Search results for: modified Jones model

Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Wan-Tzu Yen, Yu-Chen Luo, I-Ping Liu, Po-Hsuan Yeh, Sheng-Hsun Fu, Yuh-Lang Lee

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Self-assembled characteristics and adsorption performance of 1-dodecylamine molecules on gold (Au) (111) surfaces were characterized via cyclic voltammetry (CV), surface-enhanced infrared absorption spectroscopy (SEIRAS) and scanning tunneling microscopy (STM). The present study focused on the formation of 1-dodecylamine (DDA) on a gold surface with respect to the ex-situ arrangement of an adlayer on the Au(111) surface, and phase transition at potential dynamics carried out by EC-STM. This study reveals that alkyl amine molecules were formed an adsorption pattern with highly regular “lie down shape” on Au(111) surface, even in an extreme acid system (pH = 1). Acidic electrolyte (HClO₄) could protonate the surface of alkyl amine of a monolayer of the gold surface when potential shifts to negative. The quite stability of 1-dodecylamine on the gold surface maintained the monolayer across the potential window (0.1-0.8V). This transform model was confirmed by EC-STM. In addition, amine-modified Au(111) electrode adlayer used to examine how to affect an electron transfer across an interface using [Fe(CN)₆]³⁻/[Fe(CN)₆]⁴⁻ redox pair containing 0.1 M HClO₄ solution.

Keywords: cyclic voltammetry, dodecylamine, gold (Au)(111), scanning tunneling microscopy, self-assembled monolayer, surface-enhanced infrared absorption spectroscopy

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

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Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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Authors: Anna Piasek, Anna Szymkiewicz, Gabriela Wiktor, Jolanta Pulit-Prociak, Marcin Banach

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Carbon dots (CDs) have great potential for application in many fields of science. They are characterized by fluorescent properties that can be manipulated. The nanomaterial has many advantages in addition to its unique properties. CDs may be obtained easily, and they undergo surface functionalization in a simple way. In addition, there is a wide range of raw materials that can be used for their synthesis. An interesting possibility is the use of numerous waste materials of natural origin. In the research presented here, the synthesis of CDs was carried out according to the principles of Green chemistry. Beet molasses was used as a natural raw material. It has a high sugar content. This makes it an excellent high-carbon precursor for obtaining CDs. To increase the fluorescence effect, we modified the surface of CDs with silver (Ag-CDs) nanoparticles. The process of obtaining CQD was based on the hydrothermal method by applying microwave radiation. Silver nanoparticles were formed via the chemical reduction method. The synthesis plans were performed on the Design of the Experimental method (DoE). Variable process parameters such as concentration of beet molasses, temperature and concentration of nanosilver were used in these syntheses. They affected the obtained properties and particle parameters. The Ag-CDs were analyzed by UV-vis spectroscopy. The fluorescence properties and selection of the appropriate excitation light wavelength were performed by spectrofluorimetry. Particle sizes were checked using the DLS method. The influence of the input parameters on the obtained results was also studied.

Keywords: fluorescence, modification, nanosilver, molasses, Green chemistry, carbon dots

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Authors: Maria Luisa Nozawa Ribeiro, Maria Teresa Miceli Kerbauy

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This paper aims to present the theories of public participation in order to understand the context of the public GMO (Genetic Modified Organisms) policies in Brazil, highlighting the characteristics of its configuration and the dialog with the experts. As a controversy subject, the commercialization of GMO provoked manifestation of some popular and environmental representative groups questioning the decisions of policy makers and experts on the matter. Many aspects and consequences of the plantation and consumption of this crops emerged and the safety of this technology was questioned. Environmentalists, Civil Right's movement, representatives of rural workers, farmers and organics producers, etc. demonstrated their point of view, also sustained by some experts of medical, genetical, environmental, agronomical sciences, etc. fields. Despite this movement, the precautionary principle (risk management), implemented in 1987, suggested precaution facing new technologies and innovations in the sustainable development society. This principle influenced many legislation and regulation on GMO around the world, including Brazil, which became a reference among the world regulatory GMO systems. The Brazilian legislation ensures the citizens participation on GMO discussion, characteristic that was important to establish the connection between the subject and the participation theory. These deliberation spaces materialized in Brazil through the "Public Audiences", which are managed by the National Biosafety Technical Commission (CTNBio), the department responsible for controlling the research, production and commercialization of GMOs in Brazil.

Keywords: public engagement, public participation, science and technology studies, transgenic politics

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Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: Misagh Ghobadi, Rich Crane, Karen Hudson-Edwards, Clemens Vinzenz Ullmann

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Lithium is recognized as the critical energy metal of the 21st century, comparable in importance to coal in the 19th century and oil in the 20th century, often termed 'white gold'. Current global demand for lithium, estimated at 0.95-0.98 million metric tons (Mt) of lithium carbonate equivalent (LCE) annually in 2024, is projected to rise to 1.87 Mt by 2027 and 3.06 Mt by 2030. Despite anticipated short-term stability in supply and demand, meeting the forecasted 2030 demand will require the lithium industry to develop an additional capacity of 1.42 Mt of LCE annually, exceeding current planned and ongoing efforts. Brine resources constitute nearly 65% of global lithium reserves, underscoring the importance of exploring lithium recovery from underutilized sources, especially geothermal brines. However, conventional lithium extraction from brine deposits faces challenges due to its time-intensive process, low efficiency (30-50% lithium recovery), unsuitability for low lithium concentrations (<300 mg/l), and notable environmental impacts. Addressing these challenges, direct lithium extraction (DLE) methods have emerged as promising technologies capable of economically extracting lithium even from low-concentration brines (>50 mg/l) with high recovery rates (75-98%). However, most studies (70%) have predominantly focused on synthetic brines instead of native (natural/real), with limited application of these approaches in real-world case studies or industrial settings. This study aims to bridge this gap by investigating a geothermal brine sample collected from a real case study site in the UK. A Mn-based lithium-ion sieve (LIS) adsorbent was synthesized and employed to selectively extract lithium from the sample brine. Adsorbents with a Li:Mn molar ratio of 1:1 demonstrated superior lithium selectivity and adsorption capacity. Furthermore, the pristine Mn-based adsorbent was modified through transition metals doping, resulting in enhanced lithium selectivity and adsorption capacity. The modified adsorbent exhibited a higher separation factor for lithium over major co-existing cations such as Ca, Mg, Na, and K, with separation factors exceeding 200. The adsorption behaviour was well-described by the Langmuir model, indicating monolayer adsorption, and the kinetics followed a pseudo-second-order mechanism, suggesting chemisorption at the solid surface. Thermodynamically, negative ΔG° values and positive ΔH° and ΔS° values were observed, indicating the spontaneity and endothermic nature of the adsorption process.

Keywords: adsorption, critical minerals, DLE, geothermal brines, geochemistry, lithium, lithium-ion sieves

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Authors: Anjani Kumar Tiwari, Neelam Kumari, Anil Mishra

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The 18-kDa translocator protein (TSPO) previously called as peripheral benzodiazepine receptor, is proven biomarker for variety of neuroinflammation. TSPO is tryptophane rich five transmembranal protein found on outer mitochondrial membrane of steroid synthesising and immunomodulatory cells. In case of neuronal damage or inflammation the expression level of TSPO get upregulated as an immunomodulatory response. By utilizing Benzoxazolone as a basic scaffold, series of TSPO ligands have been designed followed by their screening through in silico studies. Synthesis has been planned by employing convergent methodology in six high yielding steps. For the synthesized ligands the ‘in vitro’ assay was performed to determine the binding affinity in term of Ki. On ischemic rat brain, autoradiography studies were also carried to check the specificity and affinity of the designed radiolabelled ligand for TSPO.Screening was performed on the basis of GScore of CADD based schrodinger software. All the modified and better prospective compound were successfully carried out and characterized by spectroscopic techniques (FTIR, NMR and HRMS). In vitro binding assay showed best binding affinity Ki = 6.1+ 0.3 for TSPO over central benzodiazepine receptor (CBR) Ki > 200. ARG studies indicated higher uptake of two analogues on the lesion side compared with that on the non-lesion side of ischemic rat brains. Displacement experiments with unlabelled ligand had minimized the difference in uptake between the two sides which indicates the specificity of the ligand towards TSPO receptor.

Keywords: TSPO, PET, imaging, Acetamidobenzoxazolone

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Authors: Jiajun Duan, Yang Li, Jianan Gao, Runzi Cao, Enxiang Shang, Wen Zhang

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Reactive oxygen species (ROS) generation is considered as an important photoaging mechanism of microplastics (MPs) and nanoplastics (NPs). To elucidate the ROS-induced MP/NP aging processes in water under UV365 irradiation, we examined the effects of surface coatings, polymer types, and grain sizes on ROS generation and photoaging intermediates. Bare polystyrene (PS) NPs generated hydroxyl radicals (•OH) and singlet oxygen (¹O₂), while coated PS NPs (carboxyl-modified PS (PS-COOH), amino-modified PS (PS-NH₂)) and PS MPs generated fewer ROS due to coating scavenging or size effects. Polypropylene, polyethylene, polyvinyl chloride, polyethylene terephthalate, and polycarbonate MPs only generated •OH. For aromatic polymers, •OH addition preferentially occurred at benzene rings to form monohydroxy polymers. Excess •OH resulted in H abstraction, C-C scission, and phenyl ring opening to generate aliphatic ketones, esters, aldehydes, and aromatic ketones. For coated PS NPs, •OH preferentially attacked the surface coatings to result in decarboxylation and deamination reactions. For aliphatic polymers, •OH attack resulted in the formation of carbonyl groups from peracid, aldehyde, or ketone via H abstraction and C-C scission. Moreover, ¹O₂ might participate in phenyl ring opening for PS NPs and coating degradation for coated PS NPs. This study facilitates understanding the ROS-induced weathering process of NPs/MPs in water under UV irradiation.

Keywords: microplastics, nanoplastics, photoaging, reactive oxygen species, surface coating

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Authors: Szymon Kugler, Krzysztof Kowalczyk, Tadeusz Spychaj

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An addition of carbon nanotubes (CNT) can simultaneously improve many features of epoxy coatings, i.e. electrical, mechanical, functional and thermal. Unfortunately, this nanofiller negatively affects visual properties of the coatings, such as transparency and gloss. The main reason for the low visual performance of CNT-modified epoxy coatings is the lack of compatibility between CNT and popular amine curing agents, although epoxy resins based on bisphenol A are indisputable good CNT dispersants. This is a serious obstacle in utilization of the coatings in advanced applications, demanding both high transparency and electrical conductivity. The aim of performed investigations was to find amine curing agents exhibiting affinity for CNT, and ensuring good performance of epoxy coatings with them. Commercially available CNT was dispersed in epoxy resin, as well as in different aliphatic, cycloaliphatic and aromatic amines, using one of two dispergation methods: ultrasonic or mechanical. The CNT dispersions were subsequently used in the preparation of epoxy coating compositions and coatings on a transparent substrate. It was found that amine derivative of bio-based cardanol, as well as modified o-tolylbiguanide exhibit significant CNT, dispersing properties, resulting in improved transparent/electroconductive performance of epoxy coatings. In one of prepared coating systems just 0.025 wt.% (250 ppm) of CNT was enough to obtain coatings with semi conductive properties, 83% of transparency as well as perfect chemical resistance to methyl-ethyl ketone and improved thermal stability. Additionally, a theory of the influence of amine chemical structure on CNT dispersing properties was proposed.

Keywords: bio-based cardanol, carbon nanotubes, epoxy coatings, tolylbiguanide

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Authors: T. M. Ismail, M. A. El-Salam

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A mathematical model study was carried out to investigate gasification of biomass fuels using high-temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promising way in its capability and sensitivity for the parameter effects that influence the gasification process.

Keywords: computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

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Authors: V. Bastian Aguila, C. Diego Vasco, P. Paula Galvez, R. Paula Zapata

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The main results of an experimental study of the effect of temperature and nanoparticle concentration on thermal conductivity and viscosity of a nanofluid are shown. The nanofluid was made by using octadecane as a base fluid and CuO spherical nanoparticles of 75 nm (MkNano). Since the base fluid is a phase change material (PCM) to be used in thermal storage applications, the engineered nanofluid is referred as nanoPCM. Three nanoPCM were prepared through the two-step method (2.5, 5.0 and 10.0%wv). In order to increase the stability of the nanoPCM, the surface of the CuO nanoparticles was modified with sodium oleate, and it was verified by IR analysis. The modified CuO nanoparticles were dispersed by using an ultrasonic horn (Hielscher UP50H) during one hour (amplitude of 180 μm at 50 W). The thermal conductivity was measured by using a thermal properties analyzer (KD2-Pro) in the temperature range of 30ºC to 40ºC. The viscosity was measured by using a Brookfield DV2T-LV viscosimeter to 30 RPM in the temperature range of 30ºC to 55ºC. The obtained results for the nanoPCM showed that thermal conductivity is almost constant in the analyzed temperature range, and the viscosity decreases non-linearly with temperature. Respect to the effect of the nanoparticle concentration, both thermal conductivity and viscosity increased with nanoparticle concentration. The thermal conductivity raised up to 9% respect to the base fluid, and the viscosity increases up to 60%, in both cases for the higher concentration. Finally, the viscosity measurements for different rotation speeds (30 RPM - 80 RPM) exhibited that the addition of nanoparticles modifies the rheological behavior of the base fluid, from a Newtonian to a viscoplastic (Bingham) or shear thinning (power-law) non-Newtonian behavior.

Keywords: NanoPCM, thermal conductivity, viscosity, non-Newtonian fluid

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Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

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Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

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Authors: M. Kharazmi, M. Zakeri, M. Packirisamy, J. Faraji

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Micro/Nanorobotics or manipulation of nanoparticles by Atomic Force Microscopic (AFM) is one of the most important solutions for controlling the movement of atoms, particles and micro/nano metrics components and assembling of them to design micro/nano-meter tools. Accurate modelling of manipulation requires identification of forces and mechanical knowledge in the Nanoscale which are different from macro world. Due to the importance of the adhesion forces and the interaction of surfaces at the nanoscale several friction models were presented. In this research, friction and normal forces that are applied on the AFM by using of the dynamic bending-torsion model of AFM are obtained based on Hurtado-Kim friction model (HK), Johnson-Kendall-Robert contact model (JKR) and Greenwood-Williamson roughness model (GW). Finally, the effect of standard deviation of asperities height on the normal load, friction force and friction coefficient are studied.

Keywords: atomic force microscopy, contact model, friction coefficient, Greenwood-Williamson model

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Authors: Danila Merino, Leandro N. Ludueña, Vera A. Alvarez

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Clays are commonly used to reinforce polymeric materials. In order to modify them, long-chain quaternary-alkylammonium salts have been widely employed. However, the application of these clays in biological fields is limited by the toxicity and poor biocompatibility presented by these modifiers. Meanwhile, soy lecithin, acts as a natural biosurfactant and environment-friendly biomodifier. In this report, we analyse the effect of content of soy lecithin-modified bentonite on the properties of polycaprolactone (PCL) nanocomposites. Commercial grade PCL (CAPA FB 100) was supplied by Perstorp, with Mw = 100000 g/mol. Minarmco S.A. and Melar S.A supplied bentonite and soy lecithin, respectively. Clays with 18, 30 and 45 wt% of organic content were prepared by exchanging 4 g of Na-Bent with 1, 2 and 4 g of soy lecithin aqueous and acid solution (pH=1, with HCl) at 75ºC for 2 h. Then, they were washed and lyophilized for 72 h. Samples were labeled A, B and C. Nanocomposites with 1 and 2 wt.% of each clay were prepared by melt-intercalation followed by compression-moulding. An intensive Brabender type mixer with two counter-rotating roller rotors was used. Mixing temperature was 100 ºC; speed of rotation was 100 rpm. and mixing time was 10 min. Compression moulding was carried out in a hydraulic press under 75 Kg/mm2 for 10 minutes at 100 ºC. The thickness of the samples was about 1 mm. Thermal and mechanical properties were analysed. PCL nanocomposites with 1 and 2% of B presented the best mechanical properties. It was observed that an excessive organic content produced an increment on the rigidity of PCL, but caused a detrimental effect on the tensile strength and elongation at break of the nanocomposites. Thermogravimetrical analyses suggest that all reinforced samples have higher resistance to degradation than neat PCL.

Keywords: chemical modification, clay, nanocomposite, characterization

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Authors: Elvan G. Bulut, Betul Goksun, Tugba G. Gun, Ozge Sakiyan Demirkol, Kamuran Ayhan, Kezban Candogan

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Dysphagia, difficulty in swallowing solid foods and thin liquids, is one of the common health threats among the elderly who require foods with modified texture in their diet. Although there are some commercial food formulations or hydrocolloids to thicken the liquid foods for dysphagic individuals, there is still a need for developing and offering new food products with enriched nutritional, textural and sensory characteristics to safely nourish these patients. 3D food printing is an appealing alternative in creating personalized foods for this purpose with attractive shape, soft and homogenous texture. In order to modify texture and prevent phase separation, hydrocolloids are generally used. In our laboratory, an optimized 3D printed beef-based formulation specifically for people with swallowing difficulties was developed based on the research project supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK Project # 218O017). The optimized formulation obtained from response surface methodology was 60% beef powder, 5.88% gelatin, and 0.74% kappa-carrageenan (all in a dry basis). This product was enriched with powders of freeze-dried beet, celery, and red capia pepper, butter, and whole milk. Proximate composition (moisture, fat, protein, and ash contents), pH value, CIE lightness (L*), redness (a*) and yellowness (b*), and color difference (ΔE*) values were determined. Counts of total mesophilic aerobic bacteria (TMAB), lactic acid bacteria (LAB), mold and yeast, total coliforms were conducted, and detection of coagulase positive S. aureus, E. coli, and Salmonella spp. were performed. The 3D printed products had 60.11% moisture, 16.51% fat, 13.68% protein, and 1.65% ash, and the pH value was 6.19, whereas the ΔE* value was 3.04. Counts of TMAB, LAB, mold and yeast and total coliforms before and after 3D printing were 5.23-5.41 log cfu/g, < 1 log cfu/g, < 1 log cfu/g, 2.39-2.15 log EMS/g, respectively. Coagulase positive S. aureus, E. coli, and Salmonella spp. were not detected in the products. The data obtained from this study based on determining some important product characteristics of functional beef-based formulation provides an encouraging basis for future research on the subject and should be useful in designing mass production of 3D printed products of similar composition.

Keywords: beef, dysphagia, product characteristics, texture-modified foods, 3D food printing

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Authors: Pouya Molana, Zeinab Alimohammadi

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Determining wind wave characteristics is essential for implementing projects related to Coastal and Marine engineering such as designing coastal and marine structures, estimating sediment transport rates and coastal erosion rates in order to predict significant wave height (H_s), this study applies the third generation spectral wave model, Mike 21 SW, along with CEM model. For SW model calibration and verification, two data sets of meteorology and wave spectroscopy are used. The model was exposed to time-varying wind power and the results showed that difference ratio mean, standard deviation of difference ratio and correlation coefficient in SW model for H_s parameter are 1.102, 0.279 and 0.983, respectively. Whereas, the difference ratio mean, standard deviation and correlation coefficient in The Choice Experiment Method (CEM) for the same parameter are 0.869, 1.317 and 0.8359, respectively. Comparing these expected results it is revealed that the Choice Experiment Method CEM has more errors in comparison to MIKE 21 SW third generation spectral wave model and higher correlation coefficient does not necessarily mean higher accuracy.

Keywords: MIKE 21 SW, CEM method, significant wave height, difference ratio

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Authors: Sibel Celik, Hüseyin Ergin

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The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

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Authors: Ashley Wei-Ting Wang, Wen-Yau Hsu

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Objectives: The current study applies and expands the Tripartite Model to elaborate the link between non-suicidal self-injury (NSSI) and suicidal behavior. We propose a structural model of NSSI and suicidal risk, in which negative affect (NA) predicts both anxiety and depression, positive affect (PA) predicts depression only, anxiety is linked to NSSI, and depression is linked to suicidal risk. Method: Four hundreds and eighty seven undergraduates participated. Data were collected by administering self-report questionnaires. We performed hierarchical regression and structural equation modeling to test the proposed structural model. Results: The results largely support the proposed structural model, with one exception: anxiety was strongly associated with NSSI and to a lesser extent with suicidal risk. Conclusions: We conclude that the co-occurrence of NSSI and suicidal risk is due to NA and anxiety, and suicidal risk can be differentiated by depression. Further theoretical and practical implications are discussed.

Keywords: non-suicidal self-injury, suicidal risk, anxiety, depression, the tripartite model, hierarchical relationship

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Authors: Shih-Kuei Lin

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The characterization of the arbitrage-free dynamics of interest rates is developed in this study under the presence of Markov jump risks, when the term structure of the interest rates is modeled through simple forward rates. We consider Markov jump risks by allowing randomness in jump sizes, independence between jump sizes and jump times. The Markov jump diffusion model is used to capture empirical phenomena and to accurately describe interest jump risks in a financial market. We derive the arbitrage-free model of simple forward rates under the spot measure. Moreover, the analytical pricing formulas for a cap and a floor are derived under the forward measure when the jump size follows a lognormal distribution. In our empirical analysis, we find that the LIBOR market model with Markov jump risk better accounts for changes from/to different states and different rates.

Keywords: arbitrage-free, cap and floor, Markov jump diffusion model, simple forward rate model, volatility smile, EM algorithm

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: J. Fernandez, N. Aguilar, R. Fernandez de Canete, J. C. Ramos-Diaz

Abstract:

In this paper, a simulation model of the glucose-insulin system for a patient undergoing diabetes Type 1 is developed by using a causal modeling approach under system dynamics. The OpenModelica simulation environment has been employed to build the so called causal model, while the glucose-insulin model parameters were adjusted to fit recorded mean data of a diabetic patient database. Model results under different conditions of a three-meal glucose and exogenous insulin ingestion patterns have been obtained. This simulation model can be useful to evaluate glucose-insulin performance in several circumstances, including insulin infusion algorithms in open-loop and decision support systems in closed-loop.

Keywords: causal modeling, diabetes, glucose-insulin system, diabetes, causal modeling, OpenModelica software

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Authors: Tareq Oshan

Abstract:

Facility location and size decisions are important to any company because they affect profitability and success. However, warehouses are exposed to various risks of failure that affect their activity. This paper presents a mixed-integer non-linear mathematical model that can be used to determine optimal warehouse locations and sizes, which warehouses to fortify, and which branches should be assigned to specific warehouses when there is a risk of warehouse failure. Every branch is assigned to a fortified primary warehouse or a nonfortified primary warehouse and a fortified backup warehouse. The standard method and an introduced method, based on the average probabilities, for linearizing this mathematical model were used. A Canadian case study was used to demonstrate the developed mathematical model, followed by some sensitivity analysis.

Keywords: supply chain network design, fortified warehouse, mixed-integer mathematical model, warehouse failure risk

Procedia PDF Downloads 243

Authors: Rit M., Girard R., Villot J., Thorel M.

Abstract:

In a scenario of extensive residential housing renovation, stakeholders need models that support decision-making through a deep understanding of the existing building stock and accurate energy demand simulations. To address this need, we have modified an optimization model using open data that enables the study of renovation strategies at both territorial and national scales. This approach provides (1) a definition of a strategy to simplify decision trees from theoretical combinations, (2) input to decision makers on real-world renovation constraints, (3) more reliable identification of energy-saving measures (changes in technology or behaviour), and (4) discrepancies between currently planned and actually achieved strategies. The main contribution of the studies described in this document is the geographic scale: all residential buildings in the areas of interest were modeled and simulated using national data (geometries and attributes). These buildings were then renovated, when necessary, in accordance with the environmental objectives, taking into account the constraints applicable to each territory (number of renovations per year) or at the national level (renovation of thermal deficiencies (Energy Performance Certificates F&G)). This differs from traditional approaches that focus only on a few buildings or archetypes. This model can also be used to analyze the evolution of a building stock as a whole, as it can take into account both the construction of new buildings and their demolition or sale. Using specific case studies of French territories, this paper highlights a significant discrepancy between the strategies currently advocated by decision-makers and those proposed by our optimization model. This discrepancy is particularly evident in critical metrics such as the relationship between the number of renovations per year and achievable climate targets or the financial support currently available to households and the remaining costs. In addition, users are free to seek optimizations for their building stock across a range of different metrics (e.g., financial, energy, environmental, or life cycle analysis). These results are a clear call to re-evaluate existing renovation strategies and take a more nuanced and customized approach. As the climate crisis moves inexorably forward, harnessing the potential of advanced technologies and data-driven methodologies is imperative.

Keywords: residential housing renovation, MILP, energy demand simulations, data-driven methodology

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Authors: Mohammad Hossein Harirchian, Siavash Babaie, Nika keshtkaran, Sama Bitarafan

Abstract:

Background: Fatigue is a common complaint of multiple sclerosis (MS) patients, adversely affecting their quality of life. There is a lot of evidence showing that Carnitine deficiency is linked to fatigue development and severity in some conditions. This study aimed to compare the levels of Free L-Carnitine (FLC) between MS patients and healthy people and evaluate its association with the severity of fatigue. Methods: This case-control study included 30 patients with relapsing-remitting MS (RRMS) in 2 sex-matched equal-number groups according to the presence or absence of fatigue and 30 sex-matched healthy people in the control group. In addition, between two patient groups, we compared Serum level of FLC between the patient and healthy group. Fatigue was scored using two valid questionnaires of fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS). In addition, association between Serum level of FLC and fatigue severity was evaluated in MS patients. Results: There was no significant difference in serum levels of FLC between MS patients and healthy people. The patients with fatigue had a significantly lower FLC (mg/dl) value than patients without fatigue (22.53 ± 15.84 vs. 75.36 ± 51.98, P < 0.001). The mean value of FSS and MFIS in patients with fatigue were 48.80±8.55 and 62.87 ± 13.63, respectively, which was nearly two-fold higher than group without fatigue (P < 0.001). There was a negative correlation between the serum level of FLC and fatigue severity scales (Spearman rank correlation= 0.76, P < 0.001). Conclusion: We showed healthy people and MS patients were not different in levels of FLC. In addition, patients with lower serum levels of FLC might experience more severe fatigue. Therefore, this could clarify that supplementation with L-Carnitine might be considered as a complementary treatment for MS-related fatigue.

Keywords: fatigue, multiple sclerosis, L-carnitine, modified fatigue impact scale

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Authors: K. M. Anusha, R. Krishnaveni

Abstract:

Crossing a decade of the 21st century, the paradigm of human resources can be seen evolving with the strategic gene induced into it. There seems to be a radical shift descending as the corporate sector calls on its HR team to become strategic rather than administrative. This transferal eventually requires the metrics employed by these HR teams not to be just operationally reactive but to be aligned to an evidence-based strategic thinking. Realizing the growing need for a prescriptive metric model for effective HR analytics, this study has designed a conceptual framework for a basic metric model that can assist IT-HRM professionals to transition to a practice of evidence-based decision-making to enhance organizational performance.

Keywords: metric model, evidence based HR, HR analytics, strategic HR practices, IT sector

Procedia PDF Downloads 403