Search results for: large bowel obstruction

Authors: Gopal Lamichhane, Biswash Sapkota, Grinsun Sharma, Mahendra Adhikari

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Urolithiasis is a condition in which insoluble or less soluble salts like oxalate, phosphate etc. precipitate in urinary tract and causes obstruction in ureter resulting renal colic or sometimes haematuria. It is the third most common disorder of urinary tract affecting nearly 2% of world’s population. Poor urinary drainage, microbial infection, oxalate and calcium containing diet, calciferol, hyperparathyroidism, cysteine in urine, gout, dysfunction of intestine, drought environment, lifestyle, exercise, stress etc. are risk factors for urolithiasis. Wide ranges of treatments are available in allopathic system of medicine but reoccurrence is unpreventable even with the surgical removal of stone or lithotripsy. So, people prefer alternative medicinal systems such as Unani, homeopathic, ayurvedic etc. systems of medicine due to their fewer side effects over allopathic counterpart. Different plants based ethnomedicines are being well established by their continuous effective use in human since long time in treatment of urinary problem. Many studies have scientifically proved those ethnomedicines for antiurolithiatic effect in animal and in vitro model. Plant-based remedies were found to be therapeutically effective for both prevention as well as cure of calcium oxalate urolithiasis. Plants were known to show these effects through a combination of many effects such as antioxidant, diuretic, hypocalciuric, urine alkalinizing effect in them. Berberine, triterpenoids, lupeol are the phytochemicals established for antiurolithiatic effect. Hence, plant-based medicine can be the effective herbal alternative as well as means of discovery of novel drug molecule for curing urolithiatic disorder and should be focused on further research to discover their value in coming future.

Keywords: urolithiasis, herbal medicine, ethnomedicine, kidney stone, calcium oxalate

Procedia PDF Downloads 270

Authors: Sajjad Shojaeidoust, Mohsen Ghanbarzadeh, Abdolhamid Habibi

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Exercise-induced bronchospasm (EIB) is a transitory condition of airflow obstruction that is associated with physical activities. It is noted that high ventilation can lead to an increase in the heat and reduce in the moisture in airways resistance of trachea. Also causes of pathophysiological mechanism are EIB. Accordingly, studying some parameters of pulmonary function (FVC, FEV1) among active people seems quintessential. The aim of this study was to analyze bronchospasm following the implementation of a program of maximum aerobic exercise in active men at Chamran University of Ahwaz. Method: In this quasi-experimental study, the population consisted of all students at Chamran University. Among from 55 participants, of which, 15 were randomly selected as the experimental group. In this study, the size of the maximum oxygen consumption was initially measured, and then, based on the maximum oxygen consumed, the active individuals were identified. After five minutes’ warm-up, Strand treadmill exercise test was taken (one session) and pulmonary parameters were measured at both pre- and post-tests (spirometer). After data normalization using KS and non-normality of the data, the Wilcoxon test was used to analyze the data. The significance level for all statistical surveys was considered p≤0/05. Results: The results showed that the ventilation factors and bronchospasm (FVC, FEV1) in the pre-test and post-test resulted in no significant difference among the active people (p≥0/05). Discussion and conclusion: Based on the results observed in this study, it appears that pulmonary indices in active individuals increased after aerobic test. The increase in this indicator in active people is due to increased volume and elasticity of the lungs as well. In other words, pulmonary index is affected by rib muscles. It is considered that progress over respiratory muscle strength and endurance has raised FEV1 in the active cases.

Keywords: aerobic active maximum, bronchospasm, pulmonary function, spirometer

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Authors: Laurentiu Moruz, Jens Kitzhofer, Mircea Dinulescu

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The paper aims to extend the knowledge about jet behavior and jet interaction between five plane unventilated jets with large aspect ratio (AR). The distance between the single plane jets is two times the channel height. The experimental investigation applies 2D Particle Image Velocimetry (PIV) and static pressure measurements. Our study focuses on the influence of two different outlet nozzle geometries (triangular shape with 2 x 7.5° and blunt geometry) with respect to variation of Reynolds number from 5500 - 12000. It is shown that the outlet geometry has a major influence on the jet formation in terms of uniformity of velocity profiles downstream of the sudden expansion. Furthermore, we describe characteristic regions like converging region, merging region and combined region. The triangular outlet geometry generates most uniform velocity distributions in comparison to a blunt outlet nozzle geometry. The blunt outlet geometry shows an unstable behavior where the jets tend to attach to one side of the walls (ceiling) generating a large recirculation region on the opposite side. Static pressure measurements confirm the observation and indicate that the recirculation region is connected to larger pressure drop.

Keywords: 2D particle image velocimetry, parallel jet interaction, pressure drop, sudden expansion

Procedia PDF Downloads 272

Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Yue Shuai Zhao, Rong Ping Shao, Wei Sun, Guo Hua Ren, Yong Wang, Li Chen Sun

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A large-scale cryopump (DN1250) used in large vacuum leak detecting system was designed and its performance experimentally investigated by Beijing Institute of Spacecraft Environment Engineering. The cryopump was cooled by four closed cycle helium refrigerators (two dual stage refrigerators and two single stage refrigerators). Detailed numerical analysis of the heat transfer in the first stage array and the second stage array were performed by using computational fluid dynamic method (CFD). Several design parameters were considered to find the effect on the temperature distribution and the cooldown time. The variation of thermal conductivity and heat capacity with temperature was taken into account. The thermal analysis method based on numerical techniques was introduced in this study, the heat transfer in the first stage array and the second stage cryopanel was carefully analyzed to determine important considerations in the thermal design of the cryopump. A performance test system according to the RNEUROP standards was built to test main performance of the cryopump. The experimental results showed that the structure of first stage array which was optimized by the method could meet the requirement of the cryopump well. The temperature of the cryopanel was down to 10K within 300 min, and the result of the experiment was accordant with theoretical analysis' conclusion. The test also showed that the pumping speed for N2 of the pump was up to 57,000 L/s, and the crossover was over than 300,000 Pa•L.

Keywords: cryopump, temperature distribution, thermal analysis, CFD Simulation

Procedia PDF Downloads 300

Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: Anoush Saadatmehr

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Design and build of large clear span structures have always been demanding in the construction industry targeting industrial and commercial buildings around the world. The function of these spectacular structures encompasses distinguished types of building such as aircraft and airship hangars, warehouses, bulk storage buildings, sports and recreation facilities. From an engineering point of view, there are various types of steel structure systems that are often adopted in large-span buildings like conventional trusses, space frames and cable-supported roofs. However, this paper intends to investigate and review an innovative light, economic and quickly erected large span steel structure renowned as “Stressed-Arch,” which has several advantages over the other common types of structures. This patented system integrates the use of cold-formed hollow section steel material with high-strength pre-stressing strands and concrete grout to establish an arch shape truss frame anywhere there is a requirement to construct a cost-effective column-free space for spans within the range of 60m to 180m. In this study and firstly, the main structural properties of the stressed-arch system and its components are discussed technically. These features include nonlinear behavior of truss chords during stress-erection, the effect of erection method on member’s compressive strength, the rigidity of pre-stressed trusses to overcome strict deflection criteria for cases with roof suspended cranes or specialized front doors and more importantly, the prominent lightness of steel structure. Then, the effects of utilizing pre-stressing strands to safeguard a smooth process of installation of main steel members and roof components and cladding are investigated. In conclusion, it is shown that the Stressed-Arch system not only provides an optimized light steel structure up to 30% lighter than its conventional competitors but also streamlines the process of building erection and minimizes the construction time while preventing the risks of working at height.

Keywords: large span structure, pre-stressed steel truss, stressed-arch building, stress-erection, steel structure

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Authors: Dimitar N. Karastoianov, Stanislav D. Gyoshev, Todor N. Penchev

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Preparation of briquettes of metal chips with good density and quality is of great importance for the efficiency of this process. In this paper are presented the results of impact briquetting of grey cast iron chips with rectangular shape and dimensions 15x25x1 mm. Density and quality of briquettes of these chips are compared with those obtained in another work of the authors using cast iron chips with smaller sizes. It has been found that by using a rectangular chips with a large size are produced briquettes with a very low density and poor quality. From the photographs taken by X-ray tomography, it is clear that the reason for this is the orientation of the chip in the peripheral wall of the briquettes, which does not allow of the air to escape from it. It was concluded that in order to obtain briquettes of cast iron chips with a large size, these chips must first be ground, for example in a small ball mill.

Keywords: briquetting, chips, impact, rocket engine

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology expansion, synthetic dataset, transformer fine-tuning, concept extraction, DOLCE, BERT, taxonomy, LLM, NER

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Authors: Steffen Illig, Alexander S. Eggeman, Alessandro Troisi, Stephen G. Yeates, John E. Anthony, Henning Sirringhaus

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Large-amplitude intermolecular vibrations in combination with complex shaped transfer integrals generate a thermally fluctuating energetic landscape. The resulting dynamic disorder and its intrinsic presence in organic semiconductors is one of the most fundamental differences to their inorganic counterparts. Dynamic disorder is believed to govern many of the unique electrical and optical properties of organic systems. However, the low energy nature of these vibrations makes it difficult to access them experimentally and because of this we still lack clear molecular design rules to control and reduce dynamic disorder. Applying a novel technique based on electron diffraction we encountered strong intermolecular, thermal vibrations in every single organic material we studied (14 up to date), indicating that a large degree of dynamic disorder is a universal phenomenon in organic crystals. In this paper a new molecular design strategy will be presented to avoid dynamic disorder. We found that small molecules that have their side chains attached to the long axis of their conjugated core have been found to be less likely to suffer from dynamic disorder effects. In particular, we demonstrate that 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothio-phene (C8-BTBT) and 2,9-di-decyl-dinaphtho-[2,3-b:20,30-f]-thieno-[3,2-b]-thiophene (C10DNTT) exhibit strongly reduced thermal vibrations in comparison to other molecules and relate their outstanding performance to their lower dynamic disorder. We rationalize the low degree of dynamic disorder in C8-BTBT and C10-DNTT with a better encapsulation of the conjugated cores in the crystal structure which helps reduce large amplitude thermal motions. The work presented in this paper provides a general strategy for the design of new classes of very high mobility organic semiconductors with low dynamic disorder.

Keywords: charge transport, C8-BTBT, C10-DNTT, dynamic disorder, organic semiconductors, thermal vibrations

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Authors: C. J. Coetzee, E. Horn

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One of the main challenges in using the Discrete Element Method (DEM) is to specify the correct input parameter values. In general, the models are sensitive to the input parameter values and accurate results can only be achieved if the correct values are specified. For the linear contact model, micro-parameters such as the particle density, stiffness, coefficient of friction, as well as the particle size and shape distributions are required. There is a need for a procedure to accurately calibrate these parameters before any attempt can be made to accurately model a complete bulk materials handling system. Since DEM is often used to model applications in the mining and quarrying industries, a calibration procedure was developed for materials that consist of relatively large (up to 40 mm in size) particles. A coarse crushed aggregate was used as the test material. Using a specially designed large shear box with a diameter of 590 mm, the confined Young’s modulus (bulk stiffness) and internal friction angle of the material were measured by means of the confined compression test and the direct shear test respectively. DEM models of the experimental setup were developed and the input parameter values were varied iteratively until a close correlation between the experimental and numerical results was achieved. The calibration process was validated by modelling the pull-out of an anchor from a bed of material. The model results compared well with experimental measurement.

Keywords: Discrete Element Method (DEM), calibration, shear box, anchor pull-out

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Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

Procedia PDF Downloads 513

Authors: Ji Eun Shin, Dong Hoon Lim

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Data clustering is a common technique used in data analysis and is used in many applications, such as artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. K-means clustering is a well-known clustering algorithm aiming to cluster a set of data points to a predefined number of clusters. In this paper, we implement K-means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. The main idea is to introduce a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. The experimental results demonstrated that K-means algorithm using RHadoop can scale well and efficiently process large data sets on commodity hardware. We also showed that our K-means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases.

Keywords: big data, combiner, K-means clustering, RHadoop

Procedia PDF Downloads 431

Authors: Jeffrey A. Lavarias, Jessie C. Elauria, Arnold R. Elepano, Engelbert K. Peralta, Delfin C. Suministrado

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Shelling process is one of the primary processes and critical steps in the processing of chocolate or any product that is derived from cocoa beans. It affects the quality of the cocoa nibs in terms of flavor and purity. In the Philippines, small-scale food processor cannot really compete with large scale confectionery manufacturers because of lack of available postharvest facilities that are appropriate to their level of operation. The impact of this study is to provide the needed intervention that will pave the way for cacao farmers of engaging on the advantage of value-adding as way to maximize the economic potential of cacao. Thus, provision and availability of needed postharvest machines like mechanical cacao sheller will revolutionize the current state of cacao industry in the Philippines. A mechanical cacao sheller was developed, fabricated, and evaluated to establish optimum shelling conditions such as moisture content of cocoa beans, clearance where of cocoa beans passes through the breaker section and speed of the breaking mechanism on shelling recovery, shelling efficiency, shelling rate, energy utilization and large nib recovery; To establish the optimum level of shelling parameters of the mechanical sheller. These factors were statistically analyzed using design of experiment by Box and Behnken and Response Surface Methodology (RSM). By maximizing shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization, the optimum shelling conditions were established at moisture content, clearance and breaker speed of 6.5%, 3 millimeters and 1300 rpm, respectively. The optimum values for shelling recovery, shelling efficiency, shelling rate, large nib recovery and minimizing energy utilization were recorded at 86.51%, 99.19%, 21.85kg/hr, 89.75%, and 542.84W, respectively. Experimental values obtained using the optimum conditions were compared with predicted values using predictive models and were found in good agreement.

Keywords: cocoa beans, optimization, RSM, shelling parameters

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Authors: Babar Rasheed, Saad Ghafoor

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Introduction: Idea campaigns are commonly held across organizations for generating employee engagement. The contribution is specifically designed to identify and solve prevalent issues. It is argued that numerous organizations fail to achieve their desired goals despite arranging for such campaigns and investing heavily in them. There are however practices that organizations use to achieve higher degree of effectiveness, and these practices may be up for exploration by research to make them usable for the other organizations. Purpose: The aim of this research is to surface the idea management practices of a leading electric company with global operations. The study involves a large sized, multi site organization that is attributed to have added challenges in terms of managing ideas from employees, in comparison to smaller organizations. The study aims to highlight the factors that are looked at as the idea management team strategies for the campaign, sets terms and rewards for it, makes follow up with the employees and lastly, evaluate and award ideas. Methodology: The study is conducted in a leading electric appliance corporation that has a large number of employees and is based in numerous regions of the world. A total of 7 interviews are carried out involving the chief innovation officer, innovation manager and members of idea management and evaluation teams. The interviews are carried out either on Skype or in-person based on the availability of the interviewee. Findings: While this being a working paper and while the study is under way, it is anticipated that valuable information is being achieved about specific details on how idea management systems are governed and how idea campaigns are carried out. The findings may be particularly useful for innovation consultants as resources they can use to promote idea campaigning. The usefulness of the best practices highlighted as a result is, in any case, the most valuable output of this study.

Keywords: employee engagement, motivation, idea campaigns, large organizations, best practices, employees input, organizational output

Procedia PDF Downloads 169

Authors: Sara Javanmardi, Sepehr Aziziz, Baharak Divband, Masoumeh Firouzamandi

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Post-operative adhesions are the most common cause of intestinal obstruction, female infertility and chronic abdominal pain. We developed a novel approach for preventing post-operative peritoneal adhesions using a biodegradable and thermosensitive curcumin hydrogel in rats. Thirteen male Sprague-Dawley rats were assigned randomly into five groups of six animals each: In SHAM group, the cecum was exteriorized, gently manipulated and sent back into the abdomen. In CONTROL group, the surgical abrasion was performed with no further treatment. In Hydrogel group, surgical abrasion was performed with local application of blank hydrogel (1 mL). In Curcumin group, surgical abrasion was performed with local application of curcumin (1 mL). In CUR/HGEL group, surgical abrasion was performed with local application of curcumin hydrogel (1 mL). On day 10, adhesions were assessed using a standardized scale (Evans model), and samples were collected for the Real-time PCR. Real-time PCR was performed to determine mRNA levels of VCAM-1, ICAM-1 and GAPDH. The macroscopic adhesion intensity showed statistically significant differences between the CUR/HGEL and other groups (P=0.0005). The findings of the present study revealed there were statistically significant differences between the groups regarding adhesion band length and numbers (P<0.0001). The protein and mRNA expression of VCAM-1 and ICAM-1 in secal tissues were significantly down regulated due to curcumin-hydrogel application in CUR/HGEL compared to other groups (p<0.05). The thermosensitive hydrogel could reduce the severity and even prevent formation of intra-abdominal adhesion. Curcumin hydrogel could serve as a potential barrier agent to prevent post-operative peritoneal adhesion in rats.

Keywords: peritoneal adhesion, hydrogel, curcumijn, ICAM-1, VCAM-1

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Authors: Yinwei Lin, Cha'o-Kuang Chen

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In this article, the Laplace Adomian transform method (LADM) and double decomposition method (DDM) are used to solve the annular hyperbolic profile fins with variable thermal conductivity. As the thermal conductivity parameter ε is relatively large, the numerical solution using DDM become incorrect. Moreover, when the terms of DDM are more than seven, the numerical solution using DDM is very complicated. However, the present method can be easily calculated as terms are over seven and has more precisely numerical solutions. As the thermal conductivity parameter ε is relatively large, LADM also has better accuracy than DDM.

Keywords: fins, thermal conductivity, Laplace transform, Adomian, nonlinear

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: Shinn-Dar Wu

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This study aims to synthesize lithium iron phosphate cathode material using a recycling technology involving non-protective gas calcination. The advantages include lower cost and easier production than traditional methods that require a large amount of protective gas. The novel technology may have extensive industrial applications. Given that the traditional gas calcination has a large number of protection free Fe3+ production, this study developed a precursor iron phosphate (Fe2+) material recycling technology and conducted related tests and analyses. It focused on flow field design of calcination and new technology as well as analyzed the best conditions for powder calcination combination. The electrical properties were determined by button batteries and exhibited a capacity of 118 mAh/g (The use of new materials synthesis, capacitance is about 122 mAh/g). The cost reduced to 50% of the original.

Keywords: lithium battery, lithium iron phosphate, calcined technology, recycling technology

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Authors: Loai Abdallah, Malik Yousef

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A domain space for the data should reflect the actual similarity between objects. Since objects belonging to the same cluster usually share some common traits even though their geometric distance might be relatively large. In general, the Euclidean distance of data points that represented by large number of features is not capturing the actual relation between those points. In this study, we propose a new method to construct a different space that is based on clustering to form a new distance metric. The new distance space is based on ensemble clustering (EC). The EC distance space is defined by tracking the membership of the points over multiple runs of clustering algorithm metric. Over this distance, we train the decision trees classifier (DT-EC). The results obtained by applying DT-EC on 10 datasets confirm our hypotheses that embedding the EC space as a distance metric would improve the performance.

Keywords: ensemble clustering, decision trees, classification, K nearest neighbors

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Authors: Azlin Mohd Azmi, Tongming Zhou, Akira Rinoshika, Liang Cheng

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The turbulent structures in the wake (x/d =10 to 60) of a screen cylinder have been reduced to understand the roles of the various structures as evolving downstream by comparing with those obtained in a solid circular cylinder wake at Reynolds number, Re of 7000. Using a wavelet multi-resolution technique, the flow structures are decomposed into a number of wavelet components based on their central frequencies. It is observed that in the solid cylinder wake, large-scale structures (of frequency f0 and 1.2 f0) make the largest contribution to the Reynolds stresses although they start to lose their roles significantly at x/d > 20. In the screen cylinder wake, the intermediate-scale structures (2f0 and 4f0) contribute the most to the Reynolds stresses at x/d =10 before being taken over by the large-scale structures (f0) further downstream.

Keywords: turbulent structure, screen cylinder, vortex, wavelet multi-resolution analysis

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Authors: Y. Fekir, K. Mederbal, M. A. Hammadouche, D. Anteur

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The cultural park of the Ahaggar, occupying a large area of Algeria, is characterized by a rich wetlands area to be preserved and managed both in time and space. The management of a large area, by its complexity, needs large amounts of data, which for the most part, are spatially localized (DEM, satellite images and socio-economic information...), where the use of conventional and traditional methods is quite difficult. The remote sensing, by its efficiency in environmental applications, became an indispensable solution for this kind of studies. Remote sensing imaging data have been very useful in the last decade in very interesting applications. They can aid in several domains such as the detection and identification of diverse wetland surface targets, topographical details, and geological features... In this work, we try to extract automatically wetlands area using multispectral remotely sensed data on-board the Earth Observing 1 (EO-1) and Landsat satellite. Both are high-resolution multispectral imager with a 30 m resolution. The instrument images an interesting surface area. We have used images acquired over the several area of interesting in the National Park of Ahaggar in the south of Algeria. An Extraction Algorithm is applied on the several spectral index obtained from combination of different spectral bands to extract wetlands fraction occupation of land use. The obtained results show an accuracy to distinguish wetlands area from the other lad use themes using a fine exploitation on spectral index.

Keywords: multispectral data, EO1, landsat, wetlands, Ahaggar, Algeria

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Authors: Khaing Yadana Swe, Lillie Dewan

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At present, the cascade PID control is widely used to control the super-heating temperature (main steam temperature). As the main steam temperature has the characteristics of large inertia, large time-delay, and time varying, etc., conventional PID control strategy can not achieve good control performance. In order to overcome the bad performance and deficiencies of main steam temperature control system, Model Free Adaptive Control (MFAC) P cascade control system is proposed in this paper. By substituting MFAC in PID of the main control loop of the main steam temperature control, it can overcome time delays, non-linearity, disturbance and time variation.

Keywords: model-free adaptive control, cascade control, adaptive control, PID

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Authors: R. Alias, A. Kasa, M. R. Taha

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The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200, and 300 kPa. The results show that the peak and residual shear strength decreases as particle size increases.

Keywords: particle size, shear strength, granular material, direct shear test

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Authors: Arnab Roy, P. S. Anil Kumar

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Hall bar magnetic field sensors based on planar hall effect were fabricated from permalloy (Ni¬80Fe20) thin films grown by pulsed laser ablation. As large as 400% planar Hall voltage change was observed for a magnetic field sweep within ±4 Oe, a value comparable with present day TMR sensors at room temperature. A very large planar Hall sensitivity of 1200 Ω/T was measured close to switching fields, which was not obtained so far apart from 2DEG Hall sensors. In summary, a highly sensitive low magnetic field sensor has been constructed which has the added advantage of simple architecture, good signal to noise ratio and robustness.

Keywords: planar hall effect, permalloy, NiFe, pulsed laser ablation, low magnetic field sensor, high sensitivity magnetic field sensor

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Authors: Panadda Rojpibulstit, Suthathip Kittisenachai, Songchan Puthong, Sirikul Manochantr, Pornpen Gamnarai, Sasichai Kangsadalampai, Sittiruk Roytrakul

Abstract:

Hepatocellular carcinoma (HCC) is the most primary hepatic cancer worldwide. Nowadays a targeted therapy via monoclonal antibodies (mAbs) specific to tumor-associated antigen is continually developed in HCC treatment. In this regard, after establishing and consequently exploring Hep88 mAb’s tumoricidal effect on hepatocellular carcinoma cell line (HepG2 cell line), the Hep88 mAb’s specific Ag from both membrane and cytoplasmic fractions of HepG2 cell line was identified by 2-D gel electrophoresis and western blot analysis. After in-gel digestion and subsequent analysis by liquid chromatography-mass spectrometry (LC-MS), mortalin (HSPA9) and alpha-enolase were identified. The recombinant proteins specific to Hep88 mAb were cloned and expressed in E.coli BL21 (DE3). Moreover, alteration of HepG2 and Chang liver cell line after being induced by Hep88 mAb for 1-3 days was investigated using a transmission electron microscope. The result demonstrated that Hep88 mAb can bind to the recombinant mortalin (HSPA9) andalpha-enolase. In addition, gradual appearance of mitochondria vacuolization and endoplasmic reticulum dilatation were observed. Taken together, paraptosis-like programmed cell death (PCD) of HepG2 is induced by binding of mortalin (HSPA9) and alpha-enolase to Hep88 mAb. Mortalin depletion by formation of Hep88 mAb-mortalin (HSPA9) complex might initiate transcription-independent of p53-mediated apoptosis. Additionally, Hep88 mAb-alpha-enolase complex might initiate HepG2 cells energy exhaustion by glycolysis pathway obstruction. These results imply that Hep88 mAb might be a promising tool for development of an effective treatment of HCC in the next decade.

Keywords: Hepatocellular carcinoma, Monoclonal antibody, Paraptosis-like program cell death, Transmission electron microscopy, mortalin (HSPA9), alpha-enolase

Procedia PDF Downloads 356

Authors: Yuri Teterin, Lomali Generdukaev, Dmitry Blagovestnov, Peter Yartcev

Abstract:

Introduction: Under the definition "large biliary stones," we referred to stones over 1.5 cm, in which standard transpapillary litho extraction techniques were unsuccessful. Electrohydraulic and laser contact lithotripsy under SpyGlass control have been actively applied for the last decade in order to improve endoscopic treatment results. Aims and Methods: Between January 2019 and July 2022, the N.V. Sklifosovsky Research Institute of Emergency Care treated 706 patients diagnosed with choledocholithiasis who underwent biliary stones removed from the common bile duct. Of them, in 57 (8, 1%) patients, the use of a Dormia basket or Biliary stone extraction balloon was technically unsuccessful due to the size of the stones (more than 15 mm in diameter), which required their destruction. Mechanical lithotripsy was used in 35 patients, and electrohydraulic and laser lithotripsy under SpyGlass direct visualization system - in 26 patients. Results: The efficiency of mechanical lithotripsy was 72%. Complications in this group were observed in 2 patients. In both cases, on day one after lithotripsy, acute pancreatitis developed, which resolved on day three with conservative therapy (Clavin-Dindo type 2). The efficiency of contact lithotripsy was in 100% of patients. Complications were not observed in this group. Bilirubin level in this group normalized on the 3rd-4th day. Conclusion: Our study showed the efficacy and safety of electrohydraulic and laser lithotripsy under SpyGlass control in a well-defined group of patients with large bile duct stones.

Keywords: contact lithotripsy, choledocholithiasis, SpyGlass, cholangioscopy, laser, electrohydraulic system, ERCP

Procedia PDF Downloads 73

Authors: P. Bauer, K. Mougin, V. Vignal, A. Buch, P. Ponthiaux, D. Faye

Abstract:

Nowadays, noble metallic nanostructures with unique morphology are widely used as new sensors due to their fascinating optical, electronic and catalytic properties. Among various shapes, dendritic nanostructures have attracted much attention because of their large surface-to-volume ratio, high sensitivity and special texture with sharp tips and nanoscale junctions. Several methods have been developed to fabricate those specific structures such as electrodeposition, photochemical way, seed-mediated growth or wet chemical method. The present study deals with a novel approach for a controlled growth pattern-directed organisation of Au flower-like crystals (NFs) deposited onto stainless steel plates to achieve large-scale functional surfaces. This technique consists in the deposition of a soft nanoporous template on which Au NFs are grown by electroplating and seed-mediated method. Size, morphology, and interstructure distance have been controlled by a site selective nucleation process. Dendritic Au nanostructures have appeared as excellent Raman-active candidates due to the presence of very sharp tips of multi-branched Au nanoparticles that leads to a large local field enhancement and a good SERS sensitivity. In addition, these structures have also been used as electrochemical sensors to detect traces of molecules present in a solution. A correlation of the number of active sites on the surface and the current charge by both colorimetric method and cyclic voltammetry of gold structures have allowed a calibration of the system. This device represents a first step for the fabrication of MEMs platform that could ultimately be integrated into a lab-on-chip system. It also opens pathways to several technologically large-scale nanomaterials fabrication such as hierarchically ordered crystal architectures for sensor applications.

Keywords: dendritic, electroplating, gold, template

Procedia PDF Downloads 184

Authors: Foad Vashahi, Shahnaz Rezaei, Jeekeun Lee

Abstract:

Large Eddy Simulation (LES) was performed on a dual counter rotating axial swirler in a confined rectangular configuration. Grids were constructed based on a primary Reynolds Averaged Navier-Stokes (RANS) simulation and then were refined based on the Kolmogorov length scale. Water as cold flow condition was applied and results were compared via Particle Image Velocimetry (PIV) experimental results. The focus was to investigate the flow behavior within the region before the flare and very close to the exit of the swirler. This region contributes to a highly unsteady flow behavior and requires great attention to enhancing the flame stability in gas turbine combustor and swirl burners. The PVC formation within the central core flow is strongly related to the peaks of pressure or axial velocity spectrum and up to two distinct peaks at the swirler mouth could be observed. Here, spectra analysis in iso-thermal condition inside the swirler where the inner swirler dominates the flow, showed a higher potential of instabilities with three to four distinct peaks where moving forward to the exit of swirler the number of peaks is decreased. In addition to this, the central axis corresponds to no peaks of instabilities while further away in the radial direction, several peaks exist.

Keywords: axial counter rotating swirler, large eddy simulation (LES), precessing vortex core (PVC), power spectral density (PSD)

Procedia PDF Downloads 277

Authors: Patrick Nüß

Abstract:

I estimate management opposition against unions in terms of hiring discrimination by a large scale field experiment in the German labor market. The results show that callback rates for union members decrease significantly in the presence of high sectoral union density and large firm size. I further explore how this effect varies with regional and sectoral labor dispute intensity and find that management opposition is stronger when a sector is exposed to an intense labor dispute. There is evidence that the observed management opposition can be explained by sectoral union threat effects. Sectors with lower hiring discrimination have lower coverage of collective agreements, and in the absence of a collective agreement, they are less likely to follow the collective agreement wage setting.

Keywords: trade unions, Industrial relations, management opposition, union threat, labor disputes, field experiments

Procedia PDF Downloads 181