Search results for: cycle fitting

Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Dimitra Das, Anuradha Mitra, Kalyan Kumar Chattopadhyay

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Organic polymers, constructed from light elements like carbon, hydrogen, nitrogen, oxygen, sulphur, and boron atoms, are the emergent class of non-toxic, metal-free, environmental benign advanced materials. Covalent triazine-based polymers with a functional triazine group are significant class of organic materials due to their remarkable stability arising out of strong covalent bonds. They can conventionally form hydrogen bonds, favour π–π contacts, and they were recently revealed to be involved in interesting anion–π interactions. The present work mainly focuses upon the development of a single-crystalline, highly cross-linked triazine-based nitrogen-rich organic polymer with nanodendritic morphology and significant thermal stability. The polymer has been synthesized through hydrothermal treatment of melamine and ethylene glycol resulting in cross-polymerization via condensation-polymerization reaction. The crystal structure of the polymer has been evaluated by employing Rietveld whole profile fitting method. The polymer has been found to be composed of monoclinic melamine having space group P21/a. A detailed insight into the chemical structure of the as synthesized polymer has been elucidated by Fourier Transform Infrared Spectroscopy (FTIR) and Raman spectroscopic analysis. X-Ray Photoelectron Spectroscopic (XPS) analysis has also been carried out for further understanding of the different types of linkages required to create the backbone of the polymer. The unique rod-like morphology of the triazine based polymer has been revealed from the images obtained from Field Emission Scanning Electron Microscopy (FESEM) and Transmission Electron Microscopy (TEM). Interestingly, this polymer has been found to selectively detect mercury (Hg²⁺) ions at an extremely low concentration through fluorescent quenching with detection limit as low as 0.03 ppb. The high toxicity of mercury ions (Hg²⁺) arise from its strong affinity towards the sulphur atoms of biological building blocks. Even a trace quantity of this metal is dangerous for human health. Furthermore, owing to its small ionic radius and high solvation energy, Hg²⁺ ions remain encapsulated by water molecules making its detection a challenging task. There are some existing reports on fluorescent-based heavy metal ion sensors using covalent organic frameworks (COFs) but reports on mercury sensing using triazine based polymers are rather undeveloped. Thus, the importance of ultra-trace detection of Hg²⁺ ions with high level of selectivity and sensitivity has contemporary significance. A plausible sensing phenomenon by the polymer has been proposed to understand the applicability of the material as a potential sensor. The impressive sensitivity of the polymer sample towards Hg²⁺ is the very first report in the field of highly crystalline triazine based polymers (without the introduction of any sulphur groups or functionalization) towards mercury ion detection through photoluminescence quenching technique. This crystalline metal-free organic polymer being cheap, non-toxic and scalable has current relevance and could be a promising candidate for Hg²⁺ ion sensing at commercial level.

Keywords: fluorescence quenching , mercury ion sensing, single-crystalline, triazine-based polymer

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Authors: Fellah Sihem

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The optimal use of soil moisture by culture, is related to the leaf area index, which stood in the cycle and its modulation according to the prevailing stress intensity. For a given stock of water in the soil, cultivar adapted and saving water is one that is no luxury consumption during the preanthesis. It modulates the leaf area index to regulate sweating in the degree of its water supply. In plants water saving, avoidance of dehydration is related to the reduction of water loss by cuticular and stomatal pathways. Muchow and Sinclair reported that the test of relative water content (TRE) is considered the best indicator of leaf water status. The search for indicators of the ability of the plant to make good use of the water, under water stress is a prerequisite for progress in improving performance under water stress. This experiment aims to characterize a set of durum wheat varieties, tested jars and vegetation under different levels of water stress to the surface of the leaf, relative water content, cell integrity, the accumulated biomass and efficiency of water use. The experiment was conducted during the 2005/2006 academic year, at the Agricultural Research Station of the Field Crop Institute of Setif, under semi-controlled conditions. Five genotypes of durum wheat (Triticum durum Desf) were evaluated for their ability to tolerate moderate and severe water stress. The results showed that geno types respond differently to water stress. Dry matter accumulation and growth rate varied among geno types and were significantly reduced. At severe water stress biomass accumulated by Boussalam was the least affected.

Keywords: water stress, triticum durum, biomass, cell membrane integrity, relative water content

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Authors: Pradeep Lamichhane

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Plasma-assisted nitrogen fixation is a process by which atomic nitrogen generated by plasma is converted into ammonia (NH₃) or related nitrogenous compounds. Nitrogen fixation is essential to plant because fixed inorganic nitrogen compounds are required to them for the biosynthesis of all nitrogen-containing organic compounds, such as amino acids and proteins, nucleoside triphosphates and nucleic acid. Most of our atmosphere is composed of nitrogen; however, the plant cannot absorb it directly from the air ambient. As a portion of the nitrogen cycle, nitrogen fixation fundamental for agriculture and the manufacture of fertilizer. In this study, plasma-assisted nitrogen fixation was performed by exposing a non-thermal atmospheric pressure nitrogen plasma generated a sinusoidal power supply (with an applied voltage of 10 kV and frequency of 33 kHz) on a water surface. Besides this, UV excitation of water molecules at the water interface was also done in order to disassociate water. Hydrogen and hydroxyl radical obtained from this UV photolysis electrochemically combine with nitrogen atom obtained from plasma. As a result of this, nitrogen fixation on plasma-activated water (PAW) significantly enhanced. The amount of nitrogen-based products like NOₓ and ammonia (NH₃) synthesized by this combined process of UV and plasma are 1.4 and 2.8 times higher than those obtained by plasma alone. In every 48 hours, 20 ml of plasma-activated water (pH≈3.15) for 10 minutes with moderate concentrations of NOₓ, NH₃ and hydrogen peroxide (H₂O₂) was irrigated on each corn plant (Zea Mays). It was found that the PAW has shown a significant impact on seeds germination rate and improved seedling growth. The result obtained from this experiment suggested that crop yield could increase in a short duration. In the future, this experiment could open boundless opportunities in plasma agriculture to mobilize nitrogen because nitrite, nitrate, and ammonia are more suitable for plant uptake.

Keywords: plasma-assisted nitrogen fixation, nitrogen plasma, UV excitation of water, ammonia synthesis

Procedia PDF Downloads 138

Authors: E. Kempen, M. J. Labuschagne, M. P. Jama

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There is evidence that any learning experience should happen in a safe learning environment as students then will interact, experiment, and construct new knowledge. However, little is known about the specific elements required to create a safe learning environment for the millennial generation, especially in optometry education. This study aimed to identify the specific elements that will contribute to a safe learning environment for the millennial generation of optometry students. Methods: An intrinsic qualitative case study was undertaken with undergraduate students from the Department of Optometry at the University of the Free State, South Africa. An open-ended questionnaire survey was completed after the application of nine different teaching-learning methods based on the experiential learning cycle. A total number of 307 questionnaires were analyzed. Two focus group interviews were also conducted to provide additional data to supplement the data and ensure the triangulation of data. Results: Important elements based on the opinions, feelings, and perceptions of student respondents were analyzed. Students feel safe in an environment with which they are familiar, and when they are familiar with each other, the educators, and the surroundings. Small-group learning also creates a safe and familiar environment. Both these elements create an environment where they feel safe to ask questions. Students value an environment where they are able to learn without influencing their marks or disadvantaging the patients. They enjoy learning from their peers, but also need personal contact with educators. Elements such as consistency and an achievable objective also were also analyzed. Conclusion: The findings suggest that to respond to the real need of this generation of students, insight must be gained in students’ perceptions to identify their needs and the learning environment to optimize learning pedagogies. With the implementation of these personalized elements, optometry students will be able to take responsibility and accountability for their learning.

Keywords: experiences and perceptions, safe learning environment, millennial generation, recommendation for optometry education

Procedia PDF Downloads 137

Authors: Marina Nechayeva, Malgorzata Marciniak, Vladimir Przhebelskiy, A. Dragutan, S. Lamichhane, S. Oikawa

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This presentation is a progress report on a faculty-student research collaboration at CUNY LaGuardia Community College (LaGCC) aimed at designing a small horizontal axis wind turbine optimized for the wind patterns on the roof of our campus. Our project combines statistical and engineering research. Our wind modeling protocol is based upon a recent wind study by a faculty-student research group at MIT, and some of our blade design methods are adopted from a senior engineering project at CUNY City College. Our use of genetic algorithms has been inspired by the work on small wind turbines’ design by David Wood. We combine these diverse approaches in our interdisciplinary project in a way that has not been done before and improve upon certain techniques used by our predecessors. We employ several estimation methods to determine the best fitting parametric probability distribution model for the local wind speed data obtained through correlating short-term on-site measurements with a long-term time series at the nearby airport. The model serves as a foundation for engineering research that focuses on adapting and implementing genetic algorithms (GAs) to engineering optimization of the wind turbine design using Blade Element Momentum Theory. GAs are used to create new airfoils with desirable aerodynamic specifications. Small scale models of best performing designs are 3D printed and tested in the wind tunnel to verify the accuracy of relevant calculations. Genetic algorithms are applied to selected airfoils to determine the blade design (radial cord and pitch distribution) that would optimize the coefficient of power profile of the turbine. Our approach improves upon the traditional blade design methods in that it lets us dispense with assumptions necessary to simplify the system of Blade Element Momentum Theory equations, thus resulting in more accurate aerodynamic performance calculations. Furthermore, it enables us to design blades optimized for a whole range of wind speeds rather than a single value. Lastly, we improve upon known GA-based methods in that our algorithms are constructed to work with XFoil generated airfoils data which enables us to optimize blades using our own high glide ratio airfoil designs, without having to rely upon available empirical data from existing airfoils, such as NACA series. Beyond its immediate goal, this ongoing project serves as a training and selection platform for CUNY Research Scholars Program (CRSP) through its annual Aerodynamics and Wind Energy Research Seminar (AWERS), an undergraduate summer research boot camp, designed to introduce prospective researchers to the relevant theoretical background and methodology, get them up to speed with the current state of our research, and test their abilities and commitment to the program. Furthermore, several aspects of the research (e.g., writing code for 3D printing of airfoils) are adapted in the form of classroom research activities to enhance Calculus sequence instruction at LaGCC.

Keywords: engineering design optimization, genetic algorithms, horizontal axis wind turbine, wind modeling

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Authors: André Python

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To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Sunil Kumar, Vinay Kumar, Mamta Bulla, Rita Dahiya

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Supercapacitors have emerged as a leading energy storage technology, gaining popularity in applications like digital telecommunications, memory backup, and hybrid electric vehicles. Their appeal lies in a long cycle life, high power density, and rapid recharge capabilities. These exceptional traits attract researchers aiming to develop advanced, cost-effective, and high-energy-density electrode materials for next-generation energy storage solutions. Two-dimensional (2D) nanostructures are highly attractive for fabricating nanodevices due to their high surface-to-volume ratio and good compatibility with device design. In the current study, a composite was synthesized by combining MoS2 with reduced graphene oxide (rGO) under optimal conditions and characterized using various techniques, including XRD, FTIR, SEM and XPS. The electrochemical properties of the composite material were assessed through cyclic voltammetry, galvanostatic charging-discharging and electrochemical impedance spectroscopy. The supercapacitor device demonstrated a specific capacitance of 153 F g-1 at a current density of 1 Ag-1, achieving an excellent energy density of 30.5 Wh kg-1 and a power density of 600 W kg-1. Additionally, it maintained excellent cyclic stability over 5000 cycles, establishing it as a promising candidate for efficient and durable energy storage solutions. These findings highlight the dynamic relationship between electrode materials and offer valuable insights for the development and enhancement of high-performance symmetric devices.

Keywords: 2D material, energy density, galvanostatic charge-discharge, hydrothermal reactor, specific capacitance

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Authors: Emanuele Bonamente, Andrea Aquino

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This study presents an innovative design for geothermal heat pumps with the goal of maximizing the system efficiency (COP - Coefficient of Performance), reducing the soil use (e.g. length/depth of geothermal boreholes) and initial investment costs. Based on experimental data obtained from a two-year monitoring of a working prototype implemented for a commercial building in the city of Perugia, Italy, an upgrade of the system is proposed and the performance is evaluated via CFD simulations. The prototype was designed to include a thermal heat storage (i.e. water), positioned between the boreholes and the heat pump, acting as a flywheel. Results from the monitoring campaign show that the system is still capable of providing the required heating and cooling energy with a reduced geothermal installation (approx. 30% of the standard length). In this paper, an optimization of the system is proposed, re-designing the heat storage to include phase change materials (PCMs). Two stacks of PCMs, characterized by melting temperatures equal to those needed to maximize the system COP for heating and cooling, are disposed within the storage. During the working cycle, the latent heat of the PCMs is used to heat (cool) the water used by the heat pump while the boreholes independently cool (heat) the storage. The new storage is approximately 10 times smaller and can be easily placed close to the heat pump in the technical room. First, a validation of the CFD simulation of the storage is performed against experimental data. The simulation is then used to test possible alternatives of the original design and it is finally exploited to evaluate the PCM-storage performance for two different configurations (i.e. single- and double-loop systems).

Keywords: geothermal heat pump, phase change materials (PCM), energy storage, renewable energies

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Authors: Vânia Graça, Paula Quadros-Flores, Altina Ramos

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The use of Digital Technologies in teaching and learning processes is currently a reality, namely in initial teacher training. This study aims at knowing the digital reality of students in initial teacher training in order to improve training in the educational use of ICT and to promote digital technology integration strategies in an educational context. It is part of the IFITIC Project "Innovate with ICT in Initial Teacher Training to Promote Methodological Renewal in Pre-school Education and in the 1st and 2nd Basic Education Cycle" which involves the School of Education, Polytechnic of Porto and Institute of Education, University of Minho. The Project aims at rethinking educational practice with ICT in the initial training of future teachers in order to promote methodological innovation in Pre-school Education and in the 1st and 2nd Cycles of Basic Education. A qualitative methodology was used, in which a questionnaire survey was applied to teachers in initial training. For data analysis, the techniques of content analysis with the support of NVivo software were used. The results point to the following aspects: a) future teachers recognize that they have more technical knowledge about ICT than pedagogical knowledge. This result makes sense if we consider the objective of Basic Education, so that the gaps can be filled in the Master's Course by students who wish to follow the teaching; b) the respondents are aware that the integration of digital resources contributes positively to students' learning and to the life of children and young people, which also promotes preparation in life; c) to be a teacher in the digital age there is a need for the development of digital literacy, lifelong learning and the adoption of new ways of teaching how to learn. Thus, this study aims to contribute to a reflection on the teaching profession in the digital age.

Keywords: digital technologies, initial teacher training, pedagogical use of ICT, skills

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia

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Due to developing industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is environmentally urgent. Selective catalytic reduction of NOx is one of the most common techniques for NOx removal in which zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation of the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, benefiting from molecular simulations, the adsorption phenomena in the nanocatalysts of SCR of NOx process was investigated in order to get a good insight of the catalysts’ behavior. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC) using Materials Studio Package. Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: S. M. M. Syairah, M. H. Rajikin, A. R. Sharaniza

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Several embryonic cellular mechanism including cell cycle, growth and apoptosis are regulated by phosphatidylinositol-3-kinase (PI3K)/Akt signaling pathway. The goal of present study is to determine the effects of annatto (Bixa orellana)-derived δ-tocotrienol (δ-TCT) on the regulations of PI3K/Akt genes in murine morula. Twenty four 6-8 week old (23-25g) female balb/c mice were randomly divided into four groups (G1-G4; n=6). Those groups were subjected to the following treatments for 7 consecutive days: G1 (control) received tocopherol stripped corn oil, G2 was given 60 mg/kg/day of δ-TCT mixture (contains 90% delta & 10% gamma isomers), G3 was given 60 mg/kg/day of pure δ-TCT (>98% purity) and G4 received 60 mg/kg/day α-TOC. On Day 8, females were superovulated with 5 IU Pregnant Mare’s Serum Gonadotropin (PMSG) for 48 hours followed with 5 IU human Chorionic Gonadotropin (hCG) before mated with males at the ratio of 1:1. Females were sacrificed by cervical dislocation for embryo collection 48 hours post-coitum. About fifty morula from each group were used in the gene expression analyses using Affymetrix QuantiGene Plex 2.0 Assay. Present data showed a significant increase (p<0.05) in the average number (mean + SEM) of morula produced in G2 (26.0 + 0.45), G3 (23.0 + 0.63) and G4 (25.0 + 0.73) compared to control group (G1 – 16.0 + 0.63). This is parallel with the high expression of PDK1 gene with increase of 2.75-fold (G2), 3.07-fold (G3) and 3.59-fold (G4) compared to G1 (1.78-fold). From the present data, it can be concluded that supplementation with δ-TCT(s) and α-TOC induced high expression of PDK1 in G2-G4 which enhanced the PI3K/Akt signaling activity, resulting in the increased number of morula.

Keywords: delta-tocotrienol, embryonic development, nicotine, vitamin E

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Michaela Kaineder, Beate Bartlmae, Stefan Gaebler, Miriam Gutleder, Marlene Wuerfl

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Digital tools and e-participation processes have seen a steady increase in popularity in recent years. While online trends come with the premise of new opportunities and easier participatory possibilities, there are still manifold challenges that smart city initiators and developers need to face. In this paper, innovative quality criteria of citizen participation processes was suggested by defining meaningful and measurable evaluation categories. Considering various developments, including the global megatrend of connectivity, a need for a fundamental examination of the basic structure of citizen participation processes was identified. To this end, the application of methods and tools through different points in the policy cycle is required. In order to provide an overview of the current challenges and problems in the field of participation, this paper analyzes those issues by carrying out a literature review that also focuses on disparities in the civic sector that might hinder residents in their desire for engagement. Additionally, a case study was chosen to demonstrate the potential that e-participation tools offer to planning experts and public authorities when integrating citizen’s creativity and experience at a large scale. This online co-creation process finally leads to offline events – such as local co-design workshops - with professional planners. The findings of this paper subsequently suggest a combination of e-participation and analogue forms to merge the benefits of both worlds, resulting in a broader audience and higher quality for participation processes.

Keywords: citizen participation, disparities, e-participation, integrated urban development, sustainable development goals, sustainable urban development

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Authors: Sanjai Sureshkumar, Sathish G. Kumar, P. V. V. Sathyanarayana

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For e-gear drivetrain, the transmission error and the resulting variation in mesh stiffness is one of the main source of excitation in High performance Electric Vehicle. These vibrations are transferred through the shaft to the bearings and then to the e-Gear drive housing eventually radiating noise. A parametrical model developed in 1-D system simulation by optimizing the micro and macro geometry along with bearing properties and oil filtration to achieve least transmission error and high contact ratio. Histogram analysis is performed to condense the actual road load data into condensed duty cycle to find the bearing forces. The structural vibration generated by these forces will be simulated in a nonlinear solver obtaining the normal surface velocity of the housing and the results will be carried forward to Acoustic software wherein a virtual environment of the surrounding (actual testing scenario) with accurate microphone position will be maintained to predict the sound pressure level of radiated noise and directivity plot of the e-Gear Drive. Order analysis will be carried out to find the root cause of the vibration and whine noise. Broadband spectrum will be checked to find the rattle noise source. Further, with the available results, the design will be optimized, and the next loop of simulation will be performed to build a best e-Gear Drive on NVH aspect. Structural analysis will be also carried out to check the robustness of the e-Gear Drive.

Keywords: 1-D system simulation, contact ratio, e-Gear, mesh stiffness, micro and macro geometry, transmission error, radiated noise, NVH

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Authors: Maria Karnachoriti, Ellas Spyratou, Dimitrios Lykidis, Maria Lambropoulou, Yiannis S. Raptis, Ioannis Seimenis, Efstathios P. Efstathopoulos, Athanassios G. Kontos

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Colorectal cancer is the third most common cancer diagnosed in Europe, according to the latest incidence data provided by the World Health Organization (WHO), and early diagnosis has proved to be the key in reducing cancer-related mortality. In cases where surgical interventions are required for cancer treatment, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. The current study focuses on the ex vivo handling of surgically excised colorectal specimens and the acquisition of their spectral fingerprints using Raman spectroscopy. Acquired data were analyzed in an effort to discriminate, in microscopic scale, between healthy and malignant margins. Raman spectroscopy is a spectroscopic technique with high detection sensitivity and spatial resolution of few micrometers. The spectral fingerprint which is produced during laser-tissue interaction is unique and characterizes the biostructure and its inflammatory or cancer state. Numerous published studies have demonstrated the potential of the technique as a tool for the discrimination between healthy and malignant tissues/cells either ex vivo or in vivo. However, the handling of the excised human specimens and the Raman measurement conditions remain challenging, unavoidably affecting measurement reliability and repeatability, as well as the technique’s overall accuracy and sensitivity. Therefore, tissue handling has to be optimized and standardized to ensure preservation of cell integrity and hydration level. Various strategies have been implemented in the past, including the use of balanced salt solutions, small humidifiers or pump-reservoir-pipette systems. In the current study, human colorectal specimens of 10X5 mm were collected from 5 patients up to now who underwent open surgery for colorectal cancer. A novel, non-toxic zinc-based fixative (Z7) was used for tissue preservation. Z7 demonstrates excellent protein preservation and protection against tissue autolysis. Micro-Raman spectra were recorded with a Renishaw Invia spectrometer from successive random 2 micrometers spots upon excitation at 785 nm to decrease fluorescent background and secure avoidance of tissue photodegradation. A temperature-controlled approach was adopted to stabilize the tissue at 2 °C, thus minimizing dehydration effects and consequent focus drift during measurement. A broad spectral range, 500-3200 cm-1,was covered with five consecutive full scans that lasted for 20 minutes in total. The average spectra were used for least square fitting analysis of the Raman modes.Subtle Raman differences were observed between normal and cancerous colorectal tissues mainly in the intensities of the 1556 cm-1 and 1628 cm-1 Raman modes which correspond to v(C=C) vibrations in porphyrins, as well as in the range of 2800-3000 cm-1 due to CH2 stretching of lipids and CH3 stretching of proteins. Raman spectra evaluation was supported by histological findings from twin specimens. This study demonstrates that Raman spectroscopy may constitute a promising tool for real-time verification of clear margins in colorectal cancer open surgery.

Keywords: colorectal cancer, Raman spectroscopy, malignant margins, spectral fingerprints

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Authors: Justine Cyril E. Nunag, Nestor B. Sabado Jr., Jienne Chester M. Tolosa

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Concrete has high compressive strength but a low-tension strength. The small tensile strength of concrete is regarded as its primary weakness, which is why it is typically reinforced with steel, a material that is resistant to tension. Even with steel, however, cracking can occur. In strengthening concrete, only a few researchers have modified the water to be used in a concrete mix. This study aims to compare the split tensile strength of normal structural concrete to concrete prepared with magnetic water and a quick setting admixture. In this context, magnetic water is defined as tap water that has undergone a magnetic process to become magnetized water. To test the hypothesis that magnetized concrete leads to higher split tensile strength, twenty concrete specimens were made. There were five groups, each with five samples, that were differentiated by the number of cycles (0, 50, 100, and 150). The data from the Universal Testing Machine's split tensile strength were then analyzed using various statistical models and tests to determine the significant effect of magnetized water. The result showed a moderate (+0.579) but still significant degree of correlation. The researchers also discovered that using magnetic water for 50 cycles did not result in a significant increase in the concrete's split tensile strength, which influenced the analysis of variance. These results suggest that a concrete mix containing magnetic water and a quick-setting admixture alters the typical split tensile strength of normal concrete. Magnetic water has a significant impact on concrete tensile strength. The hardness property of magnetic water influenced the split tensile strength of concrete. In addition, a higher number of cycles results in a strong water magnetism. The laboratory test results show that a higher cycle translates to a higher tensile strength.

Keywords: hardness property, magnetic water, quick-setting admixture, split tensile strength, universal testing machine

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Authors: Kamal Ameis

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This study aims to further improve our understanding of the underlying mechanism of local injury that occurs after manual acupuncture needle manipulation, and that initiates the muscle regeneration process, which is essential for muscle maintenance and adaptation. Skeletal muscle is maintained by resident stem cells called muscle satellite cells. These cells are normally in quiescent state, but following muscle injury, they re-enter the cell cycle and execute a myogenic program resulting in muscle fiber regeneration. Our previous work in young rats demonstrated that acupuncture treatment induced injury that activated resident satellite (stem) cells, which leads to muscle regeneration. Skeletal muscle regeneration is an adaptive response to injury that requires a tightly orchestrated event between signaling pathways activated by growth factor and intrinsic regulatory program controlled by myogenic transcription factor. We identified several gene expressions uniquely important for muscle regeneration in response to acupuncture treatment at different time course using different biological techniques, including Immunocytochemistry, western blotting, and Real Time PCR. This study uses a novel but non-invasive model of injury induced by manual acupuncture to further our current understanding of regenerative mechanism of muscle stem cells. From a clinical perspective, this model of injury induced by manual acupuncture may be easily translatable into a clinical tool that can be used as an alternative to physical exercise for patients challenged by bed rest or forced inactivity. Finally, the knowledge gained from this research could be useful for studies of the local effects of various modalities of induced injury, such as the traditional method of healing by cupping (hijamah), which may enhanced muscle stem cells and muscle fiber regeneration.

Keywords: acupuncture, injury, regeneration, muscle stem cells

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Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Marcello De Falco, Gianluca Natrella, Mauro Capocelli

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CO₂ capture and utilization (CCU) is a promising approach to reduce GHG(greenhouse gas) emissions. Many technologies in this field are recently attracting attention. However, since CO₂ is a very stable compound, its utilization as a reagent is energetic intensive. As a consequence, it is unclear whether CCU processes allow for a net reduction of environmental impacts from a life cycle perspective and whether these solutions are sustainable. Among the tools to apply for the quantification of the real environmental benefits of CCU technologies, exergy analysis is the most rigorous from a scientific point of view. The exergy of a system is the maximum obtainable work during a process that brings the system into equilibrium with its reference environment through a series of reversible processes in which the system can only interact with such an environment. In other words, exergy is an “opportunity for doing work” and, in real processes, it is destroyed by entropy generation. The exergy-based analysis is useful to evaluate the thermodynamic inefficiencies of processes, to understand and locate the main consumption of fuels or primary energy, to provide an instrument for comparison among different process configurations and to detect solutions to reduce the energy penalties of a process. In this work, the exergy analysis of a process for the production of Dimethyl Ether (DME) from green hydrogen generated through an electrolysis unit and pure CO₂ captured from flue gas is performed. The model simulates the behavior of all units composing the plant (electrolyzer, carbon capture section, DME synthesis reactor, purification step), with the scope to quantify the performance indices based on the II Law of Thermodynamics and to identify the entropy generation points. Then, a plant optimization strategy is proposed to maximize the exergy efficiency.

Keywords: green DME production, exergy analysis, energy penalties, exergy efficiency

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Authors: JiYoung Park, SueGoo Rhee, HyunAe Woo

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In liver regeneration, quiescent hepatocytes need to be primed to fully respond to growth factors such as hepatocyte growth factor. To understand the priming process, it is necessary to analyze patterns of gene expression that occur during liver regeneration after partial hepatectomy (PHx). Recently, tyrosine phosphorylation of signal transducer and activator of transcription 3 (pYSTAT3) has been shown to play an important role in initiating liver regeneration. In order to evaluate the role of pYSTAT3 on liver regeneration after PHx, we used an intrabody which can selectively inhibit pYSTAT3. In our previous studies, an intrabody had been shown that it bound specifically to the pYSTAT3. Adenovirus-mediated expression of the intrabody in HepG2 cells, as well as mouse liver, blocked both accumulation of pYSTAT3 in the nucleus and downstream target of pYSTAT3. In this study, PHx was performed on intrabody-expressing mice and the expression levels of liver regeneration-related genes were analyzed. We also measured liver/body weight ratios and the related cellular signaling pathways were analyzed. Acute phase response genes were reduced in an intrabody-expressing mice during liver regeneration than in control virus-injected mice. However, the time course of liver mass restoration in intrabody-expressing mice was similar to that observed in control virus-injected mice. We also observed that the expression levels of anti-apoptotic genes, such as Bcl2 and Bcl-xL were decreased in intrabody-expressing mice whereas the expression of cell cycle-related genes such as cyclin D1, and c-myc was increased. Liver regeneration after PHx was partially impaired by the selective inhibition of pYSTAT3 with a phosphorylation site-specific intrabody and these results indicated that pYSTAT3 might have limited role in liver mass recovery.

Keywords: STAT3, pYSTAT3, liver regeneration, intrabody

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Authors: Karla Sanchez-Ortiz, Yunuen Tapia-Torres, John Larsen, Felipe Garcia-Oliva

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Due to food demand production, the use of synthetic nitrogenous fertilizer has increased in agricultural soils to replace the N losses. Nevertheless, the intensive use of synthetic nitrogenous fertilizer in conventional agriculture negatively affects the soil and therefore the environment, so alternatives such as organic agriculture have been proposed for being more environmentally friendly. However, further research in soil is needed to see how agricultural management affects the dynamics of C and N. The objective of this research was to evaluate the C and N dynamics in the soil with three different agricultural management: an agricultural plot with intensive inorganic fertilization, a plot with semi-organic management and an agricultural plot with recent abandonment (2 years). For each plot, the soil C and N dynamics and the enzymatic activity of NAG and β-Glucosidase were characterized. Total C and N concentration of the plant biomass of each site was measured as well. Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) was higher in abandoned plot, as well as this plot had higher total carbon (TC) and total nitrogen (TN), besides microbial N and microbial C. While the enzymatic activity of NAG and β-Glucosidase was greater in the agricultural plot with inorganic fertilization, as well as nitrate (NO₃) was higher in fertilized plot, in comparison with the other two plots. The aboveground biomass (AB) of maize in the plot with inorganic fertilization presented higher TC and TN concentrations than the maize AB growing in the semiorganic plot, but the C:N ratio was highest in the grass AB in the abandoned plot. The C:N ration in the maize grain was greater in the semi-organic agricultural plot. These results show that the plot under intensive agricultural management favors the loss of soil organic matter and N, degrading the dynamics of soil organic compounds, promoting its fertility depletion.

Keywords: mineralization, nitrogen cycle, soil degradation, soil nutrients

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Authors: Kunal Mankodi, Sudhir Pandey

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This study aims to assess the factors that play a role in setting up and running a social enterprise driven towards sustainability at the intersection of energy, environment, and poverty alleviation. According to the theory of sustainability-oriented innovation (SOI), conventional organisations adapt their processes to focus on sustainability-oriented innovations. On the other hand, social enterprises that are purpose-driven are also influenced by the context of innovation, which need due attention. This paper presents an account of innovation at Oorja - an Indian social enterprise operating with a farming-as-a-service business model. It aims to illustrate the contexts in which the innovative solutions were developed to work at an intersection between agriculture and clean energy, thereby allowing small farmers access to efficient solutions in the agriculture cycle. Primary data was collected through in-depth interviews, and secondary data was collected from company sources. The study finds that in the case of a social enterprise, the definition of innovation assumes a wider scope by going beyond the introduction of a new product/service. The context of innovation for social enterprise is affected by organisational factors such as organisation’s philosophical mindset, behaviour towards innovation, organisation’s capabilities, regulatory environment, and customer receptiveness. Additionally, the study also finds that the context of innovation for a social enterprise is affected by its organizational structure. A majority of these organizational factors are, in turn, affected by individual (Founder’s) factors such as the founder’s formative years, education, direct exposure to relevant issues, complementary skills of co-founders, and a common calling.

Keywords: context of innovation, social enterprise, sustainability oriented innovations, emerging markets, agriculture

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Authors: L. K. Nivedha, V. Maruthapandian, R. Kothandaraman

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Rechargeable zinc-air batteries (ZAB) are gaining significant research attention owing to their high energy density and copious zinc resources worldwide. However, the unsolved obstacles such as dendrites, passivation, depth of discharge and the lack of an efficient cathode catalyst restrict their practical application1. By and large, non-noble transition metal-based catalysts are well-reputed materials for catalysing oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with greater stability in alkaline medium2. Herein, we report the synthesis and application of Mn₃O4-NiFeLDH/Carbon composite as a cathode catalyst for rechargeable ZAB. The synergetic effects of the mixed transition metals (Mn/Ni/Fe) have aided in catalysing ORR and OER in alkaline electrolyte with a shallow potential gap of 0.7 V. The composite, by its distinctive physicochemical characteristics, shows an excellent OER activity with a current density of 1.5 mA cm⁻² at a potential of 1.6 V and a superior ORR activity with an onset potential of 0.8 V when compared with their counterparts. Nevertheless, the catalyst prefers a two-electron pathway for the electrochemical reduction of oxygen which results in a limiting current density of 2.5 mA cm⁻². The bifunctional activity of the Mn₃O₄-NiFeLDH/Carbon composite was utilized in developing rechargeable ZAB. The fully fabricated ZAB delivers an open circuit voltage of 1.4 V, a peak power density of 70 mW cm⁻², and a specific capacity of 800 mAh g⁻¹ at a current density of 20 mA cm⁻² with an average discharge voltage of 1 V and the cell is operable upto 50 mA cm-2. Rechargeable ZAB demonstrated over 110 h at 10 mA cm⁻². Further, the cause for the diminished charge-discharge performance experienced beyond the 100th cycle was investigated, and carbon corrosion was testified using Infrared spectroscopy.

Keywords: rechargeable zinc-air battery, oxygen evolution reaction, bifunctional catalyst, alkaline medium

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Authors: Ammar Ayad Issa Al-Rifaie, Zuhreya Muazu, Maysam Ali Abdulwahid, Dermot Gleeson

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The aim of this audit was to examine the efficiency of alcohol history documentation and screening for hazardous drinkers at the Medical Admission Unit (MAU) of Northern General Hospital (NGH), Sheffield, to identify any potential for enhancing clinical practice. Data were collected from medical clerking sheets, ICE system and directly from 82 patients by three junior medical doctors using both CAGE questionnaire and AUDIT-C tool for newly admitted patients to MAU in NGH, in the period between January and March 2015. Alcohol consumption was documented in around two-third of the patient sample and this was documented fairly accurately by health care professionals. Some used subjective words such as 'social drinking' in the alcohol units’ section of the history. CAGE questionnaire was applied to only four patients and none of the patients had documented advice, education or referral to an alcohol liaison team. AUDIT-C tool had identified 30.4%, while CAGE 10.9%, of patients admitted to the NGH MAU as hazardous drinkers. The amount of alcohol the patient consumes positively correlated with the score of AUDIT-C (Pearson correlation 0.83). Re-audit is planned to be carried out after integrating AUDIT-C tool as labels in the notes and presenting a brief teaching session to junior doctors. Alcohol misuse screening is not adequately undertaken and no appropriate action is being offered to hazardous drinkers. CAGE questionnaire is poorly applied to patients and when satisfactory and adequately used has low sensitivity to detect hazardous drinkers in comparison with AUDIT-C tool. Re-audit of alcohol screening practice after introducing AUDIT-C tool in clerking sheets (as labels) is required to compare the findings and conclude the audit cycle.

Keywords: alcohol screening, AUDIT-C, CAGE, hazardous drinking

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Authors: Nora A. Guerrero, Adan Leon, María I. Sandoval, Romel Perez, Samuel Munoz

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The addition of solvents in cyclic steam stimulation is a technique that has shown an impact on the improved recovery of heavy oils. In this technique, it is possible to reduce the steam/oil ratio in the last stages of the process, at which time this ratio increases significantly. The mobility of improved crude oil increases due to the structural changes of its components, which at the same time reflected in the decrease in density and viscosity. In the present work, the effect of the variables such as temperature, time, and weight percentage of naphtha was evaluated, using a factorial design of experiments 23. From the results of analysis of variance (ANOVA) and Pareto diagram, it was possible to identify the effect on viscosity reduction. The experimental representation of the crude-vapor-naphtha interaction was carried out in a batch reactor on a Colombian heavy oil of 12.8° API and 3500 cP. The conditions of temperature, reaction time, and percentage of naphtha were 270-300 °C, 48-66 hours, and 3-9% by weight, respectively. The results showed a decrease in density with values in the range of 0.9542 to 0.9414 g/cm³, while the viscosity decrease was in the order of 55 to 70%. On the other hand, simulated distillation results, according to ASTM 7169, revealed significant conversions of the 315°C+ fraction. From the spectroscopic techniques of nuclear magnetic resonance NMR, infrared FTIR and UV-VIS visible ultraviolet, it was determined that the increase in the performance of the light fractions in the improved crude is due to the breakdown of alkyl chains. The methodology for cyclic steam injection with naphtha and laboratory-scale characterization can be considered as a practical tool in improved recovery processes.

Keywords: viscosity reduction, cyclic steam stimulation, factorial design, naphtha

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Authors: Saeed Yazdani, Sima Mohamadi Amidabadi, Amir Mohamadi Nejad, Farahnaz Nekoofar

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As a result of uncertainty and doubts about the quantity of agricultural products, greater significance has been attached to risk management in the agricultural sector. Normally, farmers seek to minimize risks, and crop diversity has always been a means to reduce risk. The study at hand seeks to explore the long-term impact of crop diversity on income risk reduction. The timeframe of the study is 1998 to 2018. Initially, the Herfindahl index was used to estimate crop diversity in different periods, and next, the Hodrick-Prescott filter was applied to estimate income risk both in nominal and real terms. Finally, using the Vector Error Correction Model (VECM), the long-term impact of crop diversity on two modes of risk for the farmer's income has been estimated. Given the long-term pattern’s results, it is evident that in the long-run, crop diversity can reduce income fluctuations in two nominal and real terms. Moreover, results showed that in case the fluctuation shock affects the agricultural income in the short run, to balance out the shock in nominal and real terms, 4 and 3 cycles are needed respectively. In other words, in each cycle, 25% and 33% of the shock impact can be removed, respectively. Thus, as the results of the error correction coefficient showed, policies need to be put in place to prevent income shocks. In case of a shock, they need to be balanced out in a four-year period, taking inflation into account, and in a three-year period irrespective of the inflation and reparative policies such as insurance services should be developed.

Keywords: risk, long-term model, Herfindahl index, time series model, vector error correction model

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Authors: Pravin Mishra, Ajeet K. Jha, Pankaj K. Jha

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This technical note is aimed at providing a brief information on goat breeds, its breeding seasonality and different methods of oestrous synchronization for Nepalese goat farmers. It was observed that, these goats are seasonal breeder and showed oestrous during mainly two season; December- February and March-May. This leads to an irregular supply of goat to market and a wide variations in market price. Oestrus synchronization is only an alternative reproductive tool to overcome this scarcity by enhancing production and productivity. This technique enables goat producers breed their animals within a short pre-determined period and permits breeding round the year. The principle of oestrus synchronisation is based on controlling of the luteal phase of the oestrous cycle. There are two basic mechanisms; one by shortening the luteal life (premature luteolysis) using prostaglandins or its analogues and the other by prolonging the luteal life (simulating the activity of natural progesterone produced by the corpus luteum) using exogenous progesterone source. The former is easy to apply and only effective during breeding season, whereas the latter is advantageous when the reproductive status of the goat flock is unknown. The common hormonal products easily available in Nepal includes; prostaglandins or its analogues (Oviprost® Dinoprost® Lutalyse® and Estrumate®), exogenous progesterone (Fluorogestone acetate® and Controlled Internal Drug Release®, CIDR) devices). However, before practicing the oestrous synchronization protocol, it needs to be validated for oestrous response rate, time to onset of oestrous, duration of oestrous and pregnancy rates at farmer’s field. In conclusion, application of oestrus synchronisation practice enhanced goat production and surplus the goat meat demand in Nepal.

Keywords: goat, Nepal, oestrous, synchronization

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Authors: Rubens Duarte Coelho, Timóteo Herculino da Silva Barros, Jefferson de Olveira Costa

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Brazil has an electrical matrix of predominantly renewable origin, with emphasis on water sources, which account for 65.2%, biomass energy for 8.2%, wind for 6.8% and solar for 0.13% of the domestic supply. Among these sources, sugarcane cultivation stands out, aiming both at the production of bioethanol and biomass to supply “clean energy”. However, like all other crops, sugar cane demands a large volume of a natural resource that is increasingly “scarce” in quantity and quality: water. Adequate and strategic water management throughout the entire sugarcane cycle is of fundamental importance, and water productivity can be used to adjust irrigation planning and decision-making, increasing the productivity of stalks, bioethanol, biomass, and sugar. In this way, water productivity is a good indicator for analysis and decision-making considering the sustainability of cultivation, as it allows evaluation of the variation in the ratio between production and the amount of water used, suggesting values that maximize the use of this natural resource. In this context, studies that relate water demand, in this case, expressed by water productivity, with the energy production of this crop, in this case, expressed by the production of bioethanol, biomass and sugar, are fundamental to obtaining an efficient production of renewable energy, which aims at the rational use of natural resources, especially water. The objective of the present work was to evaluate the response of sugarcane varieties subjected to different water availability to obtain better sustainability in bioenergy production, presenting water productivity indices for Bioethanol, Sugar and Biomass. The variety that responded best was RB966928, with a bioethanol yield of 68.7 L Mg-1. Future research should focus on the water response under each of the sugarcane fractions in terms of their elemental composition so that the influence of water on the energy supply of this crop can be better understood.

Keywords: energy matrix, water use, water use efficiency, sustainability

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Authors: Mahmood Alsaadi, Alexei Lisitsa

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Nowadays, medical devices rely completely on software whether as whole software or as embedded software, therefore, the organization that develops medical device software can benefit from adopting agile practices. Using agile practices in healthcare software development industries would bring benefits such as producing a product of a high-quality with low cost and in short period. However, medical device software development companies faced challenges in adopting agile practices. These due to the gaps that exist between agile practices and the requirements of healthcare regulations such as documentation, traceability, and formality. This research paper will conduct a study to investigate the adoption rate of agile practice in medical device software development, and they will extract and outline the requirements of healthcare regulations such as Food and Drug Administration (FDA), Health Insurance Portability and Accountability Act (HIPAA), and Medical Device Directive (MDD) that affect directly or indirectly on software development life cycle. Moreover, this research paper will evaluate the suitability of using agile practices in healthcare industries by analyzing the most popular agile practices such as eXtream Programming (XP), Scrum, and Feature-Driven Development (FDD) from healthcare industry point of view and in comparison with the requirements of healthcare regulations. Finally, the authors propose an agile mixture model that consists of different practices from different agile methods. As result, the adoption rate of agile practices in healthcare industries still low and agile practices should enhance with regard to requirements of the healthcare regulations in order to be used in healthcare software development organizations. Therefore, the proposed agile mixture model may assist in minimizing the gaps existing between healthcare regulations and agile practices and increase the adoption rate in the healthcare industry. As this research paper part of the ongoing project, an evaluation of agile mixture model will be conducted in the near future.

Keywords: adoption of agile, agile gaps, agile mixture model, agile practices, healthcare regulations

Procedia PDF Downloads 236