims: The first year as a doctor in any country represents a major career transition in any physician's life. During this period, many physicians concentrate on obtaining clinical skills but may not obtain the important skills necessary to cope with stress. In this study we elucidate stress levels amongst FY1 doctors regarding the transitioning into specialty career choices, working in the NHS and anxiety about future career success. Methods: A prospective single blinded analysis of Foundation Year one (FY1) trainees using a non-mandatory online questionnaire was distributed. No exclusion criteria were applied. The only inclusion criteria was the doctor was in a full-time FY1 post and this was their first job in the UK. A total of n= 22 doctors were included in the study. After data collection, statistical analysis using chi-squared testing was applied. Results: The large majority of FY1 doctors (72.7%) already knew what specialty they wished to pursue (p=0.0001). With regards to their future careers 45.5% of FY1 doctors stated "above average" stress levels. The majority of FY1 doctors (64.3%) stated their stress levels working in the NHS were either "above average" or "high". Finally, 81.8% of respondents know colleagues who have been put off from pursuing specialties due to the stress of competition. Conclusions: A large majority of FY1 doctors already know at this early stage what area they would like to specialise in. With this in mind, a large proportion have above "average" levels of stress with regards to securing this future career path. The most worrying finding is that 64.3% of FY1s stated they had "above average" or "high" stress levels working in the NHS. We therefore recommend formal stress management education to be incorporated into the foundation programme curriculum.

Keywords: stress, anxiety, junior doctor, education

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Authors: Jude K. Safo

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Knowledge Graphs KG) and their relation to Graph Embeddings (GE) represent a unique data structure in the landscape of machine learning (relative to image, text and acoustic data). Unlike the latter, GEs are the only data structure sufficient for representing hierarchically dense, semantic information needed for use-cases like supply chain data and protein folding where the search space exceeds the limits traditional search methods (e.g. page-rank, Dijkstra, etc.). While GEs are effective for compressing low rank tensor data, at scale, they begin to introduce a new problem of ’data retreival’ which we observe in Large Language Models. Notable attempts by transE, TransR and other prominent industry standards have shown a peak performance just north of 57% on WN18 and FB15K benchmarks, insufficient practical industry applications. They’re also limited, in scope, to next node/link predictions. Traditional linear methods like Tucker, CP, PARAFAC and CANDECOMP quickly hit memory limits on tensors exceeding 6.4 million nodes. This paper outlines a topological framework for linear mapping between concepts in KG space and GE space that preserve cardinality. Most importantly we introduce a traceable framework for composing dense linguistic strcutures. We demonstrate performance on WN18 benchmark this model hits. This model does not rely on Large Langauge Models (LLM) though the applications are certainy relevant here as well.

Keywords: representation theory, large language models, graph embeddings, applied algebraic topology, applied knot theory, combinatorics

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Authors: Kashish Sareen, Jatinder Singh Bal

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The use of wireless sensor networks (WSNs) has grown vastly in the last era, pointing out the crucial need for scalable and energy-efficient routing and data gathering and aggregation protocols in corresponding large-scale environments. Wireless Sensor Networks have now recently emerged as a most important computing platform and continue to grow in diverse areas to provide new opportunities for networking and services. However, the energy constrained and limited computing resources of the sensor nodes present major challenges in gathering data. The sensors collect data about their surrounding and forward it to a command centre through a base station. The past few years have witnessed increased interest in the potential use of wireless sensor networks (WSNs) as they are very useful in target detecting and other applications. However, hierarchical clustering protocols have maximum been used in to overall system lifetime, scalability and energy efficiency. In this paper, the state of the art in corresponding hierarchical clustering approaches for large-scale WSN environments is shown.

Keywords: clustering, DLCC, MLCC, wireless sensor networks

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Authors: Gen Sakoda, Hideki Takayasu, Misako Takayasu

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Waste reduction is a fundamental problem for sustainability. Methods for waste reduction with point-of-sales (POS) data are proposed, utilizing the knowledge of a recent econophysics study on a statistical property of POS data. Concretely, the non-stationary time series analysis method based on the Particle Filter is developed, which considers abnormal fluctuation scaling known as Taylor's law. This method is extended for handling incomplete sales data because of stock-outs by introducing maximum likelihood estimation for censored data. The way for optimal stock determination with pricing the cost of waste reduction is also proposed. This study focuses on the examination of the methods for large sales numbers where Taylor's law is obvious. Numerical analysis using aggregated POS data shows the effectiveness of the methods to reduce food waste maintaining a high profit for large sales numbers. Moreover, the way of pricing the cost of waste reduction reveals that a small profit loss realizes substantial waste reduction, especially in the case that the proportionality constant  of Taylor’s law is small. Specifically, around 1% profit loss realizes half disposal at =0.12, which is the actual  value of processed food items used in this research. The methods provide practical and effective solutions for waste reduction keeping a high profit, especially with large sales numbers.

Keywords: food waste reduction, particle filter, point-of-sales, sustainable development goals, Taylor's law, time series analysis

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Authors: K. Geetha Ramesh, A. Ramachandraiah

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In an internal building space, daylight becomes a powerful source of illumination. The challenge therefore, is to develop means of utilizing both direct and diffuse natural light in buildings while maintaining and improving occupant's visual comfort, particularly at greater distances from the windows throwing daylight. The geometrical features of windows in a building have significant effect in providing daylight. The main goal of this research is to develop an innovative window geometry, which will effectively provide the daylight component adequately together with internal reflected component(IRC) and also the external reflected component(ERC), if any. This involves exploration of a light redirecting system using fractal geometry for windows, in order to penetrate and distribute daylight more uniformly to greater depths, minimizing heat gain and glare, and also to reduce building energy use substantially. Of late the creation of fractal geometrical window and the occurrence of daylight illuminance due to such windows is becoming an interesting study. The amount of daylight can change significantly based on the window geometry and sky conditions. This leads to the (i) exploration of various fractal patterns suitable for window designs, and (ii) quantification of the effect of chosen fractal window based on the relationship between the fractal pattern, size, orientation and glazing properties for optimizing daylighting. There are a lot of natural lighting applications able to predict the behaviour of a light in a room through a traditional opening - a regular window. The conventional prediction methodology involves the evaluation of the daylight factor, the internal reflected component and the external reflected component. Having evaluated the daylight illuminance level for a conventional window, the technical performance of a fractal window for an optimal daylighting is to be studied and compared with that of a regular window. The methodologies involved are highlighted in this paper.

Keywords: daylighting, fractal geometry, fractal window, optimization

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Authors: Dunwen Zuo, Yongfang Deng, Bo Song

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An attempt is made here to measure the forces of three directions, under conditions of different feed speeds, different tilt angles of tool and without or with the pin on the tool, by using octagonal ring dynamometer in the AA2024 aluminum FSJ (Friction Stir Joining) process, and investigate how four main factors influence forces in the FSJ process. It is found that, high feed speed lead to small feed force and small lateral force, but high feed speed leads to large feed force in the stable joining stage of process. As the rotational speed increasing, the time of axial force drop from the maximum to the minimum required increased in the push-up process. In the stable joining stage, the rotational speed has little effect on the feed force; large rotational speed leads to small lateral force and axial force. The maximum axial force increases as the tilt angle of tool increases at the downward movement stage. At the moment of start feeding, as tilt angle of tool increases, the amplitudes of the axial force increasing become large. In the stable joining stage, with the increase of tilt angle of tool, the axial force is increased, the lateral force is decreased, and the feed force almost unchanged. The tool with pin will decrease axial force in the downward movement stage. The feed force and lateral force will increase, but the axial force will reduced in the stable joining stage by using the tool with pin compare to by using the tool without pin.

Keywords: FSJ, force factor, AA2024 aluminum, friction stir joining

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

Procedia PDF Downloads 106

Authors: Amirmozafar Benshams, Khatere Kashmari, Farzad Hatami, Mesbah Saybani

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Shape memory alloys with high capability of energy dissipation and large deformation bearing with return ability to their original shape without too much hysteresis strain have opened their place among the other damping systems as smart materials. Ninitol which is the most well-known and most used alloy material from the shape memory alloys family, has high resistance and fatigue and is coverage for large deformations. Shape memory effect and super-elasticity by shape alloys like Nitinol, are the reasons of the high power of these materials in energy depreciation. Thus, these materials are suitable for use in reciprocating dynamic loading conditions. The experiments results showed that Nitinol wires with small diameter have greater energy dissipation capability and by increase of diameter and thickness the damping capability and energy dissipation increase.

Keywords: shape memory alloys, shape memory effect, super elastic effect, nitinol, energy dissipation

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Authors: I. A. Farhat

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The dynamic economic dispatch (DED) problem is one of the complex, constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: artificial immune system, dynamic economic dispatch, optimal economic operation, large-scale problem

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Authors: Dawoon Choi, Jian Li, Yunhyun Cho

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Axial Flux Permanent Magnet (AFPM) machines have been widely used in various applications due to their important merits, such as compact structure, high efficiency and high torque density. This paper presents one of the most important characteristics in the design process of the AFPM device, which is a recent issue. To design AFPM machine, the predicting electromagnetic forces between the permanent magnets and stator is important. Because of the magnitude of electromagnetic force affects many characteristics such as machine size, noise, vibration, and quality of output power. Theoretically, this force is canceled by the equilibrium of force when it is in the middle of the gap, but it is inevitable to deviate due to manufacturing problems in actual machine. Such as large scale wind generator, because of the huge attractive force between rotor and stator disks, this is more serious in getting large power applications such as large. This paper represents the characteristics of Double-Stator Inner –Rotor AFPM machines when it has rotor eccentricity. And, unbalanced air-gap and inclined air-gap condition which is caused by rotor offset and tilt in a double-stator single inner-rotor AFPM machine are each studied in electromagnetic and mechanical aspects. The output voltage and cogging torque under un-normal air-gap condition of AF machines are firstly calculated using a combined analytical and numerical methods, followed by a structure analysis to study the effect to mechanical stress, deformation and bending forces on bearings. Results and conclusions given in this paper are instructive for the successful development of AFPM machines.

Keywords: axial flux permanent magnet machine, inclined air gap, unbalanced air gap, rotor eccentricity

Procedia PDF Downloads 194

Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Sankara Rao Gollu, Ramakant Sharma, G. Srinivas, Souvik Kundu, Dipti Gupta

Abstract:

In recent years, bulk heterojunction organic solar cells (BHJ OSCs) based on polymer–fullerene attracted a large research attention due to their numerous advantages such as light weight, easy processability, eco-friendly, low-cost, and capability for large area roll-to-roll manufacturing. BHJ OSCs usually suffer from insufficient light absorption due to restriction on keeping thin ( < 150 nm) photoactive layer because of small exciton diffusion length ( ~ 10 nm) and low charge carrier mobilities. It is thus highly desirable that light absorption as well as charge transport properties are enhanced by alternative methods so as to improve the device efficiency. In this work, therefore, we have focused on the strategy of incorporating metallic nanostructures in the active layer or charge transport layer to enhance the absorption and improve the charge transport.

Keywords: organic solar cell, efficiency, bulk heterojunction, polymer-fullerene

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Authors: Pachari Chuenta, Suwat Nanan

Abstract:

ZnO nanostructures have been synthesized successfully in high yield via catalyst-free chemical precipitation technique by varying zinc source (either zinc nitrate or zinc acetate) and oxygen source (either oxalic acid or urea) without using any surfactant, organic solvent or capping agent. The ZnO nanostructures were characterized by Fourier transform infrared spectroscopy (FT-IR), X-ray diffractometry (XRD), scanning electron microscopy (SEM), thermal gravimetric analysis (TGA), UV-vis diffuse reflection spectroscopy (UV-vis DRS), and photoluminescence spectroscopy (PL). The FTIR peak in the range of 450-470 cm-1 corresponded to Zn-O stretching in ZnO structure. The synthesized ZnO samples showed well crystalized hexagonal wurtzite structure. SEM micrographs displayed spherical droplet of about 50-100 nm. The band gap of prepared ZnO was found to be 3.4-3.5 eV. The presence of PL peak at 468 nm was attributed to surface defect state. The photocatalytic activity of ZnO was studied by monitoring the photodegradation of reactive red (RR141) azo dye under ultraviolet (UV) light irradiation. Blank experiment was also separately carried out by irradiating the aqueous solution of the dye in absence of the photocatalyst. The initial concentration of the dye was fixed at 10 mgL-1. About 50 mg of ZnO photocatalyst was dispersed in 200 mL dye solution. The sample was collected at a regular time interval during the irradiation and then was analyzed after centrifugation. The concentration of the dye was determined by monitoring the absorbance at its maximum wavelength (λₘₐₓ) of 544 nm using UV-vis spectroscopic analysis technique. The sources of Zn and O played an important role on photocatalytic performance of the ZnO photocatalyst. ZnO nanoparticles which prepared by zinc acetate and oxalic acid at molar ratio of 1:1 showed high photocatalytic performance of about 97% toward photodegradation of reactive red azo dye (RR141) under UV light irradiation for only 60 min. This work demonstrates the promising potential of ZnO nanomaterials as photocatalysts for environmental remediation.

Keywords: azo dye, chemical precipitation, photocatalytic, ZnO

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Authors: Nasim Abuali Galehdari, Venkat Mani, Ajit D. Kelkar

Abstract:

Space Radiation has become one of the major factors in successful long duration space exploration. Exposure to space radiation not only can affect the health of astronauts but also can disrupt or damage materials and electronics. Hazards to materials include degradation of properties, such as, modulus, strength, or glass transition temperature. Electronics may experience single event effects, gate rupture, burnout of field effect transistors and noise. Presently aluminum is the major component in most of the space structures due to its lightweight and good structural properties. However, aluminum is ineffective at blocking space radiation. Therefore, most of the past research involved studying at polymers which contain large amounts of hydrogen. Again, these materials are not structural materials and would require large amounts of material to achieve the structural properties needed. One of the materials to alleviate this problem is polymeric composite materials, which has good structural properties and use polymers that contained large amounts of hydrogen. This paper presents steps involved in fabrication of multi-functional hybrid sandwich panels that can provide beneficial radiation shielding as well as structural strength. Multifunctional hybrid sandwich panels were manufactured using vacuum assisted resin transfer molding process and were subjected to radiation treatment. Study indicates that various nanoparticles including Boron Nano powder, Boron Carbide and Gadolinium nanoparticles can be successfully used to block the space radiation without sacrificing the structural integrity.

Keywords: multi-functional, polymer composites, radiation shielding, sandwich composites

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Authors: Ummeh Saika, Toshio Kikuchi

Abstract:

Population growth and urbanization is a global phenomenon. As the rapid progress of technology, many cities in the international community are facing serious problems of urbanization. There is no doubt that the urbanization will proceed to have significant impact on the ecology, economy and society at local, regional, and global levels. The inhabitants of Dhaka city suffer from lack of proper urban facilities. The green spaces are needed for different functional and leisure activities of the urban dwellers. Again growing densification, a number of green space are transferred into open space in the Dhaka city. As a result greenery of the city's decreases gradually. Moreover, the existing green space is frequently threatened by encroachment. The role of green space, both at community and city level, is important to improve the natural environment and social ties for future generations. Therefore, it seems that the green space needs to be more effective for public interaction. The main objective of this study is to address the effectiveness of urban green space (Urban Park) of Dhaka City. Two approaches are selected to fulfill the study. Firstly, analyze the long-term spatial changes of urban green space using GIS and secondly, investigate the relationship of urban park network with physical and social environment. The case study site covers eight urban parks of Dhaka metropolitan area of Bangladesh. Two aspects (Physical and Social) are applied for this study. For physical aspect, satellite images and aerial photos of different years are used to find out the changes of urban parks. And for social aspect, methods are used as questionnaire survey, interview, observation, photographs, sketch and previous information of parks to analyze about the social environment of parks. After calculation of all data by descriptive statistics, result is shown by maps using GIS. According to physical size, parks of Dhaka city are classified into four types: Small, Medium, Large and Extra Large parks. The observed result showed that the physical and social environment of urban parks varies with their size. In small size parks physical environment is moderate by newly tree plantation and area expansion. However, in medium size parks physical environment are poor, example- tree decrease, exposed soil increase. On the other hand, physical environment of large size and extra large size parks are in good condition, because of plenty of vegetation and well management. Again based on social environment, in small size parks people mainly come from surroundings area and mainly used as waiting place. In medium-size parks, people come to attend various occasion from different places. In large size and extra large size parks, people come from every part of the city area for tourism purpose. Urban parks are important source of green space. Its influence both physical and social environment of urban area. Nowadays green space area gradually decreases and transfer into open space. The consequence of this research reveals that changes of urban parks influence both physical and social environment and also impact on urban life.

Keywords: physical environment, social environment, urban life, urban parks

Procedia PDF Downloads 406