Search results for: drug prediction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4191

Search results for: drug prediction

2121 Risk Factors’ Analysis on Shanghai Carbon Trading

Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

Abstract:

First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

Procedia PDF Downloads 391
2120 Searching for Novel Scaffolds of Triazole Non-Nucleoside Inhibitors of HIV-1 Reverse Transcriptase

Authors: Tomasz Frączek, Agata Paneth, Rafał Kamiński, Agnieszka Krakowiak, Piotr Paneth

Abstract:

Azoles are a promising class of the new generation of HIV-1 nonnucleoside reverse transcriptase inhibitors (NNRTIs). From thousands of reported compounds, many possess the same basic structure of an aryl substituted azole ring linked by a thioglycolamide chain with another aromatic ring. To find novel extensions for this primary scaffold, we explored the 5-position substitution of triazole NNRTIs using molecular docking followed by synthesis of selected compounds. We discovered that heterocyclic substituents in 5-position of the triazole ring are detrimental to the inhibitory activity of compounds with 4-membered thioglycolamide linker. This substitution seems to be viable only for compounds with a shorter 2-membered linker such as in derivatives of 4‐benzyl‐3‐(benzyl-sulfanyl)‐5‐(thiophen‐2‐yl)‐4H‐1,2,4‐triazole reported earlier. A new scaffold of 2‐[(4‐benzyl‐5‐methyl‐4H‐1,2,4‐triazol‐3‐yl)sulfanyl]‐N‐phenylacetamide has been identified in this study.

Keywords: docking, molecular modeling, drug design, novel scaffolds

Procedia PDF Downloads 542
2119 Partially-Averaged Navier-Stokes for Computations of Flow Around Three-Dimensional Ahmed Bodies

Authors: Maryam Mirzaei, Sinisa Krajnovic´

Abstract:

The paper reports a study about the prediction of flows around simplified vehicles using Partially-Averaged Navier-Stokes (PANS). Numerical simulations are performed for two simplified vehicles: A slanted-back Ahmed body at Re=30 000 and a square back Ahmed body at Re=300 000. A comparison of the resolved and modeled physical flow scales is made with corresponding LES and experimental data for a better understanding of the performance of the PANS model. The PANS model is compared for coarse and fine grid resolutions and it is indicated that even a coarse-grid PANS simulation is able to produce fairly close flow predictions to those from a well-resolved LES simulation. The results indicate the possibility of improvement of the predictions by employing a finer grid resolution.

Keywords: partially-averaged Navier-Stokes, large eddy simulation, PANS, LES, Ahmed body

Procedia PDF Downloads 600
2118 Polysulfide as Active ‘Stealth’ Polymers with Additional Anti-Inflammatory Activity

Authors: Farah El Mohtadi, Richard d'Arcy, Nicola Tirelli

Abstract:

Since 40 years, poly (ethylene glycol) (PEG) has been the gold standard in biomaterials and drug delivery, because of its combination of chemical and biological inertness. However, the possibility of its breakdown under oxidative conditions and the demonstrated development of anti-PEG antibodies highlight the necessity to develop carriers based on materials with increased stability in a challenging biological environment. Here, we describe the synthesis of polysulfide via anionic ring-opening polymerization. In vitro, the synthesized polymer was characterized by low toxicity and a level of complement activation (in human plasma) and macrophage uptake slightly lower than PEG and poly (2‐methyl-2‐oxazoline) (PMOX), of a similar size. Importantly, and differently from PEG, on activated macrophages, the synthesized polymer showed a strong and dose-dependent ROS scavenging activity, which resulted in the corresponding reduction of cytokine production. Therefore, the results from these studies show that polysulfide is highly biocompatible and are potential candidates to be used as an alternative to PEG for various applications in nanomedicine.

Keywords: PEG, low toxicity, ROS scavenging, biocompatible

Procedia PDF Downloads 130
2117 Reliability of Cores Test Result at Elevated Temperature in Case of High Strength Concrete (HSC)

Authors: Waqas Ali

Abstract:

Concrete is broadly used as a structural material in the construction of buildings. When the concrete is exposed to elevated temperature, its strength evaluation is very necessary in the existing structure. In this study, the effect of temperature and the reliability of the core test has been evaluated. For this purpose, the cylindrical cores were extracted from High strength concrete (HSC) specimens that were exposed to the temperature ranging from 300 ℃ to 900 ℃ with a constant duration of 4 hr. This study compares the difference between the standard heated cylinders and the cores taken from them after curing of 90 days. The difference of cylindrical control and binary mix samples and extracted cores revealed that there is 12.19 and 12.38% difference at 300℃, while this difference was found to increase up to 12.89%, 13.03% at 500 ℃. Furthermore, this value is recorded as 12.99%, 13.57% and 14.40%, 14.38% at 700 ℃ and 900 ℃, respectively. A total of four equations were developed through a regression model for the prediction of the strength of concrete for both standard cylinders and extracted cores whose R square values were 0.9733, 0.9627 and 0.9473, 0.9452, respectively.

Keywords: high strength, temperature, core, reliability

Procedia PDF Downloads 73
2116 AI-Driven Strategies for Sustainable Electronics Repair: A Case Study in Energy Efficiency

Authors: Badiy Elmabrouk, Abdelhamid Boujarif, Zhiguo Zeng, Stephane Borrel, Robert Heidsieck

Abstract:

In an era where sustainability is paramount, this paper introduces a machine learning-driven testing protocol to accurately predict diode failures, merging reliability engineering with failure physics to enhance repair operations efficiency. Our approach refines the burn-in process, significantly curtailing its duration, which not only conserves energy but also elevates productivity and mitigates component wear. A case study from GE HealthCare’s repair center vividly demonstrates the method’s effectiveness, recording a high prediction of diode failures and a substantial decrease in energy consumption that translates to an annual reduction of 6.5 Tons of CO2 emissions. This advancement sets a benchmark for environmentally conscious practices in the electronics repair sector.

Keywords: maintenance, burn-in, failure physics, reliability testing

Procedia PDF Downloads 68
2115 Antimicrobial Activity of the Cyanobacteria spp. against Fish Pathogens in Aquaculture

Authors: I. Tulay Cagatay

Abstract:

Blue-green microalgae cyanobacteria, which are important photosynthetic organisms of aquatic ecosystems, are the primary sources of many bioactive compounds such as proteins, carbohydrates, lipids, vitamins and enzymes that can be used as antimicrobial and antiviral agents. Some of these organisms are nowadays used directly in the food, cosmetic and pharmaceutical industry, or in aquaculture and biotechnological approaches like biofuel or drug therapy. Finding the effective, environmental friendly chemotropic and antimicrobial agents to control fish pathogens are crucial in a country like Turkey which has a production capacity of about 240 thousand tons of cultured fish and has 2377 production farms and which is the second biggest producer in Europe. In our study, we tested the antimicrobial activity of cyanobacterium spp. against some fish pathogens Aeromonas hydrophila and Yersinia ruckeri that are important pathogens for rainbow trout farms. Agar disk diffusion test method was used for studying antimicrobial activity on pathogens. Both tested microorganisms have shown antimicrobial activity positively as the inhibition zones were 0.45 mm and 0.40 mm respectively.

Keywords: fish pathogen, cyanobacteria, antimicrobial activity, trout

Procedia PDF Downloads 165
2114 Testing of Infill Walls with Joint Reinforcement Subjected to in Plane Lateral Load

Authors: J. Martin Leal-Graciano, Juan J. Pérez-Gavilán, A. Reyes-Salazar, J. H. Castorena, J. L. Rivera-Salas

Abstract:

The experimental results about the global behavior of twelve 1:2 scaled reinforced concrete frame subject to in-plane lateral load are presented. The main objective was to generate experimental evidence about the use of steel bars within mortar bed-joints as shear reinforcement in infill walls. Similar to the Canadian and New Zealand standards, the Mexican code includes specifications for this type of reinforcement. However, these specifications were obtained through experimental studies of load-bearing walls, mainly confined walls. Little information is found in the existing literature about the effects of joint reinforcement on the seismic behavior of infill masonry walls. Consequently, the Mexican code establishes the same equations to estimate the contribution of joint reinforcement for both confined walls and infill walls. A confined masonry construction and a reinforced concrete frame infilled with masonry walls have similar appearances. However, substantial differences exist between these two construction systems, which are mainly related to the sequence of construction and to how these structures support vertical and lateral loads. To achieve the objective established, ten reinforced concrete frames with masonry infill walls were built and tested in pairs, having both specimens in the pair identical characteristics except that one of them included joint reinforcement. The variables between pairs were the type of units, the size of the columns of the frame and the aspect ratio of the wall. All cases included tie-columns and tie-beams on the perimeter of the wall to anchor the joint reinforcement. Also, two bare frame with identical characteristic to the infilled frames were tested. The purpose was to investigate the effects of the infill wall on the behavior of the system to in-plane lateral load. In addition, the experimental results were compared with the prediction of the Mexican code. All the specimens were tested in cantilever under reversible cyclic lateral load. To simulate gravity load, constant vertical load was applied on the top of the columns. The results indicate that the contribution of the joint reinforcement to lateral strength depends on the size of the columns of the frame. Larger size columns produce a failure mode that is predominantly a sliding mode. Sliding inhibits the production of new inclined cracks, which are necessary to activate (deform) the joint reinforcement. Regarding the effects of joint reinforcement in the performance of confined masonry walls, many facts were confirmed for infill walls: this type of reinforcement increases the lateral strength of the wall, produces a more distributed cracking and reduces the width of the cracks. Moreover, it reduces the ductility demand of the system at maximum strength. The prediction of the lateral strength provided by the Mexican code is property in some cases; however, the effect of the size of the columns on the contribution of joint reinforcement needs to be better understood.

Keywords: experimental study, Infill wall, Infilled frame, masonry wall

Procedia PDF Downloads 77
2113 Biomaterials Solutions to Medical Problems: A Technical Review

Authors: Ashish Thakur

Abstract:

This technical paper was written in view of focusing the biomaterials and its various applications in modern industries. Author tires to elaborate not only the medical, infect plenty of application in other industries. The scope of the research area covers the wide range of physical, biological and chemical sciences that underpin the design of biomaterials and the clinical disciplines in which they are used. A biomaterial is now defined as a substance that has been engineered to take a form which, alone or as part of a complex system, is used to direct, by control of interactions with components of living systems, the course of any therapeutic or diagnostic procedure. Biomaterials are invariably in contact with living tissues. Thus, interactions between the surface of a synthetic material and biological environment must be well understood. This paper reviews the benefits and challenges associated with surface modification of the metals in biomedical applications. The paper also elaborates how the surface characteristics of metallic biomaterials, such as surface chemistry, topography, surface charge, and wettability, influence the protein adsorption and subsequent cell behavior in terms of adhesion, proliferation, and differentiation at the biomaterial–tissue interface. The chapter also highlights various techniques required for surface modification and coating of metallic biomaterials, including physicochemical and biochemical surface treatments and calcium phosphate and oxide coatings. In this review, the attention is focused on the biomaterial-associated infections, from which the need for anti-infective biomaterials originates. Biomaterial-associated infections differ markedly for epidemiology, aetiology and severity, depending mainly on the anatomic site, on the time of biomaterial application, and on the depth of the tissues harbouring the prosthesis. Here, the diversity and complexity of the different scenarios where medical devices are currently utilised are explored, providing an overview of the emblematic applicative fields and of the requirements for anti-infective biomaterials. In addition to this, chapter introduces nanomedicine and the use of both natural and synthetic polymeric biomaterials, focuses on specific current polymeric nanomedicine applications and research, and concludes with the challenges of nanomedicine research. Infection is currently regarded as the most severe and devastating complication associated to the use of biomaterials. Osteoporosis is a worldwide disease with a very high prevalence in humans older than 50. The main clinical consequences are bone fractures, which often lead to patient disability or even death. A number of commercial biomaterials are currently used to treat osteoporotic bone fractures, but most of these have not been specifically designed for that purpose. Many drug- or cell-loaded biomaterials have been proposed in research laboratories, but very few have received approval for commercial use. Polymeric nanomaterial-based therapeutics plays a key role in the field of medicine in treatment areas such as drug delivery, tissue engineering, cancer, diabetes, and neurodegenerative diseases. Advantages in the use of polymers over other materials for nanomedicine include increased functionality, design flexibility, improved processability, and, in some cases, biocompatibility.

Keywords: nanomedicine, tissue, infections, biomaterials

Procedia PDF Downloads 264
2112 Insights into Particle Dispersion, Agglomeration and Deposition in Turbulent Channel Flow

Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

Abstract:

The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

Procedia PDF Downloads 317
2111 A Generalized Framework for Adaptive Machine Learning Deployments in Algorithmic Trading

Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

Procedia PDF Downloads 89
2110 Prediction and Reduction of Cracking Issue in Precision Forging of Engine Valves Using Finite Element Method

Authors: Xi Yang, Bulent Chavdar, Alan Vonseggern, Taylan Altan

Abstract:

Fracture in hot precision forging of engine valves was investigated in this paper. The entire valve forging procedure was described and the possible cause of the fracture was proposed. Finite Element simulation was conducted for the forging process, with commercial Finite Element code DEFORMTM. The effects of material properties, the effect of strain rate and temperature were considered in the FE simulation. Two fracture criteria were discussed and compared, based on the accuracy and reliability of the FE simulation results. The selected criterion predicted the fracture location and shows the trend of damage increasing with good accuracy, which matches the experimental observation. Additional modification of the punch shapes was proposed to further reduce the tendency of fracture in forging. Finite Element comparison shows a great potential of such application in the mass production.

Keywords: hotforging, engine valve, fracture, tooling

Procedia PDF Downloads 279
2109 Statistical Physics Model of Seismic Activation Preceding a Major Earthquake

Authors: Daniel S. Brox

Abstract:

Starting from earthquake fault dynamic equations, a correspondence between earthquake occurrence statistics in a seismic region before a major earthquake and eigenvalue statistics of a differential operator whose bound state eigenfunctions characterize the distribution of stress in the seismic region is derived. Modeling these eigenvalue statistics with a 2D Coulomb gas statistical physics model, previously reported deviation of seismic activation earthquake occurrence statistics from Gutenberg-Richter statistics in time intervals preceding the major earthquake is derived. It also explains how statistical physics modeling predicts a finite-dimensional nonlinear dynamic system that describes real-time velocity model evolution in the region undergoing seismic activation and how this prediction can be tested experimentally.

Keywords: seismic activation, statistical physics, geodynamics, signal processing

Procedia PDF Downloads 17
2108 Application of Smplify-X Algorithm with Enhanced Gender Classifier in 3D Human Pose Estimation

Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

Abstract:

The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

Procedia PDF Downloads 99
2107 Groundwater Recharge Suitability Mapping Using Analytical Hierarchy Process Based-Approach

Authors: Aziza Barrek, Mohamed Haythem Msaddek, Ismail Chenini

Abstract:

Excessive groundwater pumping due to the increasing water demand, especially in the agricultural sector, causes groundwater scarcity. Groundwater recharge is the most important process that contributes to the water's durability. This paper is based on the Analytic Hierarchy Process multicriteria analysis to establish a groundwater recharge susceptibility map. To delineate aquifer suitability for groundwater recharge, eight parameters were used: soil type, land cover, drainage density, lithology, NDVI, slope, transmissivity, and rainfall. The impact of each factor was weighted. This method was applied to the El Fahs plain shallow aquifer. Results suggest that 37% of the aquifer area has very good and good recharge suitability. The results have been validated by the Receiver Operating Characteristics curve. The accuracy of the prediction obtained was 89.3%.

Keywords: AHP, El Fahs aquifer, empirical formula, groundwater recharge zone, remote sensing, semi-arid region

Procedia PDF Downloads 121
2106 Histopathological Alterations in Liver of Mice Exposed to Different Doses of Diclofenac Sodium

Authors: Deepak Mohan, Sushma Sharma

Abstract:

Diclofenac sodium, a member of the acetic acid family of non-steroidal anti-inflammatory drugs, is used to retard inflammation, arthritis pain and ankylosing spondylitis. The drug is known to cause severe injury in different tissues due to formation of reactive oxygen species. The present study is focused on the effect of different doses of diclofenac (4 mg/kg/body weight and 14 mg/kg/body weight on histoarchitecture of the liver from 7-28 days of the investigation. Diclofenac administration resulted in distorted hepatic degeneration and formation of wide areas in the form of sinusoidal gaps. Hepatic fibrosis noticed in different stages of investigation could be attributed to chronic inflammation and reactive oxygen species which results in deposition of extracellular matrix proteins. The abrupt degenerative changes observed during later stages of the experiment showed maximum damage to the liver, and there was enlargement of sinusoidal gaps accompanied by maximum necrosis in the tissues.

Keywords: arthritis, diclofenac, histoarchitecture, sinusoidal

Procedia PDF Downloads 271
2105 Experimental Study of Infill Walls with Joint Reinforcement Subjected to In-Plane Lateral Load

Authors: J. Martin Leal-Graciano, Juan J. Pérez-Gavilán, A. Reyes-Salazar, J. H. Castorena, J. L. Rivera-Salas

Abstract:

The experimental results about the global behavior of twelve 1:2 scaled reinforced concrete frames subject to in-plane lateral load are presented. The main objective was to generate experimental evidence about the use of steel bars within mortar bed joints as shear reinforcement in infill walls. Similar to the Canadian and New Zealand standards, the Mexican code includes specifications for this type of reinforcement. However, these specifications were obtained through experimental studies of load-bearing walls, mainly confined walls. Little information is found in the existing literature about the effects of joint reinforcement on the seismic behavior of infill masonry walls. Consequently, the Mexican code establishes the same equations to estimate the contribution of joint reinforcement for both confined walls and infill walls. Confined masonry construction and a reinforced concrete frame infilled with masonry walls have similar appearances. However, substantial differences exist between these two construction systems, which are mainly related to the sequence of construction and to how these structures support vertical and lateral loads. To achieve the objective established, ten reinforced concrete frames with masonry infill walls were built and tested in pairs, having both specimens in the pair identical characteristics except that one of them included joint reinforcement. The variables between pairs were the type of units, the size of the columns of the frame, and the aspect ratio of the wall. All cases included tie columns and tie beams on the perimeter of the wall to anchor the joint reinforcement. Also, two bare frames with identical characteristics to the infilled frames were tested. The purpose was to investigate the effects of the infill wall on the behavior of the system to in-plane lateral load. In addition, the experimental results were compared with the prediction of the Mexican code. All the specimens were tested in a cantilever under reversible cyclic lateral load. To simulate gravity load, constant vertical load was applied on the top of the columns. The results indicate that the contribution of the joint reinforcement to lateral strength depends on the size of the columns of the frame. Larger size columns produce a failure mode that is predominantly a sliding mode. Sliding inhibits the production of new inclined cracks, which are necessary to activate (deform) the joint reinforcement. Regarding the effects of joint reinforcement in the performance of confined masonry walls, many facts were confirmed for infill walls. This type of reinforcement increases the lateral strength of the wall, produces a more distributed cracking, and reduces the width of the cracks. Moreover, it reduces the ductility demand of the system at maximum strength. The prediction of the lateral strength provided by the Mexican code is a property in some cases; however, the effect of the size of the columns on the contribution of joint reinforcement needs to be better understood.

Keywords: experimental study, infill wall, infilled frame, masonry wall

Procedia PDF Downloads 175
2104 General Mathematical Framework for Analysis of Cattle Farm System

Authors: Krzysztof Pomorski

Abstract:

In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

Procedia PDF Downloads 145
2103 Prediction and Identification of a Permissive Epitope Insertion Site for St Toxoid in cfaB from Enterotoxigenic Escherichia coli

Authors: N. Zeinalzadeh, Mahdi Sadeghi

Abstract:

Enterotoxigenic Escherichia coli (ETEC) is the most common cause of non-inflammatory diarrhea in the developing countries, resulting in approximately 20% of all diarrheal episodes in children in these areas. ST is one of the most important virulence factors and CFA/I is one of the frequent colonization factors that help to process of ETEC infection. ST and CfaB (CFA/I subunit) are among vaccine candidates against ETEC. So, ST because of its small size is not a good immunogenic in the natural form. However to increase its immunogenic potential, here we explored candidate positions for ST insertion in CfaB sequence. After bioinformatics analysis, one of the candidate positions was selected and the chimeric gene (cfaB*st) sequence was synthesized and expressed in E. coli BL21 (DE3). The chimeric recombinant protein was purified with Ni-NTA columns and characterized with western blot analysis. The residue 74-75 of CfaB sequence could be a good candidate position for ST and other epitopes insertion.

Keywords: bioinformatics, CFA/I, enterotoxigenic E. coli, ST toxoid

Procedia PDF Downloads 448
2102 Influence of ABCB1 2677G > T Single Nucleotide Polymorphism on Warfarin Maintenance Therapy among Patients with Prosthetic Heart Valve

Authors: M. G. Gopisankar, A. Surendiran, M. Hemachandren

Abstract:

The dose requirement of warfarin to achieve target INR range varies in patients with prosthetic heart valve. This variation in is affected by both genetic and non-genetic factors. Earlier studies have identified role of CYP2C9 and VKORC1 genetic polymorphisms on warfarin dose requirement. Warfarin being a substrate for drug transporter, P-glycoprotein coded by ABCB1 gene, may also be influenced by its genetic polymorphisms. This study was aimed to study the effect of single nucleotide polymorphism (SNP), ABCB1 2677G > T on warfarin maintenance dose requirement in patients with steady-state International Normalized Ratio (INR). The median dose requirement was significantly different between the genotype groups GG vs. GT (35 ± 20; 42.5 ± 18, p < 0.05), GG vs. TT (35 ± 20; 41.25 ± 25, p<0.05). There was no significant difference between GT vs. TT. In conclusion, patients with variant allele require a higher weekly maintenance dose of warfarin compared to patients without variant allele.

Keywords: warfarin pharamcogenetics, pharmacogenomics of warfarin, ABCB1 and warfarin, pglycoprotein and warfarin

Procedia PDF Downloads 260
2101 Application of Model Tree in the Prediction of TBM Rate of Penetration with Synthetic Minority Oversampling Technique

Authors: Ehsan Mehryaar

Abstract:

The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.

Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM

Procedia PDF Downloads 174
2100 Evaluation of Modern Natural Language Processing Techniques via Measuring a Company's Public Perception

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 146
2099 Simulation the Stress Distribution of Wheel/Rail at Contact Region

Authors: Norie A. Akeel, Z. Sajuri, A. K. Ariffin

Abstract:

This paper discusses the effect of different loading analysis on crack initiation life of wheel/rail in the contact region. A simulated three dimensional (3D) elasto plastic model of a wheel/rail contact is modeled using the fine mesh technique in the contact region by using Finite Element Method FEM code ANSYS 11.0 software. Different loads of approximately from 70 to 140 KN was applied on the wheel tread through the running surface on the railhead surface to simulate stress distribution (Von Mises) and a life prediction of the crack initiation under rolling contact motion. Stress analysis is achieved and the fatigue life to the rail head surface is calculated numerically by using a multi-axial fatigue life of crack initiation model. All results obtained from the previous researches are compared with this research.

Keywords: FEM, rolling contact, rail track, stress distribution, fatigue life

Procedia PDF Downloads 554
2098 2D Fingerprint Performance for PubChem Chemical Database

Authors: Fatimah Zawani Abdullah, Shereena Mohd Arif, Nurul Malim

Abstract:

The study of molecular similarity search in chemical database is increasingly widespread, especially in the area of drug discovery. Similarity search is an application in the field of Chemoinformatics to measure the similarity between the molecular structure which is known as the query and the structure of chemical compounds in the database. Similarity search is also one of the approaches in virtual screening which involves computational techniques and scoring the probabilities of activity. The main objective of this work is to determine the best fingerprint when compared to the other five fingerprints selected in this study using PubChem chemical dataset. This paper will discuss the similarity searching process conducted using 6 types of descriptors, which are ECFP4, ECFC4, FCFP4, FCFC4, SRECFC4 and SRFCFC4 on 15 activity classes of PubChem dataset using Tanimoto coefficient to calculate the similarity between the query structures and each of the database structure. The results suggest that ECFP4 performs the best to be used with Tanimoto coefficient in the PubChem dataset.

Keywords: 2D fingerprints, Tanimoto, PubChem, similarity searching, chemoinformatics

Procedia PDF Downloads 293
2097 Topical Delivery of Griseofulvin via Lipid Nanoparticles

Authors: Yann Jean Tan, Hui Meng Er, Choy Sin Lee, Shew Fung Wong, Wen Huei Lim

Abstract:

Griseofulvin is a long standing fungistatic agent against dermatophytosis. Nevertheless, it has several drawbacks such as poor and highly variable bio availability, long duration of treatment, systemic side effects and drug interactions. Targeted treatment for the superficial skin infection, dermatophytosis via topical route could be beneficial. Nevertheless, griseofulvin is only available in the form of oral preparation. Hence, it generates interest in developing a topical formulation for griseofulvin, by using lipid nano particle as the vehicle. Lipid nanoparticle is a submicron colloidal carrier with a core that is solid in nature (lipid). It has combined advantages of various traditional carriers and is a promising vehicle for topical delivery. The griseofulvin loaded lipid nano particles produced using high pressure homogenization method were characterized and investigated for its skin targeting effect in vitro. It has a mean particle size of 179.8±4.9 nm with polydispersity index of 0.306±0.011. Besides, it showed higher skin permeation and better skin targeting effect compared to the griseofulvin suspension.

Keywords: lipid nanoparticles, griseofulvin, topical, dermatophytosis

Procedia PDF Downloads 458
2096 Iraq Water Resources Planning: Perspectives and Prognoses

Authors: Nadhir Al-Ansari, Ammar A. Ali, Sven Knutsson

Abstract:

Iraq is located in the Middle East. It covers an area of 433,970 square kilometres populated by about 32 million inhabitants. Iraq greatly relies in its water resources on the Tigris and Euphrates Rivers. Recently, Iraq is suffering from water shortage problems. This is due to external and internal factors. The former includes global warming and water resources policies of neighbouring countries while the latter includes mismanagement of its water resources. The supply and demand are predicted to be 43 and 66.8 Billion Cubic Meters (BCM) respectively in 2015, while in 2025 it will be 17.61 and 77 BCM respectively. In addition, future prediction suggests that Tigris and Euphrates Rivers will be completely dry in 2040. To overcome this problem, prudent water management policies are to be adopted. This includes Strategic Water Management Vision, development of irrigation techniques, reduction of water losses, use of non-conventional water resources and research and development planning.

Keywords: Iraq, Tigris River, Euphrates River, water scarcity, water resources management

Procedia PDF Downloads 449
2095 The Twin Terminal of Pedestrian Trajectory Based on City Intelligent Model (CIM) 4.0

Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

Procedia PDF Downloads 419
2094 High-Intensity, Short-Duration Electric Pulses Induced Action Potential in Animal Nerves

Authors: Jiahui Song, Ravindra P. Joshi

Abstract:

The use of high-intensity, short-duration electric pulses is a promising development with many biomedical applications. The uses include irreversible electroporation for killing abnormal cells, reversible poration for drug and gene delivery, neuromuscular manipulation, and the shrinkage of tumors, etc. High intensity, short-duration electric pulses result in the creation of high-density, nanometer-sized pores in the cellular membrane. This electroporation amounts to localized modulation of the transverse membrane conductance, and effectively provides a voltage shunt. The electrically controlled changes in the trans-membrane conductivity could be used to affect neural traffic and action potential propagation. A rat was taken as the representative example in this research. The simulation study shows the pathway from the sensorimotor cortex down to the spinal motoneurons, and effector muscles could be reversibly blocked by using high-intensity, short-duration electrical pulses. Also, actual experimental observations were compared against simulation predictions.

Keywords: action potential, electroporation, high-intensity, short-duration

Procedia PDF Downloads 269
2093 Heart Failure Identification and Progression by Classifying Cardiac Patients

Authors: Muhammad Saqlain, Nazar Abbas Saqib, Muazzam A. Khan

Abstract:

Heart Failure (HF) has become the major health problem in our society. The prevalence of HF has increased as the patient’s ages and it is the major cause of the high mortality rate in adults. A successful identification and progression of HF can be helpful to reduce the individual and social burden from this syndrome. In this study, we use a real data set of cardiac patients to propose a classification model for the identification and progression of HF. The data set has divided into three age groups, namely young, adult, and old and then each age group have further classified into four classes according to patient’s current physical condition. Contemporary Data Mining classification algorithms have been applied to each individual class of every age group to identify the HF. Decision Tree (DT) gives the highest accuracy of 90% and outperform all other algorithms. Our model accurately diagnoses different stages of HF for each age group and it can be very useful for the early prediction of HF.

Keywords: decision tree, heart failure, data mining, classification model

Procedia PDF Downloads 402
2092 Studying Projection Distance and Flow Properties by Shape Variations of Foam Monitor

Authors: Hyun-Kyu Cho, Jun-Su Kim, Choon-Geun Huh, Geon Lee Young-Chul Park

Abstract:

In this study, the relationship between flow properties and fluid projection distance look into connection for shape variations of foam monitor. A numerical analysis technique for fluid analysis of a foam monitor was developed for the prediction. Shape of foam monitor the flow path of fluid flow according to the shape, The fluid losses were calculated from flow analysis result.. The modified model used the length increase model of the flow path, and straight line of the model. Inlet pressure was 7 [bar] and external was atmosphere codition. am. The results showed that the length increase model of the flow path and straight line of the model was improved in the nozzle projection distance.

Keywords: injection performance, finite element method, foam monitor, Projection distance

Procedia PDF Downloads 347