Search results for: food distribution networks

Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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Authors: A. Aarabzadeh, R. Hizaji

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Reinforced Concrete (RC) deep beams are a special type of beams due to their geometry, boundary conditions, and behavior compared to ordinary shallow beams. For example, assumption of a linear strain-stress distribution in the cross section is not valid. Little study has been dedicated to fixed-end RC deep beams. Also, most experimental studies are carried out on simply supported deep beams. Regarding recent tendency for application of deep beams, possibility of using fixed-ended deep beams has been widely increased in structures. Therefore, it seems necessary to investigate the aforementioned structural element in more details. In addition to experimental investigation of a concrete deep beam under cyclic load, different failure mechanisms of fixed-ended deep beams under this type of loading have been evaluated in the present study. The results show that failure mechanisms of deep beams under cyclic loads are quite different from monotonic loads.

Keywords: deep beam, cyclic load, reinforced concrete, fixed-ended

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Authors: Teguh Sugiarto

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Background: The research aims to explore if there is fraud in a financial statement, use the Act stated that Benford's distribution all digits must compare the number will follow the trend of lower number. Research methods: This research uses all the analysis number being in Benford's law. After receiving the results of the analysis of all the digits, the author makes a distinction between implementation using the scale above and below 5%, the rate of occurrence of difference. With the number which have differences in the range of 5%, then can do the follow-up and the detection of the onset of fraud against the financial statements. The findings: From the research that has been done can be drawn the conclusion that the average of all numbers appear in the financial statements, and compare the rates of occurrence of numbers according to the characteristics of Benford's law. About the existence of errors and fraud in the financial statements of PT medco Energy Tbk did not occur. Conclusions: The study concludes that Benford's law can serve as indicator tool in detecting the possibility of in financial statements to case studies of PT Medco Energy Tbk for the fiscal year 2000-2010.

Keywords: Benford law, first digits, all digits number Benford law, financial statement

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Authors: Sun Zhe, Ruggero Micheletto

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The research of neural network is very important for the development of advanced next generation intelligent devices and the medical treatment. The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. For this reason, we made a model with only two coupled neurons and studied the influence of connection strength between them. To emulate the neuronal activity of realistic neurons, we prefer to use the Izhikevich neuron model. This model can simulate the neuron variables accurately and it’s simplicity is very suitable to implement on computers. In this research, the parameter ρ is used to estimate the correlation coefficient between spike train of two coupling neurons.We think the results is very important for figuring out the mechanism between synchronization of coupling neurons and synaptic plasticity. The result also presented the importance of the spike frequency adaptation in complex systems.

Keywords: neural networks, noise, stochastic processes, coupled neurons, correlation coefficient, synchronization, pacemaker, synaptic plasticity

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Authors: Kantha Siddhanth Gujjari, Shaani Singhal, Robert Andrew Danks, Adrian Praeger

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Background: Trigeminal neuralgia (TN) is a heterogenous pain syndrome characterised by short paroxysms of lancinating facial pain in the distribution of the trigeminal nerve, often triggered by usually innocuous stimuli. TN has a low prevalence of less than 0.1%, of which 80% to 90% is caused by compression of the trigeminal nerve from an adjacent artery or vein. The root entry zone of the trigeminal nerve is most sensitive to neurovascular conflict (NVC), causing dysmyelination. Whilst microvascular decompression (MVD) is an effective treatment for TN with NVC, all patients do not achieve long-term pain relief. Pre-operative scoring systems by Panczykowski and Hardaway have been proposed but have not been externally validated. These pre-operative scoring systems are composite scores calculated according to a subtype of TN, presence and degree of neurovascular conflict, and response to medical treatments. There is discordance in the assessment of NVC identified on pre-operative magnetic resonance imaging (MRI) between neurosurgeons and radiologists. To our best knowledge, the prognostic impact for MVD of this difference of interpretation has not previously been investigated in the form of a composite scoring system such as those suggested by Panczykowski and Hardaway. Aims: This study aims to identify prognostic factors and externally validate the proposed scoring systems by Panczykowski and Hardaway for TN. A secondary aim is to investigate the prognostic difference between a neurosurgeon's interpretation of NVC on MRI compared with a radiologist’s. Methods: This retrospective cohort study included 95 patients who underwent de novo MVD in a single neurosurgical unit in Melbourne. Data was recorded from patients’ hospital records and neurosurgeon’s correspondence from perioperative clinic reviews. Patient demographics, type of TN, distribution of TN, response to carbamazepine, neurosurgeon, and radiologist interpretation of NVC on MRI, were clearly described prospectively and preoperatively in the correspondence. Scoring systems published by Panczykowski et al. and Hardaway et al. were used to determine composite scores, which were compared with the recurrence of TN recorded during follow-up over 1-year. Categorical data analysed using Pearson chi-square testing. Independent numerical and nominal data analysed with logistical regression. Results: Logistical regression showed that a Panczykowski composite score of greater than 3 points was associated with a higher likelihood of pain-free outcome 1-year post-MVD with an OR 1.81 (95%CI 1.41-2.61, p=0.032). The composite score using neurosurgeon’s impression of NVC had an OR 2.96 (95%CI 2.28-3.31, p=0.048). A Hardaway composite score of greater than 2 points was associated with a higher likelihood of pain-free outcome 1 year post-MVD with an OR 3.41 (95%CI 2.58-4.37, p=0.028). The composite score using neurosurgeon’s impression of NVC had an OR 3.96 (95%CI 3.01-4.65, p=0.042). Conclusion: Composite scores developed by Panczykowski and Hardaway were validated for the prediction of response to MVD in TN. A composite score based on the neurosurgeon’s interpretation of NVC on MRI, when compared with the radiologist’s had a greater correlation with pain-free outcomes 1 year post-MVD.

Keywords: de novo microvascular decompression, neurovascular conflict, prognosis, trigeminal neuralgia

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Authors: J. M. Lee, W. R. Noh, C. Y. Kim, M. G. Lee

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Delamination of oxide scale has been often discovered at the interface between Fe carbon steel and oxide scale. Among several mechanisms of this delamination behavior, the normal tensile stress to the substrate-scale interface has been described as one of the main factors. The stress distribution at the interface is also known to be affected by thermal expansion mismatch between substrate and oxide scale, creep behavior during cooling and the geometry of the interface. In this study, stress states near the interface in a Fe carbon steel with oxide scale have been investigated using FE simulations. The thermal and mechanical properties of oxide scales are indicated in literature and Fe carbon steel is measured using tensile testing machine. In particular, the normal and shear stress components developed at the interface during bending are investigated. Preliminary numerical sensitivity analyses are provided to explain the effects of the interface geometry and oxide thickness on the delamination behavior.

Keywords: oxide scale, delamination, Fe analysis, roughness, thickness, stress state

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Authors: Salwa Salman

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On February 2016, Egypt’s President Abdel Fattah Al-Sisi ordered the former Prime Minister, Ibrahim Mehleb, to establish a committee responsible for retrieving looted state lands or providing squatters with land titles according to their individual cases. The specificity of desert lands emerges from its unique position in both Islamic law and Egypt’s Civil Code. In Egypt, desert lands can be transferred to private ownership through peaceful occupation and cultivation. This study explores the (re-) conceptualization of land rights, state territoriality, and sovereignty as a part of an emerging narrative on informal land tenure. Through the lens of an informal settlement, the study employs methodological insights from studies in the anthropology of development and their interpretation of Foucauldian discourse analysis to examine official representations on squatting over state lands and put them in conversation with individual narratives on land ownership and dispossession. It also employs Bruno Latour’s actor-network theory to explore the development of social networks through primary land contracts and informal local resource management.

Keywords: State lands, squatter community, Islamic law, Egypt’s Civil Code

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of decode and forward (DF) multihop free space optical (FSO) scheme deploying multiple input multiple output (MIMO) configuration under gamma-gamma (GG) statistical distribution, that adopts M-ary pulse position modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of symbol-error rates (SERs) respectively. The probability density function (PDF)’s closed-form formula is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, multiple-input multiple-output, M-ary pulse position modulation, symbol error rate

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Authors: Vamsi Krishna Movva

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Artificial intelligence (AI) has revolutionized traffic management in modern cities by enhancing efficiency, safety, and sustainability. This study explores the transformative role of AI-driven systems, including adaptive traffic lights, real-time incident detection, and coordinated signals, in improving urban traffic flow. Additionally, AI-powered navigation systems utilizing real-time GPS and sensor data offer more efficient and safer travel options. This study employs a mixed-methods approach combining quantitative traffic data analysis and qualitative surveys from traffic management authorities. The study also delves into AI’s application in law enforcement, monitoring traffic violations, detecting distracted driving, and reconstructing accidents to analyze causes and responsibilities. Furthermore, the research highlights the environmental and economic benefits of AI in traffic management, such as reduced emissions and energy savings, while addressing challenges like data privacy concerns and high implementation costs. Ultimately, this paper emphasizes AI’s potential to shape sustainable traffic systems and promote efficient transportation networks.

Keywords: artificial intelligence, traffic management, urban congestion, traffic safety, real-time data

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Authors: Salma Aboussalam, Karima Khalil, Khalid Elkalay

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An Ecopath model was employed to investigate the trophic structure, function, and current state of the Moroccan Mediterranean Sea ecosystem. The model incorporated 31 functional groups, including 21 fish species, 7 invertebrates, 2 primary producers, and a detritus group. The trophic interactions among these groups were analyzed, revealing an average trophic transfer efficiency of 23%. The results indicated that the ecosystem produced more energy than it consumed, with high respiration and consumption rates. Indicators of stability and development were low for the Finn cycle index (13.97), system omnivory index (0.18), and average Finn path length (3.09), indicating a disturbed ecosystem with a linear trophic structure. Keystone species were identified through the use of the keystone index and mixed trophic impact analysis, with demersal invertebrates, zooplankton, and cephalopods found to have a significant impact on other groups.

Keywords: Ecopath, food web, trophic flux, Moroccan Mediterranean Sea

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Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: Swarna Pundir, Prabuddha Hans

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As AI has already stepped into the daily life of human society, one cannot be ignorant about the data it collects and used it to provide a quality of services depending up on the individuals’ choices. It also helps in giving option for making decision Vs choice selection with a calculation based on the history of our search criteria. Over the past decade or so, the way Artificial Intelligence (AI) has impacted society is undoubtedly large.AI has changed the way we shop, the way we entertain and challenge ourselves, the way information is handled, and has automated some sections of our life. We have answered as to what AI is, but not why one may see it as useful. AI is useful because it is capable of learning and predicting outcomes, using Machine Learning (ML) and Deep Learning (DL) with the help of Artificial Neural Networks (ANN). AI can also be a system that can act like humans. One of the major impacts be Joblessness through automation via AI which is seen mostly in manufacturing sectors, especially in the routine manual and blue-collar occupations and those without a college degree. It raises some serious concerns about AI in regards of less employment, ethics in making moral decisions, Individuals privacy, human judgement’s, natural emotions, biased decisions, discrimination. So, the question is if an error occurs who will be responsible, or it will be just waved off as a “Machine Error”, with no one taking the responsibility of any wrongdoing, it is essential to form some rules for using the AI where both machines and humans are involved.

Keywords: AI, ML, DL, ANN

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Authors: Ayesha M. Facey

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The evaluation sought to determine the factors associated with the high failure rate among students taking a first-year introductory statistics course. By utilizing Tyler’s Objective Based Model, the main objectives were: to assess the effectiveness of the lecturer’s teaching strategies; to determine the proportion of students who attends lectures and tutorials frequently and to determine the impact of infrequent attendance on performance; to determine how the assigned activities assisted in students understanding of the course content; to ascertain the possible issues being faced by students in understanding the course material and obtain possible solutions to the challenges and to determine whether the learning outcomes have been achieved based on an assessment of the second in-course examination. A quantitative survey research strategy was employed and the study population was students enrolled in semester one of the academic year 2015/2016. A convenience sampling approach was employed resulting in a sample of 98 students. Primary data was collected using self-administered questionnaires over a one-week period. Secondary data was obtained from the results of the second in-course examination. Data were entered and analyzed in SPSS version 22 and both univariate and bivariate analyses were conducted on the information obtained from the questionnaires. Univariate analyses provided description of the sample through means, standard deviations and percentages while bivariate analyses were done using Spearman’s Rho correlation coefficient and Chi-square analyses. For secondary data, an item analysis was performed to obtain the reliability of the examination questions, difficulty index and discriminant index. The examination results also provided information on the weak areas of the students and highlighted the learning outcomes that were not achieved. Findings revealed that students were more likely to participate in lectures than tutorials and that attendance was high for both lectures and tutorials. There was a significant relationship between participation in lectures and performance on examination. However, a high proportion of students has been absent from three or more tutorials as well as lectures. A higher proportion of students indicated that they completed the assignments obtained from the lectures sometimes while they rarely completed tutorial worksheets. Students who were more likely to complete their assignments were significantly more likely to perform well on their examination. Additionally, students faced a number of challenges in understanding the course content and the topics of probability, binomial distribution and normal distribution were the most challenging. The item analysis also highlighted these topics as problem areas. Problems doing mathematics and application and analyses were their major challenges faced by students and most students indicated that some of the challenges could be alleviated if additional examples were worked in lectures and they were given more time to solve questions. Analysis of the examination results showed that a number of learning outcomes were not achieved for a number of topics. Based on the findings recommendations were made that suggested adjustments to grade allocations, delivery of lectures and methods of assessment.

Keywords: evaluation, item analysis, Tyler’s objective based model, university statistics

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Muhammad Ramzan

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A mathematical model has been envisaged to discuss three-dimensional Viscoelastic fluid flow with an effect of Cattaneo-Christov heat flux in attendance of magnetohydrodynamic (MHD). Variable thermal conductivity with the impact of homogeneous-heterogeneous reactions and convective boundary condition is also taken into account. Homotopy analysis method is engaged to obtain series solutions. Graphical illustrations depicting behaviour of sundry parameters on skin friction coefficient and all involved distributions are also given. It is observed that velocity components are decreasing functions of Viscoelastic fluid parameter. Furthermore, strength of homogeneous and heterogeneous reactions have opposite effects on concentration distribution. A comparison with a published paper has also been established and an excellent agreement is obtained; hence reliable results are being presented.

Keywords: Cattaneo Christov heat flux, homogenous-heterogeneous reactions, magnetic field, variable thermal conductivity

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Authors: Esmeralda Hysenbelliu

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Over the last years, the demand for high bandwidth services, such as live (IPTV Service) and on-demand video streaming, steadily and rapidly increased. It has been predicted that video traffic (IPTV, VoD, and WEB TV) will account more than 90% of global Internet Protocol traffic that will cross the globe in 2016. Consequently, the importance and consideration on requirements and challenges of service providers faced today in supporting user’s requests for entertainment video across the various IPTV services through virtualization over Software Defined Networks (SDN), is tremendous in the highest stage of attention. What is necessarily required, is to deliver optimized live and on-demand services like Internet Protocol Service (IPTV Service) with low cost and good quality by strictly fulfill the essential requirements of Clients and ISP’s (Internet Service Provider’s) in the same time. The aim of this study is to present an overview of the important requirements and challenges of IPTV service with two network trends on solving challenges through virtualization (SDN and Network Function Virtualization). This paper provides an overview of researches published in the last five years.

Keywords: challenges, IPTV service, requirements, software defined networking (SDN)

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Luana Parisi, Sohrab Donyavi

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Cities have become the nodes of global networks, standing at the intersection points of the flows of capital, goods, workers, businesses and travellers, making them the spots where innovation, progress and economic development occur. The primary challenge for them is to create the most fertile ecosystems for triggering innovation activities. Design emerges as an essential feature in this process of laboratorisation of cities. This paper aims at exploring the spatial hubs of transformation within the knowledge economy, providing an overview of the current models of innovation spaces, before focusing on the innovation district of one of the cities that are riding the innovation wave, namely, Boston, USA. Useful lessons will be drawn from the case study of the innovation district in Boston, allowing to define precious tools for policymakers, in the form of a range of factors that define the broad strategy able to implement the model successfully. A mixed methodology is implemented, including information from observations, exploratory interviews to key stakeholders and on-desk data.

Keywords: Innovation District, innovation ecosystem, economic development, urban regeneration

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Authors: Kate Smith, Shuming Liu, Yi Liu, Dragan Savic, Gustaf Olsson, Tian Chang, Xue Wu

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In a water supply system, a great deal of care goes into sourcing, treating and delivering water to consumers, but less thought is given to the energy consumed during these processes. This study uses 2011 data to quantify energy use for urban water supply in China and investigates population density as a possible influencing factor. The objective is to provide information that can be used to develop energy-conscious water infrastructure policy, calculate the energy co-benefits of water conservation and compare energy use between China and other countries. The average electrical energy intensity and per capita electrical energy consumption for urban water supply in China in 2011 were 0.29 kWh/m3 and 33.2 kWh/cap•yr, respectively. Comparison between provinces revealed a direct correlation between energy intensity of urban water supply and population served per unit length of pipe. This could imply energy intensity is lower when more densely populated areas are supplied by relatively dense networks of pipes. This study also found that whereas the percentage of energy used for urban water supply tends to increase with the percentage of population served this increase is slower where water supply is more energy efficient and where a larger percentage of population is already supplied.

Keywords: china, electrical energy use, water-energy nexus, water supply

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Authors: Homayun Ghasemi, Mojtaba Yousefirad, Mozhgan Farzamisepehr

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Heavy metals are among soil pollutant resources that in case of accumulation in the soil and absorption by the plant, enter into the food chain and poison the plants or the people who consume those plants. This research was performed in order to examine the role of cadmium as a heavy metal in the activity of catalase and peroxidase as well as protein concentration in Trifolium resupinatum L. based on a randomized block design with three repetitions. The used treatments included consumption of Cd (NO3)2 at four levels, namely, 0, 100, 200, and 300 ppm. The plants under study were treated for 10 days. The results of the study showed that catalase activity decreased by the increase of cadmium. Moreover, peroxidase activity increased by an increase inthe consumption of cadmium. The analysis of protein level showed that plantlet protein decreased in high cadmium concentrations. The findings also demonstrated that cadmium concentration in roots was higher than in shoots.

Keywords: catalase, heavy metal, peroxidase, protein

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Mohamed Fredj, Abdallah Hafsaoui, Radouane Nakache

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The study of the stability of the mining works in rock masses fractured is the major concern of the operating engineer. For geotechnical works in mines and quarries, it there is not today's general methodology for analysis and the quantification of the risks relating to the dangers inherent in these concrete types (falling boulders, landslides, etc.). The reasons for this are uncertainty, which weighs on available data or lack of knowledge of the values of the parameters required for this analysis type. Stability calculations must be based on reliable knowledge of the distribution of discontinuities that dissect the Rocky massif and the resistance to shear of the intact rock and discontinuities. This study is aimed to study the stability of slope of mine (Kef Sennoun - Tebessa, Algeria). The problem is analyzed using a numerical model based on the finite elements (software Plaxis 3D).

Keywords: stability, discontinuities, finite elements, rock mass, open-pit mine

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Authors: Kanchan Mondal, Adam Sims, Madhav Soti, Jitendra Gautam, David Carron

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Fischer-Tropsch (FT) synthesis is a complex series of heterogeneous reactions between CO and H2 molecules (present in the syngas) on the surface of an active catalyst (Co, Fe, Ru, Ni, etc.) to produce gaseous, liquid, and waxy hydrocarbons. This product is composed of paraffins, olefins, and oxygenated compounds. The key challenge in applying the Fischer-Tropsch process to produce transportation fuels is to make the capital and production costs economically feasible relative to the comparative cost of existing petroleum resources. To meet this challenge, it is imperative to enhance the CO conversion while maximizing carbon selectivity towards the desired liquid hydrocarbon ranges (i.e. reduction in CH4 and CO2 selectivities) at high throughputs. At the same time, it is equally essential to increase the catalyst robustness and longevity without sacrificing catalyst activity. This paper focuses on process development to achieve the above. The paper describes the influence of operating parameters on Fischer Tropsch synthesis (FTS) from coal derived syngas in supercritical carbon dioxide (ScCO2). In addition, the unreacted gas and solvent recycle was incorporated and the effect of unreacted feed recycle was evaluated. It was expected that with the recycle, the feed rate can be increased. The increase in conversion and liquid selectivity accompanied by the production of narrower carbon number distribution in the product suggest that higher flow rates can and should be used when incorporating exit gas recycle. It was observed that this process was capable of enhancing the hydrocarbon selectivity (nearly 98 % CO conversion), reducing improving the carbon efficiency from 17 % to 51 % in a once through process and further converting 16 % CO2 to liquid with integrated recycle of the product gas stream and increasing the life of the catalyst. Catalyst robustness enhancement has been attributed to the absorption of heat of reaction by the compressed CO2 which reduced the formation of hotspots and the dissolution of waxes by the CO2 solvent which reduced the blinding of active sites. In addition, the recycling the product gas stream reduced the reactor footprint to one-fourth of the once through size and product fractionation utilizing the solvent effects of supercritical CO2 were realized. In addition to the negative CO2 selectivities, methane production was also inhibited and was limited to less than 1.5%. The effect of the process conditions on the life of the catalysts will also be presented. Fe based catalysts are known to have a high proclivity for producing CO2 during FTS. The data of the product spectrum and selectivity on Co and Fe-Co based catalysts as well as those obtained from commercial sources will also be presented. The measurable decision criteria were the increase in CO conversion at H2:CO ratio of 1:1 (as commonly found in coal gasification product stream) in supercritical phase as compared to gas phase reaction, decrease in CO2 and CH4 selectivity, overall liquid product distribution, and finally an increase in the life of the catalysts.

Keywords: carbon efficiency, Fischer Tropsch synthesis, low GHG, pressure tunable fractionation

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Authors: Alexander Hempfing

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The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

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Authors: Eduardo Padilla, Luis Daniel Rodriguez, Ivan Sanchez, Angelica Sofia Go

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The synthesis and application of metallic nanoparticles have increased in recent years. Biological methods go beyond the chemical and physical synthesis that is expensive and not friendly to the environment. Therefore, in this study, silver nanoparticles were synthesized biologically in an environmentally friendly way by Handroanthus chrysanthus flower aqueous extract (AgNPs) that contains phytochemicals capable of reducing silver nitrate. AgNPs were characterized visually by UV-visible spectroscopy and TEM. The antimicrobial activity of the AgNPs was tested by determining the minimum inhibitory concentration (MIC), and minimal bactericidal concentration (MBC) in Escherichia coli and Staphylococcus aureus strains AgNPs showed potent antimicrobial activity against gram-negative and gram-positive bacteria. MIC and MBC values were as low as 41.6, and 83.2 ug/mL using AgNPs biosynthesized by H. chrysanthus flower extract. This nanoparticle could be the basis for the formulation of disinfectants for use in the food and pharmaceutical industry.

Keywords: antimicrobial, silver nanoparticles, flower extract, Handroanthus

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Authors: Essam Al Daoud

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Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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Authors: H. Al-Jabli

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The research on the presence of heavy metals and bromate in drinking water is of immense scientific significance due to the potential risks these substances pose to public health. These contaminants are subject to regulatory limits outlined by the National Primary Drinking Water Regulations. Through a comprehensive analysis involving the compilation of existing data and the collection of new data via water sampling in residential areas of Kuwait, the aim is to create detailed maps illustrating the spatial distribution of these substances. Furthermore, the investigation will utilize GRAPHER software to explore correlations among different chemical parameters. By implementing rigorous scientific methodologies, the research will provide valuable insights for the Ministry of Electricity and Water and the Ministry of Health. These insights can inform evidence-based decision-making, facilitate the implementation of corrective measures, and support strategic planning for future infrastructure activities.

Keywords: heavy metals, bromate, ozonation, GIS

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Authors: Yongzheng Li, Hongfang Ma, Qiwen Sun, Haitao Zhang, Weiyong Ying

Abstract:

Radial profiles of particle velocities were investigated in a 6.1 m tall methanol-to-olefins cold model experimental device using a TSI laser Doppler velocimeter. The measurement of axial levels was conducted in the full developed region. The effect of axial level on flow development was not obvious under the same operating condition. Superficial gas velocity and solid circulating rate had significant influence on particle velocity in the center region of the riser. Besides, comparisons between upward, downward and average particle velocity were conducted. The average particle velocity was close to upward velocity and higher than downward velocity in radial locations except the wall region of riser.

Keywords: circulating fluidized bed, laser doppler velocimeter, particle velocity, radial profile

Procedia PDF Downloads 374

Authors: N. Ahmadi, H. Yousefnia, A. Bahrami-Samani

Abstract:

Chitosan is a natural and biodegradable polysaccharide with special characteristic for application in intracavital therapy. 166Ho-chitosan has been reported for the treatment of hepatocellular carcinoma and RSV with promising results. The aim of this study was to prepare 186/188Re-chitosan for radiosynovectomy purposes and investigate the probability of its leakage from the knee joint. 186/188Re was produced by neutron irradiation of the natural rhenium in a research reactor. Chemical processing was performed to obtain (186/188Re)-NaReO4- according to the IAEA manual. A stock solution of chitosan was prepared by dissolving in 1 % acetic acid aqueous solution (10 mg/mL). 1.5 mL of this stock solution was added to the vial containing the activity and the mixture was stirred for 5 min in the room temperature. The radiochemical purity of the complex was checked by the ITLC method, showing the purity of higher than 98%. Distribution of the radiolabeled complex was determined after intra-articular injection into the knees of rats. Excellent retention was observed in the joint with approximately no activity in the other organs.

Keywords: chitosan, leakage, radiosynovectomy, rhenium

Procedia PDF Downloads 345

Authors: S. N. Al-Bahry, S. K. Al-Musharafi, I. Y. Mahmoud

Abstract:

Recycled treated sewage effluents (TSE) is used for agriculture, Public park irrigation and industrial purposes. TSE was found to play a major role in the distribution of antibiotic resistant bacteria into the environment. Fecal coliform and enterococci counts were significantly higher during summer compared to winter seasons. Oman has low annual rainfall with annual average temperature varied between 15-45oC. The main source of potable water is from seawater desalination. Resistance of the isolates to 10 antibiotics (Amikacin, Ampicillin, chloramphenicol, gentamycine, minocylin, nalidixicacid, neomycin, streptomycin, Tetracycline, Tobramycin, and Trimethoprim) was tested. Both fecal coliforms and enterococci were multiple resistant to 2-10 antibiotics. However, temperature variation during summer and winter did not affect resistance of the isolates to antibiotics. The significance of this investigation may be indicator to the environmental TSE pollution.

Keywords: antibiotic resistance, bacteria, environment, sewage treated effluent

Procedia PDF Downloads 418