Search results for: regional anesthesia-analgesia techniques

Authors: Ajit Brindhaban

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Background and Purpose: Computed Tomography (CT) scans have become the largest source of radiation in radiological imaging. The purpose of this study was to compare the quality of pediatric Computed Tomography (CT) images reconstructed using Filtered Back Projection (FBP) with images reconstructed using different strengths of Iterative Reconstruction (IR) technique, and to perform a feasibility study to assess the use of IR techniques as a dose reduction tool. Materials and Methods: An anthropomorphic phantom representing a 5-year old child was scanned, in two stages, using a Siemens Somatom CT unit. In stage one, scans of the head, chest and abdomen were performed using standard protocols recommended by the scanner manufacturer. Images were reconstructed using FBP and 5 different strengths of IR. Contrast-to-Noise Ratios (CNR) were calculated from average CT number and its standard deviation measured in regions of interest created in the lungs, bone, and soft tissues regions of the phantom. Paired t-test and the one-way ANOVA were used to compare the CNR from FBP images with IR images, at p = 0.05 level. The lowest strength value of IR that produced the highest CNR was identified. In the second stage, scans of the head was performed with decreased mA(s) values relative to the increase in CNR compared to the standard FBP protocol. CNR values were compared in this stage using Paired t-test at p = 0.05 level. Results: Images reconstructed using IR technique had higher CNR values (p < 0.01.) in all regions compared to the FBP images, at all strengths of IR. The CNR increased with increasing IR strength of up to 3, in the head and chest images. Increases beyond this strength were insignificant. In abdomen images, CNR continued to increase up to strength 5. The results also indicated that, IR techniques improve CNR by a up to factor of 1.5. Based on the CNR values at strength 3 of IR images and CNR values of FBP images, a reduction in mA(s) of about 20% was identified. The images of the head acquired at 20% reduced mA(s) and reconstructed using IR at strength 3, had similar CNR as FBP images at standard mA(s). In the head scans of the phantom used in this study, it was demonstrated that similar CNR can be achieved even when the mA(s) is reduced by about 20% if IR technique with strength of 3 is used for reconstruction. Conclusions: The IR technique produced better image quality at all strengths of IR in comparison to FBP. IR technique can provide approximately 20% dose reduction in pediatric head CT while maintaining the same image quality as FBP technique.

Keywords: filtered back projection, image quality, iterative reconstruction, pediatric computed tomography imaging

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Mohamed Moustafa, Medhat Abdallah, Ramy Magdy, Ahmed Abdrabou, Mohamed Badr

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The scribe box under study dates back to the old kingdom. It was excavated by the Italian expedition in Qena (1935-1937). The box consists of 2pieces, the lid and the body. The inner side of the lid is decorated with ancient Egyptian inscriptions written with a black pigment. The box was made using several panels assembled together by wooden dowels and secured with plant ropes. The entire box is covered with a red pigment. This study aims to use analytical techniques in order to identify and have deep understanding for the box components. Moreover, the authors were significantly interested in using infrared reflectance transmission imaging (RTI-IR) to improve the hidden inscriptions on the lid. The identification of wood species included in this study. The visual observation and assessment were done to understand the condition of this box. 3Ddimensions and 2D programs were used to illustrate wood joints techniques. Optical microscopy (OM), X-ray diffraction (XRD), X-ray fluorescence portable (XRF) and Fourier Transform Infrared spectroscopy (FTIR) were used in this study in order to identify wood species, remains of insects bodies, red pigment, fibers plant and previous conservation adhesives, also RTI-IR technique was very effective to improve hidden inscriptions. The analysis results proved that wooden panels and dowels were identified as Acacia nilotica, wooden rail was Salix sp. the insects were identified as Lasioderma serricorne and Gibbium psylloids, the red pigment was Hematite, while the fiber plants were linen, previous adhesive was identified as cellulose nitrates. The historical study for the inscriptions proved that it’s a Hieratic writings of a funerary Text. After its transportation from the Egyptian museum storage to the wood conservation laboratory of the Grand Egyptian museum –conservation center (GEM-CC), conservation techniques were applied with high accuracy in order to restore the object including cleaning , consolidating of friable pigments and writings, removal of previous adhesive and reassembly, finally the conservation process that were applied were extremely effective for this box which became ready for display or storage in the grand Egyptian museum.

Keywords: scribe box, hieratic, 3D program, Acacia nilotica, XRD, cellulose nitrate, conservation

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Paradigm Shift

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In an overwhelmingly import oriented content bazaar of Arabian TV industry, Musalsalat stand unique in their indigenousness and mass popularity, being rivalled only by movies and football. The Arabic term ‘Musalsalat’ stands for drama series with episodes of 30-45 minutes duration; the format being close to Latin American Telenovela concept-clear cut stories with definitive endings that permit narrative closures. Traditionally Musalsalat were either situational comedies or religiously inspired. Present-day productions have started addressing historical, creative and socially progressive issues targeting the young and well-travelled audiences. Though these soaps get prime ratings throughout the year, it is during Ramadan, that they become a raving success in securing viewership. That Musalsalat have become paramount Ramadan programming is evident by their dominance on the grid and attracting heavy ad-spend. The number of Musalsalats produced specifically for Ramadan reached over 100 last year with Ramadan TV advertising amounting to USD1, 947bn constituting 21% of the total regional TV Adspend of USD 9,189bn.

Keywords: Musalsalat, drama, pan Arab, television

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Sheila Shahidi

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UV protection by fabrics has recently become a focus of great interest, particularly in connection with environmental degradation or ozone layer depletion. Fabrics provide simple and convenient protection against UV radiation (UVR), but not all fabrics offer sufficient UV protection. To describe the degree of UVR protection offered by clothing materials, the ultraviolet protection factor (UPF) is commonly used. UV-protective fabric can be generated by application of a chemical finish using normal wet-processing methodologies. However, traditional wet-processing techniques are known to consume large quantities of water and energy and may lead to adverse alterations of the bulk properties of the substrate. Recently, usage of plasmas to generate physicochemical surface modifications of textile substrates has become an intriguing approach to replace or enhance conventional wet-processing techniques. In this research work the effect of plasma treatment on UV protection properties of fabrics was investigated. DC magnetron sputtering was used and the parameters of plasma such as gas type, electrodes, time of exposure, power and, etc. were studied. The morphological and chemical properties of samples were analyzed using Scanning Electron Microscope (SEM) and Furrier Transform Infrared Spectroscopy (FTIR), respectively. The transmittance and UPF values of the original and plasma-treated samples were measured using a Shimadzu UV3101 PC (UV–Vis–NIR scanning spectrophotometer, 190–2, 100 nm range). It was concluded that, plasma which is an echo-friendly, cost effective and dry technique is being used in different branches of the industries, and will conquer textile industry in the near future. Also it is promising method for preparation of UV protection textile.

Keywords: fabric, plasma, textile, UV protection

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Authors: Charlotte Lülf

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Migration flows cannot be tackled by single states but need to be addressed as a transnational and international responsibility. However, the current international framework staggers. Widely excluded from legal protection are people that flee from the indiscriminate effects of an armed conflict as well as people fleeing natural disasters. This paper as part of an on-going PhD Project deals with the current and partly contradicting approaches to the protection of so-called war- and climate refugees in the European Union. The analysis will emphasize and evaluate the role of the European judiciary to define, redefine and potentially expand legal protection. Changing jurisprudential practice of national and regional courts will be assessed, as will be their dialogue to interpret the international obligations of human rights law, migration laws and asylum laws in an interacting world.

Keywords: human rights law, asylum law, migration, refugee protection

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Authors: Chokri Slim

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The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.

Keywords: stationarity, cointegration, dynamic models, causality, VECM models

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: A. Sathiya Susuman, Hamisi F. Hamisi

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Background: Many socio-economic and demographic data are age-sex attributed. However, a variety of irregularities and misstatement are noted with respect to age-related data and less to sex data because of its biological differences between the genders. Noting the misstatement/misreporting of age data regardless of its significance importance in demographics and epidemiological studies, this study aims at assessing the quality of 2012 Tanzania Population and Housing Census Results. Methods: Data for the analysis are downloaded from Tanzania National Bureau of Statistics. Age heaping and digit preference were measured using summary indices viz., Whipple’s index, Myers’ blended index, and Age-Sex Accuracy index. Results: The recorded Whipple’s index for both sexes was 154.43; male has the lowest index of about 152.65 while female has the highest index of about 156.07. For Myers’ blended index, the preferences were at digits ‘0’ and ‘5’ while avoidance were at digits ‘1’ and ‘3’ for both sexes. Finally, Age-sex index stood at 59.8 where sex ratio score was 5.82 and age ratio scores were 20.89 and 21.4 for males and female respectively. Conclusion: The evaluation of the 2012 PHC data using the demographic techniques has qualified the data inaccurate as the results of systematic heaping and digit preferences/avoidances. Thus, innovative methods in data collection along with measuring and minimizing errors using statistical techniques should be used to ensure accuracy of age data.

Keywords: age heaping, digit preference/avoidance, summary indices, Whipple’s index, Myer’s index, age-sex accuracy index

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Authors: Markéta Slováková

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The largest share of policy and money within the European Union goes to agriculture. The Union’s Common Agricultural Policy has undergone several transformations in the last five decades, with the main change taking place in the 1990's. This change influenced agriculture in the Czech Republic, inasmuch as the fledgling republic was preparing to join the European Union and adopt its policies. In the 1990s, Czech agriculture passed from a centrally planned economy to a market economy and subsequently adopted the terms of the Common Agricultural Policy. The Czech Republic is also characterized by a significant landscape sphere diversification. Agricultural entrepreneurs in the Czech Republic are still not used the possibility of grants from the European Union. They focus rather on national or regional subsidy titles. Only half of all agricultural entrepreneurs in the Czech Republic use European subsidies. This article focuses on the introduction of the Common Agricultural Policy to the Czech Republic and its subsequent influence on Czech agriculture. It is demonstrated on the implementation rate of the CAP in the EU Member States and the closer focus is on the Czech integration.

Keywords: common agricultural policy, agriculture, European Union, transformation

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Authors: Wiriranai Brilliant Masara

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The African Peace and Security Architecture is widely celebrated and revered as a paragon of the will to address peace and security challenges in Africa. However, like any other institution, it is embedded with operational and institutional challenges that prevent it from effectively carrying out its mandate and turning goals into achieved results. The article examines the fundamental flaws and weaknesses of the African Peace and Security Architecture by focusing on its institutions, norms, instruments, and its relationship to Africa’s Regional Economic Communities. Therefore, the article reviews the flaws of the five elements of the African Peace and Security Architecture which are the Peace and Security Council, Panel of the Wise, Continental Early Warning System, African Standby Force, and Peace Fund.

Keywords: African Union, African Peace and Security Architecture, peace and security council, continental early warning system, African Standby Force, Panel of the Wise, Peace Fund

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Authors: Jianhua Wang, Ying Zhou, Han Guo

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Translation underwent culture turn for more than half a century, which brought translation and its studies beyond intra-texts. Different cultures in recent years have developed towards a translation turn, which made a great contribution to relocate national or local cultures being localized to become regional or global cultures. As China grows quickly economically integrating into the world, it becomes urgent to relate China’s story and disseminate the Chinese culture. Due to the weaknesses and drawbacks of different existing cultural translation theories for Chinese culture to go out, a new perspective on translation turn for the go-out of Chinese culture should be drawn to spread better and disseminate Chinese culture to other countries. Based on the existing cultural translation theories, the equivalence of ideology, style of the translator and agency of the support are proposed to draw a new perspective: an innovative poly-system theory for Chinese culture translation.

Keywords: cultural translation theory, Chinese culture, innovative poly system, global cultures

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Authors: Darusalam, Jorish Hulstijn, Marijn Janssen

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Media has revealed a variety of corruption cases in the regional and local governments all over the world. Many governments pursued many anti-corruption reforms and have created a system of checks and balances. Three types of corruption are faced by citizens; administrative corruption, collusion and extortion. Accountability is one of the benchmarks for building transparent government. The public sector is required to report the results of the programs that have been implemented so that the citizen can judge whether the institution has been working such as economical, efficient and effective. Open Data is offering solutions for the implementation of good governance in organizations who want to be more transparent. In addition, Open Data can create transparency and accountability to the community. The objective of this paper is to build a framework of open data for accountability to combating corruption. This paper will investigate the relationship between open data, and accountability as part of anti-corruption initiatives. This research will investigate the impact of open data implementation on public organization.

Keywords: open data, accountability, anti-corruption, framework

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Authors: R. Nandhini, Gaurab Mudbhari

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Ranging from the field of health care to self-driving cars, machine learning and deep learning algorithms have revolutionized the field with the proper utilization of images and visual-oriented data. Segmentation, regression, classification, clustering, dimensionality reduction, etc., are some of the Machine Learning tasks that helped Machine Learning and Deep Learning models to become state-of-the-art models for the field where images are key datasets. Among these tasks, classification and clustering are essential but difficult because of the intricate and high-dimensional characteristics of image data. This finding examines and assesses advanced techniques in supervised classification and unsupervised clustering for image datasets, emphasizing the relative efficiency of Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Deep Embedded Clustering (DEC), and self-supervised learning approaches. Due to the distinctive structural attributes present in images, conventional methods often fail to effectively capture spatial patterns, resulting in the development of models that utilize more advanced architectures and attention mechanisms. In image classification, we investigated both CNNs and ViTs. One of the most promising models, which is very much known for its ability to detect spatial hierarchies, is CNN, and it serves as a core model in our study. On the other hand, ViT is another model that also serves as a core model, reflecting a modern classification method that uses a self-attention mechanism which makes them more robust as this self-attention mechanism allows them to lean global dependencies in images without relying on convolutional layers. This paper evaluates the performance of these two architectures based on accuracy, precision, recall, and F1-score across different image datasets, analyzing their appropriateness for various categories of images. In the domain of clustering, we assess DEC, Variational Autoencoders (VAEs), and conventional clustering techniques like k-means, which are used on embeddings derived from CNN models. DEC, a prominent model in the field of clustering, has gained the attention of many ML engineers because of its ability to combine feature learning and clustering into a single framework and its main goal is to improve clustering quality through better feature representation. VAEs, on the other hand, are pretty well known for using latent embeddings for grouping similar images without requiring for prior label by utilizing the probabilistic clustering method.

Keywords: machine learning, deep learning, image classification, image clustering

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Authors: Nadia Allouache

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Energy conservation is one of the major concerns in the modern high tech era due to the limited amount of energy resources and the increasing cost of energy. Predicting an efficient use of energy in thermal systems like heat exchangers can only be achieved if the second law of thermodynamics is accounted for. The performance of heat exchangers can be substantially improved by many passive heat transfer augmentation techniques. These letters permit to improve heat transfer rate and to increase exchange surface, but on the other side, they also increase the friction factor associated with the flow. This raises the question of how to employ these passive techniques in order to minimize the useful energy. The objective of this present study is to use a porous substrate attached to the walls as a passive enhancement technique in heat exchangers and to find the compromise between the hydrodynamic and thermal performances under turbulent flow conditions, by using a second law approach. A modified k- ε model is used to simulating the turbulent flow in the porous medium and the turbulent shear flow is accounted for in the entropy generation equation. A numerical modeling, based on the finite volume method is employed for discretizing the governing equations. Effects of several parameters are investigated such as the porous substrate properties and the flow conditions. Results show that under certain conditions of the porous layer thickness, its permeability, and its effective thermal conductivity the minimum rate of entropy production is obtained.

Keywords: second law approach, annular heat exchanger, turbulent flow, porous medium, modified model, numerical analysis

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Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

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The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

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Authors: N. L. Divya Gayatri

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In India, over 377 million urban people generate 62 million tons of municipal solid waste per annum. Forty-three million tons are collected, 11.9 million are treated and 31 million tons is dumped in landfill sites. The study aims to have an overall understanding of the working and functioning of a sanitary landfill from the siting to the closure stage and identifying various landscape design techniques that can be implemented in a landfill site and come up with a set of guidelines by analyzing the existing policies and guidelines pertaining to landfills. Constituents of municipal solid waste, methods of landfilling, issues, impacts, Mitigation strategies, Landscape design strategies, design approaches towards a landfill, infrastructure requirements, end-use opportunities have been discussed. The objective is to study the ecological and environmental degradation prevention methods, compare various techniques in remediation, study issues in landfill sites in India, analyze scope and opportunities and explore various landscape design strategies. The understanding of the function of landfills with respect to Municipal solid waste and landscaping is conveyed through this study. The study is limited to Landscape design factors in landfill design guidelines and policies mentioned with regard to the issues and impacts specific to the Indian context.

Keywords: sanitary landfill landscaping, environmental impact, municipal solid waste, guidelines, landscape design strategies, landscape design approaches

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Authors: Jose A. Romero, Frank Otremba, Alejandro A. Lozano-Guzman

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Road safety is affected by many factors, involving the vehicle, the infrastructure, and the environment. Many efforts have been thus made to improve road safety through rational standards for the different systems involved in freight transportation. Cargo shifting and falling have been recognized as critical and contributive effects for road crashes. To avoid such situations, regional and international standards have been implemented, aiming to prevent such types of cargo-related accidents. In particular, there are specific compulsory standard requirements to maintain the cargo on the vehicle without shifting, when the vehicle performs an emergency braking maneuver. In this paper, a simulation is presented to analyze the effect of the vibration of the cargo on the braking distance of the vehicle. Such vibration can lead to a poor cargo restraining, and higher braking efficiency, as a result of the decoupling of the cargo mass from the vehicle mass. Such higher braking efficiency, on the order of 4.4%, further suggests a greater demand for the current braking standards.

Keywords: road safety, cargo securement, shifting cargo, vehicle dynamics, ABS

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Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

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An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

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Authors: Chung-Hyeon Ryu, Do-Hyoung Kim, Hak-Sung Kim

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As the use of the composites was increased, the detecting method of hidden damages which have an effect on performance of the composite was important. Terahertz (THz) spectroscopy was assessed as one of the new powerful nondestructive evaluation (NDE) techniques for fiber reinforced composite structures because it has many advantages which can overcome the limitations of conventional NDE techniques such as x-rays or ultrasound. The THz wave offers noninvasive, noncontact and nonionizing methods evaluating composite damages, also it gives a broad range of information about the material properties. In additions, it enables to detect the multiple-delaminations of various nonmetallic materials. In this study, the pulse type THz spectroscopy imaging system was devised and used for detecting and evaluating the hidden delamination in the glass fiber reinforced plastic (GFRP) composite laminates. The interaction between THz and the GFRP composite was analyzed respect to the type of delamination, including their thickness, size and numbers of overlaps among multiple-delaminations in through-thickness direction. Both of transmission and reflection configurations were used for evaluation of hidden delaminations and THz wave propagations through the delaminations were also discussed. From these results, various hidden delaminations inside of the GFRP composite were successfully detected using time-domain THz spectroscopy imaging system and also compared to the results of C-scan inspection. It is expected that THz NDE technique will be widely used to evaluate the reliability of composite structures.

Keywords: terahertz, delamination, glass fiber reinforced plastic composites, terahertz spectroscopy

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Authors: Sifatullah Bahij, Safiullah Omary, Francoise Feugeas, Amanullah Faqiri

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Reinforced concrete (RC) is commonly used material in the construction sector, due to its low-cost and durability, and allowed the architectures and designers to construct structural members with different shapes and finishing. Usually, RC members are designed to sustain service loads efficiently without any destruction. However, because of the faults in the design phase, overloading, materials deficiencies, and environmental effects, most of the structural elements will require maintenance and repairing over their lifetime. Therefore, strengthening and repair of the deteriorated and/or existing RC structures are much important to extend their life cycle. Various techniques are existing to retrofit and strengthen RC structural elements such as steel plate bonding, external pre-stressing, section enlargement, fiber reinforced polymer (FRP) wrapping, etc. Although these configurations can successfully improve the load bearing capacity of the beams, they are still prone to corrosion damage which results in failure of the strengthened elements. Therefore, many researchers used fiber reinforced cementitious materials due to its low-cost, corrosion resistance, and result in improvement of the tensile and fatigue behaviors. Various types of cementitious materials have been used to strengthen or repair structural elements. This paper has summarized to accumulate data regarding on previously published research papers concerning the torsional behaviors of RC beams strengthened by various types of cementitious materials.

Keywords: reinforced concrete beams, strengthening techniques, cementitious materials, torsional strength, twisting angle

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Authors: Hala A. Alrumaih

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It is widely believed that mobile device is a promising technology for lending the opportunity for the third wave of electronic commerce. Mobile devices have changed the way companies do business. Many applications are under development or being incorporated into business processes. In this day, mobile applications are a vital component of any industry strategy. One of the greatest benefits of selling merchandise and providing services on a mobile application is that it widens a company’s customer base significantly. Mobile applications are accessible to interested customers across regional and international borders in different electronic business (e-business) area. But there is a dark side to this success story. The security risks associated with mobile devices and applications are very significant. This paper introduces a broad risk analysis for the various threats, vulnerabilities, and risks in mobile e-business applications and presents some important risk mitigation approaches. It reviews and compares two different frameworks for security assurance in mobile e-business applications. Based on the comparison, the paper suggests some recommendations for applications developers and business owners in mobile e-business application development process.

Keywords: e-business, mobile applications, risk mitigations, security assurance

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Authors: Adria Kajenski, Guinevere Strack, Edward Kingsley, Shahriar Khushrushahi, Alkim Akyurtlu

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Radio Frequency (RF) metasurfaces are arrangements of subwavelength elements interacting with electromagnetic radiation. These arrangements affect polarization state, amplitude, and phase of impinged radio waves; for example, metasurface designs are used to produce functional passband and stopband filters. Recent advances in additive manufacturing techniques have enabled the low-cost, rapid fabrication of ultra-thin metasurface elements on flexible substrates such as plastic films, paper, and textiles. Furthermore, scalable manufacturing processes promote the integration of fabric-based RF metasurfaces into the market of sensors and devices within the Internet of Things (IoT). The design and fabrication of metasurfaces on textiles require a multidisciplinary team with expertise in i) textile and materials science, ii) metasurface design and simulation, and iii) metasurface fabrication and testing. In this presentation, we will discuss RF metasurfaces on fabric with an emphasis on how the materials, including fabric and inks, along with fabrication techniques, affect the RF performance. We printed metasurfaces using a direct-write approach onto various woven and non-woven fabrics, as well as on fabrics coated with either thermoplastic or thermoset coatings. Our team also performed a range of tests on the printed structures, including different inks and their curing parameters, wash durability, abrasion resistance, and RF performance over time.

Keywords: electronic textiles, metasurface, printed electronics, flexible

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Authors: Rajkumar Ghosh

Abstract:

Earthquakes are natural disasters that pose a significant risk to human life and infrastructure. Effective earthquake mitigation measures require a thorough understanding of the dynamics of seismic occurrences, including thrust movement. Traditionally, estimating thrust movement has relied on typical techniques that may not capture the full complexity of these events. Therefore, investigating alternative approaches, such as incorporating out-of-sequence thrust movement data, could enhance earthquake mitigation strategies. This review aims to provide an overview of the applications of out-of-sequence thrust movement in earthquake mitigation. By examining existing research and studies, the objective is to understand how precise estimation of thrust movement can contribute to improving structural design, analyzing infrastructure risk, and developing early warning systems. The study demonstrates how to estimate out-of-sequence thrust movement using multiple data sources, including GPS measurements, satellite imagery, and seismic recordings. By analyzing and synthesizing these diverse datasets, researchers can gain a more comprehensive understanding of thrust movement dynamics during seismic occurrences. The review identifies potential advantages of incorporating out-of-sequence data in earthquake mitigation techniques. These include improving the efficiency of structural design, enhancing infrastructure risk analysis, and developing more accurate early warning systems. By considering out-of-sequence thrust movement estimates, researchers and policymakers can make informed decisions to mitigate the impact of earthquakes. This study contributes to the field of seismic monitoring and earthquake risk assessment by highlighting the benefits of incorporating out-of-sequence thrust movement data. By broadening the scope of analysis beyond traditional techniques, researchers can enhance their knowledge of earthquake dynamics and improve the effectiveness of mitigation measures. The study collects data from various sources, including GPS measurements, satellite imagery, and seismic recordings. These datasets are then analyzed using appropriate statistical and computational techniques to estimate out-of-sequence thrust movement. The review integrates findings from multiple studies to provide a comprehensive assessment of the topic. The study concludes that incorporating out-of-sequence thrust movement data can significantly enhance earthquake mitigation measures. By utilizing diverse data sources, researchers and policymakers can gain a more comprehensive understanding of seismic dynamics and make informed decisions. However, challenges exist, such as data quality difficulties, modelling uncertainties, and computational complications. To address these obstacles and improve the accuracy of estimates, further research and advancements in methodology are recommended. Overall, this review serves as a valuable resource for researchers, engineers, and policymakers involved in earthquake mitigation, as it encourages the development of innovative strategies based on a better understanding of thrust movement dynamics.

Keywords: earthquake, out-of-sequence thrust, disaster, human life

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Authors: Muhammad H. Alu’datt, Inteaz Alli

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This study was conducted to prepare and evaluate the biological properties of protein co-precipitates from flaxseed and soybean. Protein was prepared by NaOH extraction through the mixing of soybean flour (Sf) and flaxseed flour (Ff) or mixtures of soybean extract (Se) and flaxseed extract (Fe). The protein co-precipitates were precipitated by isoelectric (IEP) and isoelectric-heating (IEPH) co-precipitation techniques. Effects of extraction and co-precipitation techniques on co-precipitate yield were investigated. Native-PAGE, SDS-PAGE were used to study the molecular characterization. Content and antioxidant activity of extracted free and bound phenolic compounds were evaluated for protein co-precipitates. Removal of free and bound phenolic compounds from protein co-precipitates showed little effects on the electrophoretic behavior of the proteins or the protein subunits of protein co-precipitates. Results showed that he highest protein contents and yield were obtained in for Sf-Ff/IEP co-precipitate with values of 53.28 and 25.58% respectively as compared to protein isolates and other co-precipitates. Results revealed that the Sf-Ff/IEP showed a higher content of bound phenolic compounds (53.49% from total phenolic content) as compared to free phenolic compounds (46.51% from total phenolic content). Antioxidant activities of extracted bound phenolic compounds with and without heat treatment from Sf-Ff/IEHP were higher as compared to free phenolic compounds extracted from other protein co-precipitates (29.68 and 22.84%, respectively).

Keywords: antioxidant, phenol, protein co-precipitate, yield

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Authors: Birome Holo Ba, Christian Prins, Caroline Prodhon

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Optimization is an important aspect of logistics management. It can reduce significantly logistics costs and also be a good tool for decision support. In this paper, we address a planning problem specific to biomass supply chain. We propose a new mixed integer linear programming (MILP) model dealing with different feed stock production operations such as harvesting, packing, storage, pre-processing and transportation, with the objective of minimizing the total logistic cost of the system on a regional basis. It determines the optimal number of harvesting machine, the fleet size of trucks for transportation and the amount of each type of biomass harvested, stored and pre-processed in each period to satisfy demands of refineries in each period. We illustrate the effectiveness of the proposal model with a numerical example, a case study in Aube (France department), which gives preliminary and interesting, results on a small test case.

Keywords: biomass logistics, supply chain, modelling, optimization, bioenergy, biofuels

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Authors: Yilin Liao, Hewen Li, Paula McConvey

Abstract:

Speed skaters often face a risk of concussion when they fall on the ice floor and impact crash mats during practices and competitive races. Several variables, including those related to the skater, the crash mat, and the impact position (body side/head/feet impact), are believed to influence the severity of the skater's concussion. While computer simulation modeling can be employed to analyze these accidents, the simulation process is time-consuming and does not provide rapid information for coaches and teams to assess the skater's injury risk in competitive events. This research paper promotes the exploration of the feasibility of using AI techniques for evaluating skater’s potential concussion severity, and to develop a fast concussion prediction tool using artificial neural networks to reduce the risk of treatment delays for injured skaters. The primary data is collected through virtual tests and physical experiments designed to simulate skater-mat impact. It is then analyzed to identify patterns and correlations; finally, it is used to train and fine-tune the artificial neural networks for accurate prediction. The development of the prediction tool by employing machine learning strategies contributes to the application of AI methods in sports science and has theoretical involvements for using AI techniques in predicting and preventing sports-related injuries.

Keywords: artificial neural networks, concussion, machine learning, impact, speed skater

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Authors: Dereje Moges Azbite

Abstract:

Laboratory analysis of igneous rocks is performed with the help of the main oxide plots. The lithology of the two wells was identified using the main oxides obtained using the XRF method. Twenty-four (24) cutting samples with different degrees of alteration were analyzed to determine and identify the rock types by plotting these well samples on special diagrams and correlating with the regional rocks. The results for the analysis of the main oxides and trace elements of 24 samples are presented. Alteration analysis in the two well samples was conducted for 21 samples from two wells for identifying clay minerals. Bulk sample analysis indicated quartz, illite & micas, calcite, cristobalite, smectite, pyrite, epidote, alunite, chlorite, wairakite, diaspore, and kaolin minerals present in both wells. Hydrothermal clay minerals such as illite, chlorite, smectite, and kaoline minerals were identified in both wells by X-ray diffraction.

Keywords: igneous rocks, major oxides, tracer elements, XRF, XRD, alteration minerals

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