Search results for: spiking neuron models

Authors: Naila Nasreen, Dianchen Lu

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This paper explores the dynamical behavior of the (2+1)-dimensional Boussinesq equation, which is a nonlinear water wave equation and is used to model wave packets in dispersive media with weak nonlinearity. This equation depicts how long wave made in shallow water propagates due to the influence of gravity. The (2+1)- dimensional Boussinesq equation combines the two-way propagation of the classical Boussinesq equation with the dependence on a second spatial variable, as that occurs in the two-dimensional Kadomstev- Petviashvili equation. This equation provides a description of head- on collision of oblique waves and it possesses some interesting properties. The governing model is discussed by the assistance of Ricatti equation mapping method, a relatively integration tool. The solutions have been extracted in different forms the solitary wave solutions as well as hyperbolic and periodic solutions. Moreover, the sensitivity analysis is demonstrated for the designed dynamical structural system’s wave profiles, where the soliton wave velocity and wave number parameters regulate the water wave singularity. In addition to being helpful for elucidating nonlinear partial differential equations, the method in use gives previously extracted solutions and extracts fresh exact solutions. Assuming the right values for the parameters, various graph in different shapes are sketched to provide information about the visual format of the earned results. This paper’s findings support the efficacy of the approach taken in enhancing nonlinear dynamical behavior. We believe this research will be of interest to a wide variety of engineers that work with engineering models. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complicated systems in a variety of fields, especially in ocean engineering.

Keywords: (2+1)-dimensional Boussinesq equation, solitary wave solutions, Ricatti equation mapping approach, nonlinear phenomena

Procedia PDF Downloads 100

Authors: Monique Somma

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As special education service delivery models are shifting in order to better meet the academic and social rights of students with exceptionalities, teaching practices must also align with these goals. This phenomenological case study explored the change experiences of special education teachers who have transitioned from teaching in a self-contained special education class to an inclusive class setting. Ten special educators who had recently changed their teaching roles to inclusive classrooms, completed surveys and participated in a focus group. Of the original ten educators, five chose to participate further in individual interviews. Data collected from the three methods was examined and compared for common themes. Emergent themes included, support and training, attitudes and perceptions, inclusive practice, growth and change, and teaching practice. The overall findings indicated that despite their special education training, these educators were challenged by their own beliefs and expectations, the attitudes of others and systematic barriers in the education system. They were equally surprised by the overall social and academic performance of students with exceptionalities in inclusive classes, as well as, the social and academic growth and development of the other students in the class. Over the course of their careers, they all identified an overall personal pedagogical shift, to some degree or another, which they contributed to the successful experiences of inclusion they had. They also recognized that collaborating with others was essential for inclusion to be successful. The findings from this study suggest several implications for professional development and training needs specific to special education teachers moving into inclusive settings. Maximizing the skills of teachers with special education experience in a Professional Learning Community (PLC) and mentorship opportunities would be beneficial to all staffs working toward creating inclusive classrooms and schools.

Keywords: attitudes and perceptions, inclusion of students with exceptionalities, special education teachers, teacher change

Procedia PDF Downloads 233

Authors: Yahia Massinissa, Afaf Benhouda, Mouloud Yahia

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Objective: The aim of this study was to investigate the toxicity; analgesic and anti-pyretic properties of standardized HA methanolic extract (HAMeOH) in vivo. Methods: The acute toxicity study was performed on rats while adopting the OECD-420 Guidelines (fixed dose procedure). Assessment of analgesic activity was performed in rats with two analgesic models. One was acetic acid induced writhing response and the other formalin-induced paw licking. The anti-pyretic effect was tested by Brewer’s yeast induced fever in rats. Results: For the acute toxicity test, the higher dose administration of 2000 mg/kg bw. of H.albus did not produce any toxic signs or deaths in rats. There were no significant differences (p>0.05) in the body and organ weights between control and treated groups. The (LD50) of 'H. albus' was higher than 2000 g/kg bw. In subacute toxicity study, no mortality and toxic signs were observed with the doses of 100 and 200 mg/kg bw. of extracts of for 28 consecutive days. These analgesic experimental results indicated that HAMeOH (100 mg/kg and 200 mg/kg) decreased the acetic acid-induced writhing responses and HAMeOH (100 mg/kg and 200 mg/kg) decreased the licking time in the second phase of the formalin test. Moreover, in the model of yeast-induced elevation of the body temperature HAMeOH showed dose-dependent lowering of the body temperature up to 3h at both the doses these results obtained, were comparable to that of paracetamol. Conclusion: The present findings indicate that the leaves of Hyoscyamus albus L. possess potent analgesic and antipyretic activity.

Keywords: Hyoscyamus albus, Umbilicus rupestris, secondary metabolites, NMR with protons, pharmacobiologic activities, methanolic extract

Procedia PDF Downloads 423

Authors: Marc Evenst Jn Jacques, Sophie Bernard

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Electrical and electronic applications, as well as rechargeable batteries, are common in any economy. They also contain a number of important and valuable metals. It is critical to investigate the impact of these new materials or volume sources on the metal market dynamics. This paper investigates the impact of responsible recycling within the European region on metal price volatility. As far as we know, no empirical studies have been conducted to assess the role of metal recycling in metal market price volatility. The goal of this paper is to test the claim that metal recycling helps to cushion price volatility. A set of circular economy indicators/variables, namely, 1) annual total trade values of recycled metals, 2) annual volume of scrap traded and 3) circular material use rate, and 4) information about recycling, are used to estimate the volatility of monthly spot prices of regular metals. A combination of the GARCH-MIDAS model for mixed frequency data sampling and a simple GARCH (1,1) model for the same frequency variables was adopted to examine the potential links between each variable and price volatility. We discovered that from 2010 to 2019, except for Nickel, scrap consumption (Millions of tons), Scrap Trade Values, and Recycled Material use rate had no significant impact on the price volatility of standard metals (Aluminum, Lead) and precious metals (Gold and Platinum). Worldwide interest in recycling has no impact on returns or volatility. Specific interest in metal recycling did have a link to the mean return equation for Aluminum, Gold and to the volatility equation for lead and Nickel.

Keywords: recycling, circular economy, price volatility, GARCH, mixed data sampling

Procedia PDF Downloads 56

Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: Katerina Bakela, Ioanna Zerva, Irene Athanassakis

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Lipopolysaccharide (LPS) is commonly used in murine sepsis models, which are largely associated with immunosuppression (incretion of MDSCs cells and Tregs, imbalance of inflammatory/anti-inflammatory cytokines) and collapse of the immune system. After adapting the LPS treatment to the needs of locally bred BALB/c mice, the present study explored the protective role of Micrococcus luteus peptidoglycan (PG) pre-activated vaccine-on chip in endotoxemia. The established protocol consisted of five daily intraperitoneal injections of 0.2mg/g LPS. Such protocol allowed longer survival, necessary in the prospect of the therapeutic treatment application. The so-called vaccine-on-chip consists of a 3-dimensional laser micro-texture Si-scaffold loaded with BALB/c mouse macrophages and activated in vitro with 1μg/ml PG, which exert its action upon subcutaneous implantation. The LPS treatment significantly decreased CD4+, CD8+, CD3z+, and CD19+ cells, while increasing myeloid-derived suppressor cells (MDSCs), CD25+, and Foxp3+ cells. These results were accompanied by increased arginase-1 activity in spleen cell lysates and production of IL-6, TNF-a, and IL-18 while acquiring severe sepsis phenotype as defined by the murine sepsis scoring. The in vivo application of PG pre-activated vaccine-on chip significantly decreased the percent of CD11b+, Gr1+, CD25+, Foxp3+ cells, and arginase-1 activity in the spleen of LPS-treated animals, while decreasing IL-6 and TNF-a in the serum, allowing survival to all animals tested and rescuing the severity of sepsis phenotype. In conclusion, these results reveal a promising mode of action of PG pre-activated vaccine-on chip in LPS endotoxemia, strengthening; thus, the use of treatment is septic patients.

Keywords: myeloid-derived suppressor cells, peptidoglycan, sepsis, Si-scaffolds

Procedia PDF Downloads 135

Authors: Bergun Meric Bingul, Cigdem Bulgan, Ozlem Tore, Mensure Aydin, Erdal Bal

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The aim of the study was to compare the effects of impact forces and some kinematic parameters with two different straight punch stance positions in boxing. 9 elite boxing athletes from the Turkish National Team (mean age± SD 19.33±2.11 years, mean height 174.22±3.79 cm, mean weight 66.0±6.62 kg) participated in this study as voluntarily. Boxing athletes performed one trial in straight punch technique for each two different stance positions (orthodox and southpaw stances) at sandbag. The trials were recorded at a frequency of 120Hz using eight synchronized high-speed cameras (Oqus 7+), which were placed, approximately at right- angles to one another. The three-dimensional motion analysis was performed with a Motion Capture System (Qualisys, Sweden). Data was transferred to Windows-based data acquisition software, which was QTM (Qualisys Track Manager). 11 segment models were used for determination of the kinematic variables (Calf, leg, punch, upperarm, lowerarm, trunk). Also, the sandbag was markered for calculation of the impact forces. Wand calibration method (with T stick) was used for field calibration. The mean velocity and acceleration of the punch; mean acceleration of the sandbag and angles of the trunk, shoulder, hip and knee were calculated. Stance differences’ data were compared with Wilcoxon test for using SPSS 20.0 program. According to the results, there were statistically significant differences found in trunk angle on the sagittal plane (yz) (p<0.05). There was a significant difference also found in sandbag acceleration and impact forces between stance positions (p < 0.05). Boxing athletes achieved more impact forces and accelerations in orthodox stance position. It is recommended that to use an orthodox stance instead of southpaw stance in straight punch technique especially for creating more impact forces.

Keywords: boxing, impact force, kinematics, straight punch, orthodox, southpaw

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

Procedia PDF Downloads 186

Authors: Roman Kulikov, Svetlana Kolesnikova

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Last decade Cloud Computing technologies have been rapidly becoming ubiquitous. Each year more and more organizations, corporations, internet services and social networks trust their business sensitive information to Public Cloud. The data storage in Public Cloud is protected by security mechanisms such as firewalls, cryptography algorithms, backups, etc.. In this way, however, only outsider attacks can be prevented, whereas virtualization tools can be easily compromised by insider. The protection of Public Cloud’s critical elements from internal intruder remains extremely challenging. A hypervisor, also called a virtual machine manager, is a program that allows multiple operating systems (OS) to share a single hardware processor in Cloud Computing. One of the hypervisor's functions is to enforce access control policies. Furthermore, it prevents guest OS from disrupting each other and from accessing each other's memory or disk space. Hypervisor is the one of the most critical and vulnerable elements in Cloud Computing infrastructure. Nevertheless, it has been poorly protected from being compromised by insider. By exploiting certain vulnerabilities, privilege escalation can be easily achieved in insider attacks on hypervisor. In this way, an internal intruder, who has compromised one process, is able to gain control of the entire virtual machine. Thereafter, the consequences of insider attacks in Public Cloud might be more catastrophic and significant to virtual tools and sensitive data than of outsider attacks. So far, almost no preventive security countermeasures have been developed. There has been little attention paid for developing models to assist risks mitigation strategies. In this paper formal model of insider attacks on hypervisor is designed. Our analysis identifies critical hypervisor`s vulnerabilities that can be easily compromised by internal intruder. Consequently, possible conditions for successful attacks implementation are uncovered. Hence, development of preventive security countermeasures can be improved on the basis of the proposed model.

Keywords: insider attack, public cloud, cloud computing, hypervisor

Procedia PDF Downloads 361

Authors: Maryam Shirmohammadi, Prasad K. D. V. Yarlagadda, YuanTong Gu

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The mechanical damage on the agricultural crop during and after harvesting can create high volume of damage on tissue. Uniaxial compression and tensile loading were performed on flesh and peel samples of pumpkin. To investigate the structural changes on the tissue, Scanning Electron Microscopy (SEM) was used to capture the cellular structure change before and after loading on tissue for tensile, compression and indentation tests. To obtain required mechanical properties of tissue for the finite element analysis (FEA) model, laser measurement sensors were used to record the lateral displacement of tissue under the compression loading. Uniaxial force versus deformation data were recorded using Universal Testing Machine for both tensile and compression tests. The experimental Results were employed to develop a material model with failure criteria. The results obtained by the simulation were compared with those obtained by experiments. Note that although modelling food materials’ behaviour is not a new concept however, majority of previous studies focused on elastic behaviour and damages under linear limit, this study, however, has developed FEA models for tensile and compressive loading of pumpkin flesh and peel samples using, as the first study, both elastic and elasto-plastic material types. In addition, pumpkin peel and flesh tissues were considered as two different materials with different properties under mechanical loadings. The tensile and compression loadings were used to develop the material model for a composite structure for FEA model of mechanical peeling of pumpkin as a tough skinned vegetable.

Keywords: compressive and tensile response, finite element analysis, poisson’s ratio, elastic modulus, elastic and plastic response, rupture and bio-yielding

Procedia PDF Downloads 331

Authors: Kateryna Zharan, Jan C. Bongaerts

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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

Procedia PDF Downloads 343

Authors: Titanilla Komenda

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Human-machine-collaboration defines a direct interaction between humans and machines to fulfil specific tasks. Those so-called collaborative machines are used without fencing and interact with humans in predefined workspaces. Even though, human-machine-collaboration enables a flexible adaption to variable degrees of freedom, industrial applications are rarely found. The reasons for this are not technical progress but rather limitations in planning processes ensuring safety for operators. Until now, humans and machines were mainly considered separately in the planning process, focusing on ergonomics and system performance respectively. Within human-machine-collaboration, those aspects must not be seen in isolation from each other but rather need to be analysed in interaction. Furthermore, a simulation model is needed that can validate the system performance and ensure the safety for the operator at any given time. Following on from this, a holistic simulation model is presented, enabling a simulative representation of collaborative tasks – including both, humans and machines. The presented model does not only include a geometry and a motion model of interacting humans and machines but also a numerical behaviour model of humans as well as a Boole’s probabilistic sensor model. With this, error scenarios can be simulated by validating system behaviour in unplanned situations. As these models can be defined on the basis of Failure Mode and Effects Analysis as well as probabilities of errors, the implementation in a collaborative model is discussed and evaluated regarding limitations and simulation times. The functionality of the model is shown on industrial applications by comparing simulation results with video data. The analysis shows the impact of considering human factors in the planning process in contrast to only meeting system performance. In this sense, an optimisation function is presented that meets the trade-off between human and machine factors and aids in a successful and safe realisation of collaborative scenarios.

Keywords: human-machine-system, human-robot-collaboration, safety, simulation

Procedia PDF Downloads 361

Authors: Maria Rodriguez-Gazquez, Sara Chaparro-Hernandez, Jose Rafael Gonzalez-Lopez

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Introduction: Nurses are models in healthy behaviors for their patients. This is why it is important for these professionals to not only have a good knowledge of healthy behaviors but also practice. Today’s nursing students will be tomorrow’s professionals and to fulfill their role in caring they not only need knowledge, they also must maintain behaviors which enable them to improve and protect both the health of others and their own. This is why the university is a unique environment of opportunities to foster the maximum potential of health. To care for others we first have to take care of ourselves. It is important for these behaviors in Nursing students to be evaluated during the years of their university education in order to design timely interventions which improve the health behaviors of the future professionals. Aim: The objective of this study was to evaluate the lifestyles of first year nursing students of two Universities. Methodology: Cross-sectional study. In 2014, 140 first year Nursing students of two Universities Seville –US- (Spain -Europe, n=37) and Antioquia –UA- (Colombia -South America, n=93) self-reported the FANTASTIC Lifestyle checklist. Results: Findings reveal that (I) UA students doubled the percentage of dangerous or bad lifestyles with respect to the US students, (II) the lifestyles are not appropriate in 1 of 3 of nursing students in both Universities, (II) there are statistically significant differences for family support items (higher in US), positive thinkers (higher in UA), the use of safety belts and alcohol consumption before driving (higher in US). Discussion: The nursing students are mostly young people who are at a stage in which some of the most important behaviors for adult life can still be molded. It is necessary to develop educational interventions in their Nursing curricula to strengthen healthy behaviours during training. Nursing Schools not only have the duty to train professionals, but to also be agents that foster the health, welfare and quality of those who study and work there. It must encourage knowledge and skills oriented to healthy lifestyles.

Keywords: cross-sectional studies, life style, nursing students, questionnaires

Procedia PDF Downloads 273

Authors: Vephkhvia Grigalashvili

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The defense of Georgia is every citizen’s duty. The present article reviews the principles and standards of gender policy in the Georgian national defense sector. In addition, it looks at mechanisms for ensuring gender equality, going through the relevant Georgian legislation. Furthermore, this work aims to conduct a comparative analysis of defense models of Georgia, Finland, and the Baltic States in order to identify core institutional challenges. The study produced the following findings:(a) The national defense planning is based on the Total Defense approach, which implies a wide involvement of the country`s population in state defense. (b) This political act does not specify gender equality aspects of the Total Defense strategy; (c) According to the Constitution of Georgia, irrespective of gender factors, every citizen of Georgia is legally obliged to participate in state security activities. However, the state has an authority (power of choice) to decide which gender group (male or/and female citizen) must fulfill above mentioned their constitutional commitment. For instance, completion of compulsory military and reserve military services is a male citizen’s duty, whereas professional military service is equally accessible to both genders. The study concludes that effective implementation of the Total Defense concept largely depends on how Georgia uses its capabilities and human resources. Based on the statistical fact that more than 50% of the country’s population are women, Georgia has to elaborate on relevant institutional mechanisms for implementation of gender equality in the national defense organization. In this regard, it would be advisable: (i) to give the legal opportunity to women to serve in compulsory military service, and (ii) to develop labor reserve service as a part of the anti-crisis management system of Georgia.

Keywords: gender in defense organisation, gender mechanisms, gender in defense policy, gender policy

Procedia PDF Downloads 161

Authors: Scott Draper, Nat Benjanuvatra, Grant Landers, Terry Griffiths, Justin Geldard

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Open water swimming has been an Olympic sport since 2008 and is growing in popularity world-wide as a low impact form of exercise. Unlike pool swimming, open water swimmers experience a range of different environmental conditions, including surface waves, variable water temperature, aquatic life, and ocean currents. This presentation will describe experimental research to investigate how freestyle swimming behaviour and performance is influenced by surface waves. A group of 12 swimmers were instructed to swim freestyle in the 54 m long wave flume located at The University of Western Australia’s Coastal and Offshore Engineering Laboratory. A variety of different regular waves were simulated, varying in height (up to 0.3 m), period (1.25 – 4s), and direction (with or against the swimmer). Swimmer’s velocity and acceleration, respectively, were determined from video recording and inertial sensors attached to five different parts of the swimmer’s body. The results illustrate how the swimmers stroke rate and the wave encounter frequency influence their forward speed and how particular wave conditions can benefit or hinder performance. Comparisons to simplified mathematical models provide insight into several aspects of performance, including: (i) how much faster swimmers can travel when swimming with as opposed to against the waves, and (ii) why swimmers of lesser ability are expected to be affected proportionally more by waves than elite swimmers. These findings have implications across the spectrum from elite to ‘weekend’ swimmers, including how they are coached and their ability to win (or just successfully complete) iconic open water events such as the Rottnest Channel Swim held annually in Western Australia.

Keywords: open water, surface waves, wave height/length, wave flume, stroke rate

Procedia PDF Downloads 112

Authors: Tuğçe Kiper Elibol, İbrahim Uslan, Mehmet Ali Guler, Murat Buyuk, Uğur Yolum

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According to the FAA report, 142603 bird strikes were reported for a period of 24 years, between 1990 – 2013. Bird strike with aerospace structures not only threaten the flight security but also cause financial loss and puts life in danger. The statistics show that most of the bird strikes are happening with the nose and the leading edge of the wings. Also, a substantial amount of bird strikes is absorbed by the jet engines and causes damage on blades and engine body. Crash proof designs are required to overcome the possibility of catastrophic failure of the airplane. Using computational methods for bird strike analysis during the product development phase has considerable importance in terms of cost saving. Clearly, using simulation techniques to reduce the number of reference tests can dramatically affect the total cost of an aircraft, where for bird strike often full-scale tests are considered. Therefore, development of validated numerical models is required that can replace preliminary tests and accelerate the design cycle. In this study, to verify the simulation parameters for a bird strike analysis, several different numerical options are studied for an impact case against a primitive structure. Then, a representative bird mode is generated with the verified parameters and collided against the leading edge of a training aircraft wing, where each structural member of the wing was explicitly modeled. A nonlinear explicit dynamics finite element code, LS-DYNA was used for the bird impact simulations. SPH methodology was used to model the behavior of the bird. Dynamic behavior of the wing superstructure was observed and will be used for further design optimization purposes.

Keywords: bird impact, bird strike, finite element modeling, smoothed particle hydrodynamics

Procedia PDF Downloads 327

Authors: Nadia Allouache, Mohamed Belmedani

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Energy source is a sustainable, totally inexhaustible and environmentally friendly alternative to the fossil fuels available. It is a renewable and economical energy that can be harnessed sustainably over the long term and thus stabilizes energy costs. Solar cooling technologies have been developed to decrease the augmentation electricity consumption for air conditioning and to displace the peak load during hot summer days. A numerical analysis of thermal and solar performances of an annular finned adsorber, which is the most important component of the adsorption solar refrigerating system, is considered in this work. Different adsorbent/adsorbate pairs, such as activated carbon AC35/methanol, activated carbon AC35/ethanol, and activated carbon BPL/Ammoniac, are undertaken in this study. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular finned adsorber. The Wilson and Dubinin- Astakhov models of the solid-adsorbate equilibrium are used to calculate the adsorbed quantity. The porous medium and the fins are contained in the annular space, and the adsorber is heated by solar energy. Effects of key parameters on the adsorbed quantity and on the thermal and solar performances are analysed and discussed. The AC35/methanol pair is the best pair compared to BPL/Ammoniac and AC35/ethanol pairs in terms of system performance. The system performances are sensitive to the fin geometry. For the considered data measured for clear type days of July 2023 in Algeria and Morocco, the performances of the cooling system are very significant in Algeria.

Keywords: activated carbon AC35-methanol pair, activated carbon AC35-ethanol pair, activated carbon BPL-ammoniac pair, annular finned adsorber, performance coefficients, numerical analysis, solar cooling system

Procedia PDF Downloads 55

Authors: M. Rahou, A. J. Andrews, G. Rosengarten

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One of the main challenges in high-temperature solar thermal applications transfer concentrated solar radiation to the load with minimum energy loss and maximum overall efficiency. The use of a solar concentrator in conjunction with bundled optical fibres has potential advantages in terms of transmission energy efficiency, technical feasibility and cost-effectiveness compared to a conventional heat transfer system employing heat exchangers and a heat transfer fluid. In this paper, a theoretical and computer simulation method is described to estimate the net solar radiation transmission from a solar concentrator into and through optical fibres to a thermal application at the end of the fibres over distances of up to 100 m. A key input to the simulation is the angular distribution of radiation intensity at each point across the aperture plane of the optical fibre. This distribution depends on the optical properties of the solar concentrator, in this case, a parabolic mirror with a small secondary mirror with a common focal point and a point-focus Fresnel lens to give a collimated beam that pass into the optical fibre bundle. Since solar radiation comprises a broad band of wavelengths with very limited spatial coherence over the full range of spectrum only ray tracing models absorption within the fibre and reflections at the interface between core and cladding is employed, assuming no interference between rays. The intensity of the radiation across the exit plane of the fibre is found by integrating across all directions and wavelengths. Results of applying the simulation model to a parabolic concentrator and point-focus Fresnel lens with typical optical fibre bundle will be reported, to show how the energy transmission varies with the length of fibre.

Keywords: concentrated radiation, fibre bundle, parabolic dish, fresnel lens, transmission

Procedia PDF Downloads 564

Authors: Shuxin Li, Peihao Song, Haixiao Hu, Dongfeng Cao

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The interactive deformation and failure mechanisms, including local bucking/delamination propagation and global bucking, are investigated in this paper with numerical simulation and validation with experimental results. Three dimensional numerical models using ABAQUS brick elements combined with cohesive elements and contact elements are developed to simulate the deformation and failure characteristics of composite laminates with and without delamination under compressive loading. The zero-thickness cohesive elements are inserted on the possible path of delamination propagation, and the inter-laminate behavior is characterized by the mixed-mode traction-separation law. The numerical simulations identified the complex feature of interaction among local buckling and/or delamination propagation and final global bucking for composite laminates with delamination under compressive loading. Firstly there is an interaction between the local buckling and delamination propagation, i.e., local buckling induces delamination propagation, and then delamination growth further enhances the local buckling. Secondly, the interaction between the out-plan deformation caused by local buckling and the global bucking deformation results in final failure of the composite laminates. The simulation results are validated by the good agreement with the experimental results published in the literature. The numerical simulation validated with experimental results revealed that the degradation of the load capacity, in particular of the compressive strength of composite structures with delamination, is mainly attributed to the combined local buckling/delamination propagation effects. Consequently, a simple field-bolt repair approach that can hinder the local buckling and prevent delamination growth is explored. The analysis and simulation results demonstrated field-bolt repair could effectively restore compressive strength of composite laminates with delamination.

Keywords: cohesive elements, composite laminates, delamination, local and global bucking, field-bolt repair

Procedia PDF Downloads 120

Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

Procedia PDF Downloads 316

Authors: Iveta Ludviga, Agita Kalvina

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This paper aims to link together the concepts of job satisfaction, work engagement, trust, job meaningfulness and loyalty to the organisation focusing on specific type of employment–academic jobs. The research investigates the relationships between job satisfaction, work engagement and loyalty as well as the impact of trust and job meaningfulness on the work engagement and loyalty. The survey was conducted in one of the largest Latvian higher education institutions and the sample was drawn from academic staff (n=326). Structured questionnaire with 44 reflective type questions was developed to measure toe constructs. Data was analysed using SPSS and Smart-PLS software. Variance based structural equation modelling (PLS-SEM) technique was used to test the model and to predict the most important factors relevant to employee engagement and loyalty. The first order model included two endogenous constructs (loyalty and intention to stay and recommend, and employee engagement), as well as six exogenous constructs (feeling of fair treatment and trust in management; career growth opportunities; compensation, pay and benefits; management; colleagues; teamwork; and finally job meaningfulness). Job satisfaction was developed as second order construct and both: first and second order models were designed for data analysis. It was found that academics are more engaged than satisfied with their work and main reason for that was found to be job meaningfulness, which is significant predictor for work engagement, but not for job satisfaction. Compensation is not significantly related to work engagement, but only to job satisfaction. Trust was not significantly related neither to engagement, nor to satisfaction, however, it appeared to be significant predictor of loyalty and intentions to stay with the University. This paper revealed academic jobs as specific kind of employment where employees can be more engaged than satisfied and highlighted the specific role of job meaningfulness in the University settings.

Keywords: job satisfaction, job meaningfulness, higher education, work engagement

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Authors: Kunwar Paritosh, Sanjay Mathur, Monika Yadav, Paras Gandhi, Subodh Kumar, Nidhi Pareek, Vivekanand Vivekanand

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A significant fraction of energy is wasted every year managing the biodegradable organic waste inadequately as development and sustainability are the inherent enemies. The management of these waste is indispensable to boost its optimum utilization by converting it to renewable energy resource (here biogas) through anaerobic digestion and to mitigate greenhouse gas emission. Food and yard wastes may prove to be appropriate and potential feedstocks for anaerobic co-digestion for biogas production. The present study has been performed to explore the synergistic effect of co-digesting food waste and yard trimmings from MNIT campus for enhanced biogas production in different ratios in batch tests (37±10C, 90 rpm, 45 days). The results were overwhelming and showed that blending two different organic waste in proper ratio improved the biogas generation considerably, with the highest biogas yield (2044±24 mLg-1VS) that was achieved at 75:25 of food waste to yard waste ratio on volatile solids (VS) basis. The yield was 1.7 and 2.2 folds higher than the mono-digestion of food or yard waste (1172±34, 1016±36mLg-1VS) respectively. The increase in biogas production may be credited to optimum C/N ratio resulting in higher yield. Also Adding TiO2 nanoparticles showed virtually no effect on biogas production as sometimes nanoparticles enhance biogas production. ICP-MS, FTIR analysis was carried out to gain an insight of feedstocks. Modified Gompertz and logistics models were applied for the kinetic study of biogas production where modified Gompertz model showed goodness-of-fit (R2=0.9978) with the experimental results.

Keywords: anaerobic co-digestion, biogas, kinetics, nanoparticle, organic waste

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Authors: Linda Boussaid, Farid Brahim Belaribi

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The physico-chemical properties of liquid materials in the industrial field, in general, and in that of the chemical industries, in particular, constitutes a prerequisite for the design of equipment, for the resolution of specific problems (related to the techniques of purification and separation, at risk in the transport of certain materials, etc.) and, therefore, at the production stage. Chloroalkanes, ethers constitute three chemical families having an industrial, theoretical and environmental interest. For example, these compounds are used in various applications in the chemical and pharmaceutical industries. In addition, they contribute to the particular thermodynamic behavior (deviation from ideality, association, etc.) of certain mixtures which constitute a severe test for predictive theoretical models. Finally, due to the degradation of the environment in the world, a renewed interest is observed for ethers, because some of their physicochemical properties could contribute to lower pollution (ethers would be used as additives in aqueous fuels.). This work is a thermodynamic, experimental and theoretical study of the volumetric properties of liquid binary systems formed from compounds belonging to the chemical families of chloroalkanes, ethers, having an industrial, theoretical and environmental interest. Experimental determination of the densities and excess volumes of the systems studied, at different temperatures in the interval [278.15-333.15] K and at atmospheric pressure, using an AntonPaar vibrating tube densitometer of the DMA5000 type. This contribution of experimental data, on the volumetric properties of the binary liquid mixtures of 1,2-dichloroethane with an ether, supplemented by an application of the theoretical model of Prigogine-Flory-Patterson PFP, will probably contribute to the enrichment of the thermodynamic database and the further development of the theory of Flory in its Prigogine-Flory-Patterson (PFP) version, for a better understanding of the thermodynamic behavior of these liquid binary mixtures

Keywords: prigogine-flory-patterson (pfp), propriétés volumétrique , volume d’excés, ethers

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Authors: Sin Ying Tan, Mohammed Alloghani, A. J. Aljaaf, Abir Hussain, Jamila Mustafina

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Industry 4.0 is a term frequently used to describe the new upcoming industry era. Higher education institutions aim to prepare students to fulfil the future industry needs. Advancement of digital technology has paved the way for the evolution of education and technology. Evolution of education has proven its conservative nature and a high level of resistance to changes and transformation. The gap between the industry's needs and competencies offered generally by education is revealing the increasing need to find new educational models to face the future. The aim of this study was to identify the main issues faced by both universities and students in preparing the future workforce. From December 2018 to April 2019, a regional qualitative study was undertaken in Liverpool, United Kingdom (UK). Interviews were conducted with employers, faculty members and undergraduate students, and the results were analyzed using the open coding method. Four main issues had been identified, which are the characteristics of the future workforce, student's readiness to work, expectations on different roles played at the tertiary education level and awareness of the latest trends. The finding of this paper concluded that the employers and academic practitioners agree that their expectations on each other’s roles are different and in order to face the rapidly changing technology era, students should not only have the right skills, but they should also have the right attitude in learning. Therefore, the authors address this issue by proposing a learning framework known as 'ASK SUMA' framework as a guideline to support the students, academicians and employers in meeting the needs of 'Industry 4.0'. Furthermore, this technology era requires the employers, academic practitioners and students to work together in order to face the upcoming challenges and fast-changing technologies. It is also suggested that an interactive system should be provided as a platform to support the three different parties to play their roles.

Keywords: attitude, expectations, industry needs, knowledge, skills

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Authors: Svetlana Guryeva, Inna Kornienko, Elena Petersen

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At present, translational medicine is a rapidly developing branch of biomedicine. The main idea of translational medicine is a practical application of fundamental research. One of the possible applications for translational medicine is researching therapies that improve human age-related organism condition. To fill the gap between experiments and clinical practice, it is necessary to create the standardized system for the investigation of different effects on cellular aging models. In this study, primary human fibroblasts derived from patients of different ages were used as a cellular aging model. The senescence-associated β-galactosidase activity, lipofuscin, γ-H2AX, the reactive oxygen species level, and cell death markers (annexin V/propidium iodide) were used as biomarkers of the cell functional state. The effects of damaging exposures (oxidative stress and heat shock), potential positive factors (metformin and acetaminophen), and their combinations were investigated using the described biomarkers. Oxidative stress and heat shock caused the increase in the levels of all biomarkers, and only the cells from young patients partly coped with stress 3 days after the exposures. Metformin improved the state of pretreatment cells from young and old patients. The acetaminophen did not show significant changes in the biomarker levels compare to the action of metformin. This study proved the opportunity to develop a standardized screening system based on biomarkers of the cell functional state to identify potential positive or negative effects of some physical and chemical exposures. Moreover, such a system can be useful for the aims of regenerative medicine to determine the effect of cell pretreatment before transplantation.

Keywords: biomarkers, primary fibroblasts, regenerative medicine, senescence, test system, translational medicine

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Authors: Hamed Reza Heshmat Mohajer, Lan Ding, Mattheos Santamouris

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One of the worst environmental dangers for people who live in cities is the Urban Heat Island (UHI) impact which is anticipated to become stronger in the coming years as a result of climate change. Accordingly, the key aim of this paper is to study the interaction between the urban configuration and mitigation strategies including increasing albedo of the urban environment (reflective material), implementation of Urban Green Infrastructure (UGI) and/or a combination thereof. To analyse the microclimate models of different urban categories in the metropolis of Sydney, this study will assess meteorological parameters using a 3D model simulation tool of computational fluid dynamics (CFD) named ENVI-met. In this study, four main parameters are taken into consideration while assessing the effectiveness of UHI mitigation strategies: ambient air temperature, wind speed/direction, and outdoor thermal comfort. Layouts with present condition simulation studies from the basic model (scenario one) are taken as the benchmark. A base model is used to calculate the relative percentage variations between each scenario. The findings showed that maximum cooling potential across different urban layouts can be decreased by 2.15 °C degrees by combining high-albedo material with flora; besides layouts with open arrangements(OT1) present a highly remarkable improvement in ambient air temperature and outdoor thermal comfort when mitigation technologies applied compare to compact counterparts. Besides all layouts present a higher intensity on the maximum ambient air temperature reduction rather than the minimum ambient air temperature. On the other hand, Scenarios associated with an increase in greeneries are anticipated to have a slight cooling effect, especially on high-rise layouts.

Keywords: sustainable urban development, urban green infrastructure, high-albedo materials, heat island effect

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Authors: Dian Guan

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With the wide application of multimedia and the Internet, the development of teaching theories, and the implementation of teaching reforms, many different university English classroom teaching modes have emerged. The university English teaching mode is changing from the traditional teaching mode based on conversation and text to the multimodal English teaching mode containing discussion, pictures, audio, film, etc. Applying university English teaching models is conducive to cultivating lifelong learning skills. In addition, lifelong learning skills can also be called learners' autonomous learning skills. Learners' independent learning ability has a significant impact on English learning. However, many university students, especially art and design students, don't know how to learn individually. When they become university students, their English foundation is a relative deficiency because they always remember the language in a traditional way, which, to a certain extent, neglects the cultivation of English learners' independent ability. As a result, the autonomous learning ability of most university students is not satisfactory. The participants in this study were 60 students and one teacher in their first year at a university in western China. Two observations and interviews were conducted inside and outside the classroom to understand the impact of a multimodal teaching model of university English on students' autonomous learning ability. The results were analyzed, and it was found that the multimodal teaching model of university English significantly affected learners' autonomy. Incorporating classroom presentations and poster exhibitions into multimodal teaching can increase learners' interest in learning and enhance their learning ability outside the classroom. However, further exploration is needed to develop multimodal teaching materials and evaluate multimodal teaching outcomes. Despite the limitations of this study, the study adopts a scientific research method to analyze the impact of the multimodal teaching mode of university English on students' independent learning ability. It puts forward a different outlook for further research on this topic.

Keywords: art university, EFL education, learner autonomy, multimodal pedagogy

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Authors: Colm Barcoe, Garvan Whelan

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Over the past five years, visitations of American holidaymakers to Ireland have grown exponentially owing to the online strategies of Tourism Ireland, a Destination Marketer (DMO) with a meagre budget which is extended by their understanding of best practices to maximise their monetary allowance. This suggested framework incorporates a range of Key Performance Indicators (KPI’s) such as financial, marketing, and operational that offer a scale of measurement from which the Irish DMO can monitor the success of each promotional campaign when targeting the US and Canada. These are presented not as final solutions but rather as suggestions based on empirical evidence obtained from both primary and secondary sources. This research combines the wisdom extracted through qualitative methodologies with the objective of understanding the processes that drive both emergent and agile strategies. The Study extends the work relative to performance and examines the role of social media in the context of promoting Ireland to North America. There are two main themes that are identified and analysed in this investigation, these are the approach of the DMO when advocating Ireland as a brand and the benefits of digital platforms set against a proposed scale of KPIs, such as destination marketing, brand positioning, and identity development. The key narrative of this analysis is to focus on the power of social media when capitalising upon marketing opportunities, operating on a relatively small budget. This will always be a relevant theme of discussion due to the responsibility of an organisation like Tourism Ireland operating under the restraints imposed by government funding. The overall conclusions of this research may help inform those concerned with the implementing of social media strategies develop clearer models of measurement when promoting a destination to North America. The suggestions of this study will benefit small and medium enterprises particularly.

Keywords: destination marketing, framework, measure, performance

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Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

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Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

Procedia PDF Downloads 286