Search results for: in vitro skin model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18452

Search results for: in vitro skin model

13952 Optimizing the Efficiency of Measuring Instruments in Ouagadougou-Burkina Faso

Authors: Moses Emetere, Marvel Akinyemi, S. E. Sanni

Abstract:

At the moment, AERONET or AMMA database shows a large volume of data loss. With only about 47% data set available to the scientist, it is evident that accurate nowcast or forecast cannot be guaranteed. The calibration constants of most radiosonde or weather stations are not compatible with the atmospheric conditions of the West African climate. A dispersion model was developed to incorporate salient mathematical representations like a Unified number. The Unified number was derived to describe the turbulence of the aerosols transport in the frictional layer of the lower atmosphere. Fourteen years data set from Multi-angle Imaging SpectroRadiometer (MISR) was tested using the dispersion model. A yearly estimation of the atmospheric constants over Ouagadougou using the model was obtained with about 87.5% accuracy. It further revealed that the average atmospheric constant for Ouagadougou-Niger is a_1 = 0.626, a_2 = 0.7999 and the tuning constants is n_1 = 0.09835 and n_2 = 0.266. Also, the yearly atmospheric constants affirmed the lower atmosphere of Ouagadougou is very dynamic. Hence, it is recommended that radiosonde and weather station manufacturers should constantly review the atmospheric constant over a geographical location to enable about eighty percent data retrieval.

Keywords: aerosols retention, aerosols loading, statistics, analytical technique

Procedia PDF Downloads 295
13951 Implementation of an Economic – Probabilistic Model to Risk Analysis of ERP Project in Technological Innovation Firms – A Case Study of ICT Industry in Iran

Authors: Reza Heidari, Maryam Amiri

Abstract:

In a technological world, many countries have a tendency to fortifying their companies and technological infrastructures. Also, one of the most important requirements for developing technology is innovation, and then, all companies are struggling to consider innovation as a basic principle. Since, the expansion of a product need to combine different technologies, therefore, different innovative projects would be run in the firms as a base of technology development. In such an environment, enterprise resource planning (ERP) has special significance in order to develop and strengthen of innovations. In this article, an economic-probabilistic analysis was provided to perform an implementation project of ERP in the technological innovation (TI) based firms. The used model in this article assesses simultaneously both risk and economic analysis in view of the probability of each event that is jointly between economical approach and risk investigation approach. To provide an economic-probabilistic analysis of risk of the project, activities and milestones in the cash flow were extracted. Also, probability of occurrence of each of them was assessed. Since, Resources planning in an innovative firm is the object of this project. Therefore, we extracted various risks that are in relation with innovative project and then they were evaluated in the form of cash flow. This model, by considering risks affecting the project and the probability of each of them and assign them to the project's cash flow categories, presents an adjusted cash flow based on Net Present Value (NPV) and with probabilistic simulation approach. Indeed, this model presented economic analysis of the project based on risks-adjusted. Then, it measures NPV of the project, by concerning that these risks which have the most effect on technological innovation projects, and in the following measures probability associated with the NPV for each category. As a result of application of presented model in the information and communication technology (ICT) industry, provided an appropriate analysis of feasibility of the project from the point of view of cash flow based on risk impact on the project. Obtained results can be given to decision makers until they can practically have a systematically analysis of the possibility of the project with an economic approach and as moderated.

Keywords: cash flow categorization, economic evaluation, probabilistic, risk assessment, technological innovation

Procedia PDF Downloads 391
13950 Natural Ventilation for the Sustainable Tall Office Buildings of the Future

Authors: Ayşin Sev, Görkem Aslan

Abstract:

Sustainable tall buildings that provide comfortable, healthy and efficient indoor environments are clearly desirable as the densification of living and working space for the world’s increasing population proceeds. For environmental concerns, these buildings must also be energy efficient. One component of these tasks is the provision of indoor air quality and thermal comfort, which can be enhanced with natural ventilation by the supply of fresh air. Working spaces can only be naturally ventilated with connections to the outdoors utilizing operable windows, double facades, ventilation stacks, balconies, patios, terraces and skygardens. Large amounts of fresh air can be provided to the indoor spaces without mechanical air-conditioning systems, which are widely employed in contemporary tall buildings. This paper tends to present the concept of natural ventilation for sustainable tall office buildings in order to achieve healthy and comfortable working spaces, as well as energy efficient environments. Initially the historical evolution of ventilation strategies for tall buildings is presented, beginning with natural ventilation and continuing with the introduction of mechanical air-conditioning systems. Then the emergence of natural ventilation due to the health and environmental concerns in tall buildings is handled, and the strategies for implementing this strategy are revealed. In the next section, a number of case studies that utilize this strategy are investigated. Finally, how tall office buildings can benefit from this strategy is discussed.

Keywords: tall office building, energy efficiency, double-skin façade, stack ventilation, air conditioning

Procedia PDF Downloads 495
13949 Prediction of Anticancer Potential of Curcumin Nanoparticles by Means of Quasi-Qsar Analysis Using Monte Carlo Method

Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

Abstract:

The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

Procedia PDF Downloads 306
13948 Towards a Computational Model of Consciousness: Global Abstraction Workspace

Authors: Halim Djerroud, Arab Ali Cherif

Abstract:

We assume that conscious functions are implemented automatically. In other words that consciousness as well as the non-consciousness aspect of human thought, planning, and perception, are produced by biologically adaptive algorithms. We propose that the mechanisms of consciousness can be produced using similar adaptive algorithms to those executed by the mechanism. In this paper, we propose a computational model of consciousness, the ”Global Abstraction Workspace” which is an internal environmental modelling perceived as a multi-agent system. This system is able to evolve and generate new data and processes as well as actions in the environment.

Keywords: artificial consciousness, cognitive architecture, global abstraction workspace, multi-agent system

Procedia PDF Downloads 324
13947 Fucoidan: A Potent Seaweed-Derived Polysaccharide with Immunomodulatory and Anti-inflammatory Properties

Authors: Tauseef Ahmad, Muhammad Ishaq, Mathew Eapen, Ahyoung Park, Sam Karpiniec, Vanni Caruso, Rajaraman Eri

Abstract:

Fucoidans are complex, fucose-rich sulfated polymers discovered in brown seaweeds. Fucoidans are popular around the world, particularly in the nutraceutical and pharmaceutical industries, due to their promising medicinal properties. Fucoidans have been shown to have a variety of biological activities, including anti-inflammatory effects. They are known to inhibit inflammatory processes through a variety of mechanisms, including enzyme inhibition and selectin blockade. Inflammation is a part of the complicated biological response of living systems to damaging stimuli, and it plays a role in the pathogenesis of a variety of disorders, including arthritis, inflammatory bowel disease, cancer, and allergies. In the current investigation, various fucoidan extracts from Undaria pinnatifida, Fucus vesiculosus, Macrocystis pyrifera, Ascophyllum nodosum, and Laminaria japonica were assessed for inhibition of pro-inflammatory cytokine production (TNF-α, IL-1β, and IL-6) in LPS induced human macrophage cell line (THP-1) and human peripheral blood mononuclear cells (PBMCs). Furthermore, we also sought to catalogue these extracts based on their anti-inflammatory effects in the current in-vitro cell model. Materials and Methods: To assess the cytotoxicity of fucoidan extracts, MTT (3-[4,5-dimethylthiazol-2-yl]-2,5, -diphenyltetrazolium bromide) cell viability assay was performed. Furthermore, a dose-response for fucoidan extracts was performed in LPS induced THP-1 cells and PBMCs after pre-treatment for 24 hours, and levels of TNF-α, IL-1β, and IL-6 cytokines were measured using Enzyme-Linked Immunosorbent Assay (ELISA). Results: The MTT cell viability assay demonstrated that fucoidan extracts exhibited no evidence of cytotoxicity in THP-1 cells or PBMCs after 48 hours of incubation. The results of the sandwich ELISA revealed that all fucoidan extracts suppressed cytokine production in LPS-stimulated PBMCs and human THP-1 cells in a dose-dependent manner. Notably, at lower concentrations, the lower molecular fucoidan (5-30 kDa) extract from Macrocystis pyrifera was a highly efficient inhibitor of pro-inflammatory cytokines. Fucoidan extracts from all species including Undaria pinnatifida, Fucus vesiculosus, Macrocystis pyrifera, Ascophyllum nodosum, and Laminaria japonica exhibited significant anti-inflammatory effects. These findings on several fucoidan extracts provide insight into strategies for improving their efficacy against inflammation-related diseases. Conclusion: In the current research, we have successfully catalogued several fucoidan extracts based on their efficiency in LPS-induced macrophages and PBMCs in downregulating the key pro-inflammatory cytokines (TNF-, IL-1 and IL-6), which are prospective targets in human inflammatory illnesses. Further research would provide more information on the mechanism of action, allowing it to be tested for therapeutic purposes as an anti-inflammatory medication.

Keywords: fucoidan, PBMCs, THP-1, TNF-α, IL-1β, IL-6, inflammation

Procedia PDF Downloads 48
13946 Investigation of an Alkanethiol Modified Au Electrode as Sensor for the Antioxidant Activity of Plant Compounds

Authors: Dana A. Thal, Heike Kahlert, Fritz Scholz

Abstract:

Thiol molecules are known to easily form self-assembled monolayers (SAM) on Au surfaces. Depending on the thiol’s structure, surface modifications via SAM can be used for electrode sensor development. In the presented work, 1-decanethiol coated polycrystalline Au electrodes were applied to indirectly assess the radical scavenging potential of plant compounds and extracts. Different plant compounds with reported antioxidant properties as well as an extract from the plant Gynostemma pentaphyllum were tested for their effectiveness to prevent SAM degradation on the sensor electrodes via photolytically generated radicals in aqueous media. The SAM degradation was monitored over time by differential pulse voltammetry (DPV) measurements. The results were compared to established antioxidant assays. The obtained data showed an exposure time and concentration dependent degradation process of the SAM at the electrode’s surfaces. The tested substances differed in their capacity to prevent SAM degradation. Calculated radical scavenging activities of the tested plant compounds were different for different assays. The presented method poses a simple system for radical scavenging evaluation and, considering the importance of the test system in antioxidant activity evaluation, might be taken as a bridging tool between in-vivo and in-vitro antioxidant assay in order to obtain more biologically relevant results in antioxidant research.

Keywords: alkanethiol SAM, plant antioxidant, polycrystalline Au, radical scavenger

Procedia PDF Downloads 288
13945 Establishment of a Nomogram Prediction Model for Postpartum Hemorrhage during Vaginal Delivery

Authors: Yinglisong, Jingge Chen, Jingxuan Chen, Yan Wang, Hui Huang, Jing Zhnag, Qianqian Zhang, Zhenzhen Zhang, Ji Zhang

Abstract:

Purpose: The study aims to establish a nomogram prediction model for postpartum hemorrhage (PPH) in vaginal delivery. Patients and Methods: Clinical data were retrospectively collected from vaginal delivery patients admitted to a hospital in Zhengzhou, China, from June 1, 2022 - October 31, 2022. Univariate and multivariate logistic regression were used to filter out independent risk factors. A nomogram model was established for PPH in vaginal delivery based on the risk factors coefficient. Bootstrapping was used for internal validation. To assess discrimination and calibration, receiver operator characteristics (ROC) and calibration curves were generated in the derivation and validation groups. Results: A total of 1340 cases of vaginal delivery were enrolled, with 81 (6.04%) having PPH. Logistic regression indicated that history of uterine surgery, induction of labor, duration of first labor, neonatal weight, WBC value (during the first stage of labor), and cervical lacerations were all independent risk factors of hemorrhage (P <0.05). The area-under-curve (AUC) of ROC curves of the derivation group and the validation group were 0.817 and 0.821, respectively, indicating good discrimination. Two calibration curves showed that nomogram prediction and practical results were highly consistent (P = 0.105, P = 0.113). Conclusion: The developed individualized risk prediction nomogram model can assist midwives in recognizing and diagnosing high-risk groups of PPH and initiating early warning to reduce PPH incidence.

Keywords: vaginal delivery, postpartum hemorrhage, risk factor, nomogram

Procedia PDF Downloads 58
13944 Design and Identification of Mycobacterium tuberculosis Glutamate Racemase (MurI) Inhibitors

Authors: Prasanthi Malapati, R. Reshma, Vijay Soni, Perumal Yogeeswari, Dharmarajan Sriram

Abstract:

In the present study, we attempted to develop Mycobacterium tuberculosis (Mtb) inhibitors by exploring the pharmaceutically underexploited enzyme targets which are majorly involved in cell wall biosynthesis of mycobacteria. For this purpose, glutamate racemase (coded by MurI gene) was selected. This enzyme racemize L-glutamate to D-glutamate required for the construction of peptidoglycan in the bacterial cell wall synthesis process. Furthermore this enzyme is neither expressed nor its product, D-glutamate is normally found in mammals, and hence designing inhibitors against this enzyme will not affect the host system as well act as potential antitubercular drugs. A library of BITS in house compounds were screened against Mtb MurI enzyme. Based on docking score, interactions and synthetic feasibility one hit lead was identified. Further optimization of lead was attempted and its derivatives were synthesized. Forty eight derivatives of 2-phenylbenzo[d]oxazole and 2-phenylbenzo[d]thiazole were synthesized and evaluated for Mtb MurI inhibition study, in vitro activities against Mtb, cytotoxicity against RAW 264.7 cell line. Chemical derivatization of the lead resulted in compounds NR-1213 AND NR-1124 as the potent M. tuberculosis glutamate racemase inhibitors with IC50 of 4-5µM which are remarkable and were found to be non-cytotoxic. Molecular dynamics, dormant models and cardiotoxicity studies of the most active molecules are in process.

Keywords: cell wall biosynthesis, dormancy, glutamate racemase, tuberculosis

Procedia PDF Downloads 256
13943 Socioterritorial Inequalities in a Region of Chile. Beyond the Geography

Authors: Javier Donoso-Bravo, Camila Cortés-Zambrano

Abstract:

In this paper, we analyze socioterritorial inequalities in the region of Valparaiso (Chile) using secondary data to account for these inequalities drawing on economic, social, educational, and environmental dimensions regarding the thirty-six municipalities of the region. We looked over a wide-ranging set of secondary data from public sources regarding economic activities, poverty, employment, income, years of education, post-secondary education access, green areas, access to potable water, and others. We found sharp socioterritorial inequalities especially based on the economic performance in each territory. Analysis show, on the one hand, the existence of a dual and unorganized development model in some territories with a strong economic activity -especially in the areas of finance, real estate, mining, and vineyards- but, at the same time, with poor social indicators. On the other hand, most of the territories show a dispersed model with very little dynamic economic activities and very poor social development. Finally, we discuss how socioterritorial inequalities in the region of Valparaiso reflect the level of globalization of the economic activities carried on in every territory.

Keywords: socioterritorial inequalities, development model, Chile, secondary data, Region of Valparaiso

Procedia PDF Downloads 85
13942 A Review on Application of Phase Change Materials in Textiles Finishing

Authors: Mazyar Ahrari, Ramin Khajavi, Mehdi Kamali Dolatabadi, Tayebeh Toliyat, Abosaeed Rashidi

Abstract:

Fabric as the first and most common layer that is in permanent contact with human skin is a very good interface to provide coverage, as well as heat and cold insulation. Phase change materials (PCMs) are organic and inorganic compounds which have the capability of absorbing and releasing noticeable amounts of latent heat during phase transitions between solid and liquid phases at a low temperature range. PCMs come across phase changes (liquid-solid and solid-liquid transitions) during absorbing and releasing thermal heat; so, in order to use them for a long time, they should have been encapsulated in polymeric shells, so-called microcapsules. Microencapsulation and nanoencapsulation methods have been developed in order to reduce the reactivity of a PCM with outside environment, promoting the ease of handling, decreasing the diffusion and evaporation rates. Methods of incorporation of PCMs in textiles such as electrospinning and determining thermal properties had been summarized. Paraffin waxes catch a lot of attention due to their high thermal storage density, repeatability of phase change, thermal stability, small volume change during phase transition, chemical stability, non-toxicity, non-flammability, non-corrosive and low cost and they seem to play a key role in confronting with climate change and global warming. In this article, we aimed to review the researches concentrating on the characteristics of PCMs and new materials and methods of microencapsulation.

Keywords: thermoregulation, microencapsulation, phase change materials, thermal energy storage, nanoencapsulation

Procedia PDF Downloads 373
13941 Improvement of Process Competitiveness Using Intelligent Reference Models

Authors: Julio Macedo

Abstract:

Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

Procedia PDF Downloads 73
13940 Development of a Mathematical Theoretical Model and Simulation of the Electromechanical System for Wave Energy Harvesting

Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

Abstract:

As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: electromechanical device, modeling, renewable energy, sea wave energy, simulation

Procedia PDF Downloads 466
13939 A Fast, Reliable Technique for Face Recognition Based on Hidden Markov Model

Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

Abstract:

Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

Procedia PDF Downloads 314
13938 Transformer Fault Diagnostic Predicting Model Using Support Vector Machine with Gradient Decent Optimization

Authors: R. O. Osaseri, A. R. Usiobaifo

Abstract:

The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

Procedia PDF Downloads 306
13937 Effect of Damping on Performance of Magnetostrictive Vibration Energy Harvester

Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

Abstract:

This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: internal damping coefficient, external damping coefficient, euler-bernoulli, energy harvester, galfenol, magnetostrictive, response surface method

Procedia PDF Downloads 102
13936 A Development Model of Factors Affecting Decision Making to Select Successor in Family Business of Thailand

Authors: Polvasut Mahaiamsiri, Piraphong Foosiri

Abstract:

The purpose of this research is to explore the model of factors affecting decision making to select successor in family business of Thailand. A Structural Equation Model (SEM) was created from relevant theories and researches. Consequently, examine and analyse, the causal relation factors of Succession Plan, Recruitment Process and Strategic Planning, whether they have direct or indirect effects on Decision Making to Select Successor in family business. Units of analysis are selected from the family business, totalling 300 sampling. Population sampling is current owners or CEO from the percentage of six district areas in Thailand with multi-stage sampling. A set of questionnaires is used to collect data. An analysis of structural equation modelling (SEM) technique using AMOS 21 program is conducted to test the hypotheses and confirmatory factor analysis is performed and shows that these variables can be tested. The finding of this study revealed that these factors are separate constructs that combine to determine decision making to select successors.

Keywords: succession plan, family business, recruitment process, strategic planning, decision making to select successor

Procedia PDF Downloads 190
13935 Using Atomic Force Microscope to Investigate the Influence of UVA Radiation and HA on Cell Behaviour and Elasticity of Dermal Fibroblasts

Authors: Pei-Hsiu Chiang, Ling Hong Huang, Hsin-I Chang

Abstract:

In this research, we used UVA irradiation, which can penetrate into dermis and fibroblasts, the most abundant cells in dermis, to investigate the effect of UV light on dermis, such as inflammation, ECM degradation and elasticity loss. Moreover, this research is focused on the influence of hyaluronic acid (HA) on UVA treated dermal fibroblasts. We aim to establish whether HA can effectively relief ECM degradation, and restore the elasticity of UVA-damaged fibroblasts. Prolonged exposure to UVA radiation can damage fibroblasts and led variation in cell morphology and reduction in cell viability. Besides, UVA radiation can induce IL-1β expression on fibroblasts and then promote MMP-1 and MMP-3 expression, which can accelerate ECM degradation. On the other hand, prolonged exposure to UVA radiation reduced collagen and elastin synthesis on fibroblasts. Due to the acceleration of ECM degradation and the reduction of ECM synthesis, Atomic force microscope (AFM) was used to analyze the elasticity reduction on UVA-damaged fibroblasts. UVA irradiation causes photoaging on fibroblasts. UVA damaged fibroblasts with HA treatment can down-regulate the gene expression of MMP-1, MMP-3, and then slow down ECM degradation. On the other hand, HA may restore elastin and collagen synthesis in UV-damaged fibroblasts. Based on the slowdown of ECM degradation, UVA-damaged fibroblast elasticity can be effectively restored by HA treatment. In summary, HA can relief the photoaging conditions on fibroblasts, but may not be able to return fibroblasts to normal, healthy state. Although HA cannot fully recover UVA-damaged fibroblasts, HA is still potential for repairing photoaging skin.

Keywords: atomic force microscope, hyaluronic acid, UVA radiation, dermal fibroblasts

Procedia PDF Downloads 382
13934 Predicting Success and Failure in Drug Development Using Text Analysis

Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

Abstract:

Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

Procedia PDF Downloads 136
13933 The Pioneering Model in Teaching Arabic as a Mother Tongue through Modern Innovative Strategies

Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

Abstract:

This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

Procedia PDF Downloads 212
13932 Formulation and Evaluation of Lisinopril Microspheres for Nasal Delivery

Authors: S. S. Patil, R. M. Mhetre, S. V. Patil

Abstract:

Lisinopril is an angiotensin converting enzyme inhibitor used in the treatment of hypertension and heart failure in prophylactic treatment after myocardial infarction and in diabetic nephropathy. However, it is very poorly absorbed from gastro-intestinal tract. Intranasal administration is an ideal alternative to the parenteral route for systemic drug delivery. Formulating multiparticulate system with mucoadhesive polymers provide a significant increase in the nasal residence time. The aim of the present approach was to overcome the drawbacks of the conventional dosage forms of lisinopril by formulating intranasal microspheres with Carbopol 974P NF and HPMC K4 M along with film forming polymer ethyl cellulose.The microspheres were prepared by emulsion solvent evaporation method. The prepared microspheres were characterized for encapsulation efficiency, drug loading, particle size, and surface morphology, degree of swelling, ex vivo mucoadhesion, drug release, ex vivo diffusion studies. All formulations has shown entrapment efficiency between 80 to more than 95%, mucoadhesion was more than 80 % and drug release up to 90 %. Ex vivo studies revealed tht the improved bioavailability of drug compared to oral drug administration. Both in vitro and in vivo studies conclude that combination of Carbopol and HPMC based microspheres shown better results than single carbopol based microspheres for the delivery of lisinopril.

Keywords: microspheres, lisinopril, nasal delivery, solvent evaporation method

Procedia PDF Downloads 516
13931 Factors Influencing the Adoption of Social Media as a Medium of Public Service Broadcasting

Authors: Seyed Mohammadbagher Jafari, Izmeera Shiham, Masoud Arianfar

Abstract:

The increased usage of Social media for different uses in turn makes it important to develop an understanding of users and their attitudes toward these sites, and moreover, the uses of such sites in a broader perspective such as broadcasting. This quantitative study addressed the problem of factors influencing the adoption of social media as a medium of public service broadcasting in the Republic of Maldives. These powerful and increasingly usable tools, accompanied by large public social media datasets, are bringing in a golden age of social science by empowering researchers to measure social behavior on a scale never before possible. This was conducted by exploring social responses on the use of social media. Research model was developed based on the previous models such as TAM, DOI and Trust combined model. It evaluates the influence of perceived ease of use, perceived usefulness, trust, complexity, compatibility and relative advantage influence on the adoption of social Media. The model was tested on a sample of 365 Maldivian people using survey method via questionnaire. The result showed that perceived usefulness, trust, relative advantage and complexity would highly influence the adoption of social media.

Keywords: adoption, broadcasting, maldives, social media

Procedia PDF Downloads 470
13930 Determination and Qsar Modelling of Partitioning Coefficients for Some Xenobiotics in Soils and Sediments

Authors: Alaa El-Din Rezk

Abstract:

For organic xenobiotics, sorption to Aldrich humic acid is a key process controlling their mobility, bioavailability, toxicity and fate in the soil. Hydrophobic organic compounds possessing either acid or basic groups can be partially ionized (deprotonated or protonated) within the range of natural soil pH. For neutral and ionogenicxenobiotics including (neutral, acids and bases) sorption coefficients normalized to organic carbon content, Koc, have measured at different pH values. To this end, the batch equilibrium technique has been used, employing SPME combined with GC-MSD as an analytical tool. For most ionogenic compounds, sorption has been affected by both pH and pKa and can be explained through Henderson-Hasselbalch equation. The results demonstrate that when assessing the environmental fate of ionogenic compounds, their pKa and speciation under natural conditions should be taken into account. A new model has developed to predict the relationship between log Koc and pH with full statistical evaluation against other existing predictive models. Neutral solutes have displayed a good fit with the classical model using log Kow as log Koc predictor, whereas acidic and basic compounds have displayed a good fit with the LSER approach and the new proposed model. Measurement limitations of the Batch technique and SPME-GC-MSD have been found with ionic compounds.

Keywords: humic acid, log Koc, pH, pKa, SPME-GCMSD

Procedia PDF Downloads 251
13929 Chemical Composition of Essential Oil and in vitro Antibacterial and Anticancer Activity of the Hydroalcolic Extract from Coronilla varia

Authors: A. A. Dehpour, B. Eslami, S. Rezaie, S. F. Hashemian, F. Shafie, M. Kiaie

Abstract:

The aims of study were investigation on chemical composition essential oil and the effect of extract of Coronilla varia on antimicrobial and cytotoxicity activity. The essential oils of Coronilla varia is obtained by hydrodistillation and analyzed by (GC/MS) for determining their chemical composition and identification of their components. Antibacterial activity of plant extract was determined by disc diffusion method. The effect of hydroalcolic extracts from Cornilla varia investigated on MCF7 cancer cell line by MTT assay. The major components were Caryophyllene Oxide (60.19%), Alphacadinol (4.13%) and Homoadantaneca Robexylic Acid (3.31%). The extracts from Coronilla varia had interesting activity against Proteus mirabilis in the concentration of 700 µg/disc and did not show any activity against Staphylococus aureus, Bacillus subtillis, Klebsiella pneumonia and Entrobacter cloacae. The positive control, Ampicillin, Chloramphenicol and Cenphalothin had shown zone of inhibition resistant all bacteria. Corohilla varia ethanol extract could inhibit the proliferation of MCF7 cell line in RPMI 1640 medium. IC50 5(mg/ml) was the optimum concentration of extract from Coronilla varia inhibition of cell line growth. The MCF7 cancer cell line and Proteus mirabilis were more sensitive to Coronilla varia ethanol extract.

Keywords: Coronilla varia, essential oil, antibacterial, anticancer, hela cell line

Procedia PDF Downloads 379
13928 Influence of the Coarse-Graining Method on a DEM-CFD Simulation of a Pilot-Scale Gas Fluidized Bed

Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

Abstract:

The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

Procedia PDF Downloads 53
13927 Development of a Spatial Data for Renal Registry in Nigeria Health Sector

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

Abstract:

Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 181
13926 A Modular and Reusable Bond Graph Model of Epithelial Transport in the Proximal Convoluted Tubule

Authors: Leyla Noroozbabaee, David Nickerson

Abstract:

We introduce a modular, consistent, reusable bond graph model of the renal nephron’s proximal convoluted tubule (PCT), which can reproduce biological behaviour. In this work, we focus on ion and volume transport in the proximal convoluted tubule of the renal nephron. Modelling complex systems requires complex modelling problems to be broken down into manageable pieces. This can be enabled by developing models of subsystems that are subsequently coupled hierarchically. Because they are based on a graph structure. In the current work, we define two modular subsystems: the resistive module representing the membrane and the capacitive module representing solution compartments. Each module is analyzed based on thermodynamic processes, and all the subsystems are reintegrated into circuit theory in network thermodynamics. The epithelial transport system we introduce in the current study consists of five transport membranes and four solution compartments. Coupled dissipations in the system occur in the membrane subsystems and coupled free-energy increasing, or decreasing processes appear in solution compartment subsystems. These structural subsystems also consist of elementary thermodynamic processes: dissipations, free-energy change, and power conversions. We provide free and open access to the Python implementation to ensure our model is accessible, enabling the reader to explore the model through setting their simulations and reproducibility tests.

Keywords: Bond Graph, Epithelial Transport, Water Transport, Mathematical Modeling

Procedia PDF Downloads 71
13925 The Influence of Ligands Molecular Structure on the Antibacterial Activity of Some Metal Complexes

Authors: Sanja O. Podunavac-Kuzmanović, Lidija R. Jevrić, Strahinja Z. Kovačević

Abstract:

In last decade, metal-organic complexes have captured intensive attention because of their wide range of biological activities such as antibacterial, antifungal, anticancerous, antimicrobial and antiHIV. Therefore, it is of great importance for the development of coordination chemistry to explore the assembly of functional organic ligands with metal ion and to investigate the relationship between the structure and property. In view of our studies, we reasoned that benzimidazoles complexed to metal ions could act as a potent antibacterial agents. Thus, we have bioassayed the inhibitory potency of benzimidazoles and their metal salts (Co or Ni) against Gram negative bacteria Escherichia coli. In order to validate our in vitro study, we performed in silico studies using molecular docking software’s. The investigated compounds and their metal complexes (Co, Ni) showed good antibacterial activity against Escherichia coli. In silico docking studies of the synthesized compounds suggested that complexed benzimidazoles have a greater binding affinity and enhanced antibacterial activity in comparison with noncomplexed ligands. In view of their enhanced inhibitory properties we propose that the studied complexes can be used as potential pharmaceuticals. This study is financially supported by COST action CM1306 and the project No. 114-451-347/2015-02, financially supported by the Provincial Secretariat for Science and Technological Development of Vojvodina.

Keywords: benzimidazoles, complexes, antibacterial, Escherichia coli, metal

Procedia PDF Downloads 302
13924 SVM-RBN Model with Attentive Feature Culling Method for Early Detection of Fruit Plant Diseases

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

Abstract:

Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

Procedia PDF Downloads 45
13923 Genome-Wide Functional Analysis of Phosphatase in Cryptococcus neoformans

Authors: Jae-Hyung Jin, Kyung-Tae Lee, Yee-Seul So, Eunji Jeong, Yeonseon Lee, Dongpil Lee, Dong-Gi Lee, Yong-Sun Bahn

Abstract:

Cryptococcus neoformans causes cryptococcal meningoencephalitis mainly in immunocompromised patients as well as immunocompetent people. But therapeutic options are limited to treat cryptococcosis. Some signaling pathways including cyclic AMP pathway, MAPK pathway, and calcineurin pathway play a central role in the regulation of the growth, differentiation, and virulence of C. neoformans. To understand signaling networks regulating the virulence of C. neoformans, we selected the 114 putative phosphatase genes, one of the major components of signaling networks, in the genome of C. neoformans. We identified putative phosphatases based on annotation in C. neoformans var. grubii genome database provided by the Broad Institute and National Center for Biotechnology Information (NCBI) and performed a BLAST search of phosphatases of Saccharomyces cerevisiae, Aspergillus nidulans, Candida albicans and Fusarium graminearum to Cryptococcus neoformans. We classified putative phosphatases into 14 groups based on InterPro phosphatase domain annotation. Here, we constructed 170 signature-tagged gene-deletion strains through homologous recombination methods for 91 putative phosphatases. We examined their phenotypic traits under 30 different in vitro conditions, including growth, differentiation, stress response, antifungal resistance and virulence-factor production.

Keywords: human fungal pathogen, phosphatase, deletion library, functional genomics

Procedia PDF Downloads 346