Search results for: half step

Authors: Beverly Redman

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With the Theatre Season of 2020-2021 cancelled due to COVID-19 at Purdue University, Fort Wayne, IN, USA, faculty directors found themselves scrambling to create theatre production opportunities for their students in the Department of Theatre. Redman, Chair of the Department, found her community to be suffering from anxieties brought on by a confluence of issues: the global-scale Covid-19 Pandemic, the United States’ Black Lives Matter protests erupting in cities all across the country and the coming Presidential election, arguably the most important and most contentious in the country’s history. Redman wanted to give her students the opportunity to speak not only on these issues but also to be able to record who they were at this time in their personal lives, as well as in this broad socio-political context. She also wanted to invite them into an experience of feeling empathy, too, at a time when empathy in this world seems to be sorely lacking. Returning to a mode of Devising Theatre she had used with community groups in the past, in which storytelling and re-enactment of participants’ life events combined with oral history documentation practices, Redman planned The Shared Breath Project. The process involved three months of workshops, in which participants alternated between theatre exercises and oral history collection and documentation activities as a way of generating original material for a theatre production. The goal of the first half of the project was for each participant to produce a solo piece in the form of a monologue after many generations of potential material born out of gammes, improvisations, interviews and the like. Along the way, many film and audio clips recorded the process of each person’s written documentation—documentation prepared by the subject him or herself but also by others in the group assigned to listen, watch and record. Then, in the second half of the project—and only once each participant had taken their own contributions from raw improvisatory self-presentations and through the stages of composition and performative polish, participants then exchanged their pieces. The second half of the project involved taking on each other’s words, mannerisms, gestures, melodic and rhythmic speech patterns and inhabiting them through the rehearsal process as their own, thus the title, The Shared Breath Project. Here, in stage two the acting challenges evolved to be those of capturing the other and becoming the other through accurate mimicry that embraces Denis Diderot’s concept of the Paradox of Acting, in that the actor is both seeming and being simultaneous. This paper shares the carefully documented process of making the live-streamed theatre production that resulted from these workshops, writing processes and rehearsals, and forming, The Shared Breath Project, which ultimately took the students’ Realist, life-based pieces and edited them into a single unified theatre production. The paper also utilizes research on the Paradox of Acting, putting a Post-Structuralist spin on Diderot’s theory. Here, the paper suggests the limitations of inhabiting the other by allowing that the other is always already a thing impenetrable but nevertheless worthy of unceasing empathetic, striving and delving in an epoch in which slow, careful attention to our fellows is in short supply.

Keywords: otherness, paradox of acting, oral history theatre, devised theatre, political theatre, community-based theatre, peoples’ theatre

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Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

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The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose a novel inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multi-class. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: bayesian rule, gaussian process classification model with multiclass, gaussian process prior, human action classification, laplace approximation, variational EM algorithm

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Authors: Hugo Ribadeau Dumas

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In India, cities represent intense battlefields where patriarchal norms are simultaneously defied and reinforced. While Indian metropolises have witnessed numerous initiatives where women boldly claimed their right to the city, urban spaces still remain disproportionately unfriendly to female city-dwellers. As a result, the presence of strees (women, in Hindi) in the streets remains a socially and politically potent phenomenon. This paper explores how, in India, women engage with the city as compared to men. Borrowing analytical tools from urban geography, it uses Hindi cinema as a medium to map the extent to which activities, attitudes and experiences in urban spaces are highly gendered. The sample consists of 30 movies, both mainstream and independent, which were released between 2010 and 2020, were set in an urban environment and comprised at least one pivotal female character. The paper adopts a quantitative approach, consisting of the scrutiny of close to 3,000 minutes of footage, the labeling and time count of every scene, and the computation of regressions to identify statistical relationships between characters and the way they navigate the city. According to the analysis, female characters spend half less time in the public space than their male counterparts. When they do step out, women do it mostly for utilitarian reasons; inversely, in private spaces or in pseudo-public commercial places – like malls – they indulge in fun activities. For male characters, the pattern is the exact opposite: fun takes place in public and serious work in private. The characters’ attitudes in the streets are also greatly gendered: men spend a significant amount of time immobile, loitering, while women are usually on the move, displaying some sense of purpose. Likewise, body language and emotional expressiveness betray differentiated gender scripts: while women wander in the streets either smiling – in a charming role – or with a hostile face – in a defensive mode – men are more likely to adopt neutral facial expressions. These trends were observed across all movies, although some nuances were identified depending on the character's age group, social background, and city, highlighting that the urban experience is not the same for all women. The empirical pieces of evidence presented in this study are helpful to reflect on the meaning of public space in the context of contemporary Indian cities. The paper ends with a discussion on the link between universal access to public spaces and women's empowerment.

Keywords: cinema, Indian cities, public space, women empowerment

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Authors: P. R. Chauhan, S. K. Tyagi

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Adsorption refrigeration technology offers a sustainable and energy-efficient cooling alternative over traditional refrigeration technologies for meeting the fast-growing cooling demands. With its ability to utilize natural refrigerants, low-grade heat sources, and modular configurations, it has the potential to revolutionize the cooling industry. Despite these benefits, the commercial viability of this technology is hampered by several fundamental limiting constraints, including its large size, low uptake capacity, and poor performance as a result of deficient heat and mass transfer characteristics. The primary cause of adequate heat and mass transfer characteristics and magnitude of exergy loss in various real processes of adsorption cooling system can be assessed by the entropy generation rate analysis, i. e. Second law of Thermodynamics. Therefore, this article presents the second law of thermodynamic-based investigation in terms of entropy generation rate (EGR) to identify the energy losses in various processes of the HPCC-based adsorption system using MATLAB R2021b software. The adsorption technology-based cooling system consists of two beds made up of silica gel and arranged in a single stage, while the water is employed as a refrigerant, coolant, and hot fluid. The variation in process-wise EGR is examined corresponding to cycle time, and a comparative analysis is also presented. Moreover, the EGR is also evaluated in the external units, such as the heat source and heat sink unit used for regeneration and heat dump, respectively. The research findings revealed that the combination of adsorber and desorber, which operates across heat reservoirs with a higher temperature gradient, shares more than half of the total amount of EGR. Moreover, the EGR caused by the heat transfer process is determined to be the highest, followed by a heat sink, heat source, and mass transfer, respectively. in case of heat transfer process, the operation of the valve is determined to be responsible for more than half (54.9%) of the overall EGR during the heat transfer. However, the combined contribution of the external units, such as the source (18.03%) and sink (21.55%), to the total EGR, is 35.59%. The analysis and findings of the present research are expected to pinpoint the source of the energy waste in HPCC based adsorption cooling systems.

Keywords: adsorption cooling cycle, heat transfer, mass transfer, entropy generation, silica gel-water

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Nivedita Sharma

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The global demand for fossil fuels is very high, but their use is not sustainable since its reserves are declining. Additionally, fossil fuels are responsible for the accumulation of greenhouse gases. The emission of greenhouse gases from the transport sector can be reduced by substituting fossil fuels by biofuels. Thus, renewable fuels capable of sequestering carbon dioxide are in high demand. Second‐generation biofuels, which require lignocellulosic biomass as a substrate and ultimately producing ethanol, fall largely in this category. Bioethanol is a favorable and near carbon-neutral renewable biofuel leading to reduction in tailpipe pollutant emission and improving the ambient air quality. Lignocellulose consists of three main components: cellulose, hemicellulose and lignin which can be converted to ethanol with the help of microbial enzymes. Enzymatic hydrolysis of lignocellulosic biomass in 1st step is considered as the most efficient and least polluting methods for generating fermentable hexose and pentose sugars which subsequently are fermented to power alcohol by yeasts in 2nd step of the process. In the present technology, a complete bioconversion process i.e. potential hydrolytic enzymes i.e. cellulase and xylanase producing microorganisms have been isolated from different niches, screened for enzyme production, identified using phenotyping and genotyping, enzyme production, purification and application of enzymes for saccharification of different lignocellulosic biomass followed by fermentation of hydrolysate to ethanol with high yield is to be presented in detail.

Keywords: cellulase, xylanase, lignocellulose, bioethanol, microbial enzymes

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Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

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In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

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Authors: Alex Fedoseyev

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This study investigates a generalized hydrodynamic equation (GHE) simplified model for the simulation of turbulent flow over a two-dimensional backward-facing step (BFS) at Reynolds number Re=132000. The GHE were derived from the generalized Boltzmann equation (GBE). GBE was obtained by first principles from the chain of Bogolubov kinetic equations and considers particles of finite dimensions. The GHE has additional terms, temporal and spatial fluctuations, compared to the Navier-Stokes equations (NSE). These terms have a timescale multiplier τ, and the GHE becomes the NSE when $\tau$ is zero. The nondimensional τ is a product of the Reynolds number and the squared length scale ratio, τ=Re*(l/L)², where l is the apparent Kolmogorov length scale, and L is a hydrodynamic length scale. The BFS flow modeling results obtained by 2D calculations cannot match the experimental data for Re>450. One or two additional equations are required for the turbulence model to be added to the NSE, which typically has two to five parameters to be tuned for specific problems. It is shown that the GHE does not require an additional turbulence model, whereas the turbulent velocity results are in good agreement with the experimental results. A review of several studies on the simulation of flow over the BFS from 1980 to 2023 is provided. Most of these studies used different turbulence models when Re>1000. In this study, the 2D turbulent flow over a BFS with height H=L/3 (where L is the channel height) at Reynolds number Re=132000 was investigated using numerical solutions of the GHE (by a finite-element method) and compared to the solutions from the Navier-Stokes equations, k–ε turbulence model, and experimental results. The comparison included the velocity profiles at X/L=5.33 (near the end of the recirculation zone, available from the experiment), recirculation zone length, and velocity flow field. The mean velocity of NSE was obtained by averaging the solution over the number of time steps. The solution with a standard k −ε model shows a velocity profile at X/L=5.33, which has no backward flow. A standard k−ε model underpredicts the experimental recirculation zone length X/L=7.0∓0.5 by a substantial amount of 20-25%, and a more sophisticated turbulence model is needed for this problem. The obtained data confirm that the GHE results are in good agreement with the experimental results for turbulent flow over two-dimensional BFS. A turbulence model was not required in this case. The computations were stable. The solution time for the GHE is the same or less than that for the NSE and significantly less than that for the NSE with the turbulence model. The proposed approach was limited to 2D and only one Reynolds number. Further work will extend this approach to 3D flow and a higher Re.

Keywords: backward-facing step, comparison with experimental data, generalized hydrodynamic equations, separation, reattachment, turbulent flow

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Authors: Benish Chaudhry

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Most of the accidents these days are occurring because of the ‘text-and-drive’ concept. If we look at the structure of cities in UAE, there are great distances, because of which it is impossible to drive without using or merely checking the cellphone. Moreover, if we look at the road structure, it is almost impossible to stop at a point and text. With the introduction of TEXT STOPs, drivers will be able to stop different stops for a maximum of 1 and a half-minute in order to reply or write a message. They can be introduced at a distance of 10 minutes of driving on the average speed of the road, so the drivers can look forward to a stop and can reply to a text when needed. A user survey indicates that drivers are willing to NOT text-and-drive if they have such a facility available.

Keywords: transport, accidents, urban planning, road planning

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Authors: İsmail Seçer

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Although depression and anxiety disorders are considered to be adult disorders, the evidence obtained from several studies conducted recently shows that the roots of depression and anxiety disorders go back to childhood years. Thus, it is thought that analyzing depressive symptoms and anxiety disorders observed in the childhood is an important necessity. In the direction of the problem status of the study, the purpose of this study is to adapt anxiety and depression questionnaire for children into Turkish culture and analyze the psychometric characteristics of it on clinical and nonclinical samples separately. The study is a descriptive survey research. The study was conducted on two different sample groups, clinical and nonclinical. The clinical sample is formed of 205 individuals and the nonclinical sample is formed of 630 individuals. Through the study, anxiety and depression questionnaire for children, anxiety sensitivity index and obsessive compulsive disorder questionnaire for children were used. Experts’ opinions were asked to provide language validity of the scale. Confirmatory factor analysis and criterion-related validity to analyze construct validity and internal consistency and split-half reliability analyses were done for reliability. In the direction of experts’ opinions, construct validity of the scale was analyzed with simple confirmatory factor analysis and it was determined that the model fit of the two-factor structure of the scale gives good fit on both the clinical and nonclinical samples after determining that the language validity of the scale is provided. In criterion-related validity, it was determined that there are positive and significant relations between anxiety and depression questionnaire for children and anxiety sensitivity and obsessive compulsive disorder. The results of internal consistency and half-split reliability analyses also show that the scale has adequate reliability value. It can be said that depression and anxiety questionnaire for children which was adapted to determine depressive symptoms and anxiety disorders observed in childhood has adequate reliability and validity values and it can be used in future studies. It can be recommended that the psychometric characteristics of the scale can be analyzed and reported on new samples in the future studies.

Keywords: scale adapting, construct validity, confirmatory factor analysis, childhood depression

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Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova

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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.

Keywords: mechatronic systems, Matlab GUI, sensitivity, tolerance

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Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

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Authors: Anand Kumar Yadav

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Purpose – The purpose of this paper is to investigate the fluctuation of amplitude ratios of various transmitted and reflected waves. Design/methodology/approach – The reflection and transmission of plane waves on the interface between an orthotropic hygro-thermo-elastic half-space (OHTHS) and a viscous-fluid half-space (VFHS) were investigated in this study with reference to coupled hygro-thermo-elasticity. Findings – The interface, where y = 0, is struck by the principal (P) plane waves as they travel through the VFHS. Two waves are reflected in VFHS, and four waves are transmitted in OHTHS as a result namely longitudinal displacement, Pwave − , thermal diffusion TDwave − and moisture diffusion mDwave − and shear vertical SV wave. Expressions for the reflection and transmitted coefficient are developed for the incidence of a hygrothermal plane wave. It is noted that these ratios are graphically displayed and are observed under the influence of coupled hygro-thermo-elasticity. Research limitations/implications – There isn't much study on the model under consideration, which combines OHTHS and VFHS with coupled hygro-thermo-elasticity, according to the existing literature Practical implications – The current model can be applied in many different areas, such as soil dynamics, nuclear reactors, high particle accelerators, earthquake engineering, and other areas where linked hygrothermo-elasticity is important. In a range of technical and geophysical settings, wave propagation in a viscous fluid-thermoelastic medium with various characteristics, such as initial stress, magnetic field, porosity, temperature, etc., gives essential information regarding the presence of new and modified waves. This model may prove useful in modifying earthquake estimates for experimental seismologists, new material designers, and researchers. Social implications – Researchers may use coupled hygro-thermo-elasticity to categories the material, where the parameter is a new indication of its ability to conduct heat in interaction with diverse materials. Originality/value – The submitted text is the sole creation of the team of writers, and all authors equally contributed to its creation.

Keywords: hygro-thermo-elasticity, viscous fluid, reflection coefficient, transmission coefficient, moisture concentration

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Authors: Hari Singh, Abhishek Kamboj, Sudhir Kumar

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This investigation proposes a grey-based Taguchi method to solve the multi-response problems. The grey-based Taguchi method is based on the Taguchi’s design of experimental method, and adopts Grey Relational Analysis (GRA) to transfer multi-response problems into single-response problems. In this investigation, an attempt has been made to optimize the drilling process parameters considering weighted output response characteristics using grey relational analysis. The output response characteristics considered are surface roughness, burr height and hole diameter error under the experimental conditions of cutting speed, feed rate, step angle, and cutting environment. The drilling experiments were conducted using L27 orthogonal array. A combination of orthogonal array, design of experiments and grey relational analysis was used to ascertain best possible drilling process parameters that give minimum surface roughness, burr height and hole diameter error. The results reveal that combination of Taguchi design of experiment and grey relational analysis improves surface quality of drilled hole.

Keywords: metal matrix composite, drilling, optimization, step drill, surface roughness, burr height, hole diameter error

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Authors: Lu-Yin Lin

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The morphology of electroactive material is highly related to energy storage ability. Structure-directing agent (SDA) can design electroactive materials with favorable surface properties. Zeolitic imidazolate framework 67 (ZIF67) is one of the potential electroactive materials for energy storage devices. The SDA concept is less applied to designing ZIF67 derivatives in previous studies. An in-situ technique with ammonium fluoride (NH₄F) as SDA is proposed to produce a ZIF67 derivative with highly improved energy storage ability. Attracted by the effective in-situ technique, the NH₄F, ammonium bifluoride (NH₄HF₂), and ammonium tetrafluoroborate (NH₄BF₄) are first used as SDA to synthesize ZIF67 derivatives in one-step solution process as electroactive material of energy storage devices. The mechanisms of forming ZIF67 derivatives synthesized with different SDAs are discussed to explain the SDA effects on physical and electrochemical properties. The largest specific capacitance (CF) of 1527.0 Fg-¹ and the capacity of 296.9 mAhg-¹ are obtained for the ZIF67 derivative prepared using NH₄BF₄ as SDA. The energy storage device composed of the optimal ZIF67 derivative and carbon electrodes presents a maximum energy density of 15.1 Whkg-¹ at the power density of 857 Wkg-¹. The CF retention of 90% and Coulombic efficiency larger than 98% are also obtained after 5000 cycles.

Keywords: ammonium bifluoride, ammonium tetrafluoroborate, energy storage device, one-step solution process, structure-directing agent, zeolitic imidazolate framework 67

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Authors: A. Bekbaev, M. Dzhamanbaev, R. Abitaeva, A. Karbozova, G. Nabyeva

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In this paper, the regression dependence of dancing intensity from wind speed and length of span was established due to the statistic data obtained from multi-year observations on line wires dancing accumulated by power systems of Kazakhstan and the Russian Federation. The lower and upper limitations of the equations parameters were estimated, as well as the adequacy of the regression model. The constructed model will be used in research of dancing phenomena for the development of methods and means of protection against dancing and for zoning plan of the territories of line wire dancing.

Keywords: power lines, line wire dancing, dancing intensity, regression equation, dancing area intensity

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Authors: Kseniia Zviagintseva, Brett Buttliere

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Science is fundamentally a problem-solving enterprise, and scientists pay more attention to the negative things, that cause them dissonance and negative affective state of uncertainty or contradiction. While this is agreed upon by philosophers of science, there are few empirical demonstrations. Here we examine the keywords from those papers published by PLoS in 2014 and show with several sentiment analyzers that negative keywords are studied more than positive keywords. Our dataset is the 927,406 keywords of 32,870 scientific articles in all fields published in 2014 by the journal PLOS ONE (collected from Altmetric.com). Counting how often the 47,415 unique keywords are used, we can examine whether those negative topics are studied more than positive. In order to find the sentiment of the keywords, we utilized two sentiment analysis tools, Hu and Liu (2004) and SentiStrength (2014). The results below are for Hu and Liu as these are the less convincing results. The average keyword was utilized 19.56 times, with half of the keywords being utilized only 1 time and the maximum number of uses being 18,589 times. The keywords identified as negative were utilized 37.39 times, on average, with the positive keywords being utilized 14.72 times and the neutral keywords - 19.29, on average. This difference is only marginally significant, with an F value of 2.82, with a p of .05, but one must keep in mind that more than half of the keywords are utilized only 1 time, artificially increasing the variance and driving the effect size down. To examine more closely, we looked at those top 25 most utilized keywords that have a sentiment. Among the top 25, there are only two positive words, ‘care’ and ‘dynamics’, in position numbers 5 and 13 respectively, with all the rest being identified as negative. ‘Diseases’ is the most studied keyword with 8,790 uses, with ‘cancer’ and ‘infectious’ being the second and fourth most utilized sentiment-laden keywords. The sentiment analysis is not perfect though, as the words ‘diseases’ and ‘disease’ are split by taking 1st and 3rd positions. Combining them, they remain as the most common sentiment-laden keyword, being utilized 13,236 times. More than just splitting the words, the sentiment analyzer logs ‘regression’ and ‘rat’ as negative, and these should probably be considered false positives. Despite these potential problems, the effect is apparent, as even the positive keywords like ‘care’ could or should be considered negative, since this word is most commonly utilized as a part of ‘health care’, ‘critical care’ or ‘quality of care’ and generally associated with how to improve it. All in all, the results suggest that negative concepts are studied more, also providing support for the notion that science is most generally a problem-solving enterprise. The results also provide evidence that negativity and contradiction are related to greater productivity and positive outcomes.

Keywords: bibliometrics, keywords analysis, negativity bias, positive and negative words, scientific papers, scientometrics

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Authors: Shabnam Sarwar, Franck Lacoeuille, Nadia Withofs, Roland Hustinx

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After the development of a potential surrogate of MAA, and its successful application for the diagnosis of pulmonary embolism in artificially embolized rats’ lungs, this microparticulate system were radiolabelled with gallium-68 to synthesize 68Ga-SBMP with high radiochemical purity >99%. As a prerequisite step of clinical trials, 68Ga- labelled starch based microparticles (SBMP) were analysed for their in-vivo behavior in small animals. The purpose of the presented work includes the ex-vivo biodistribution studies of 68Ga-SBMP in order to assess the activity uptake in target organs with respect to time, excretion pathways of the radiopharmaceutical, %ID/g in major organs, T/NT ratios, in-vivo stability of the radiotracer and subsequently the microparticles in the target organs. Radiolabelling of starch based microparticles was performed by incubating it with 68Ga generator eluate (430±26 MBq) at room temperature and pressure without using any harsh reaction condition. For Ex-vivo biodistribution studies healthy White Wistar rats weighing between 345-460 g were injected intravenously 68Ga-SBMP 20±8 MBq, containing about 2,00,000-6,00,000 SBMP particles in a volume of 700µL. The rats were euthanized at predefined time intervals (5min, 30min, 60min and 120min) and their organ parts were cut, washed, and put in the pre-weighed tubes and measured for radioactivity counts through automatic Gamma counter. The 68Ga-SBMP produced >99% RCP just after 10-20 min incubation through a simple and robust procedure. Biodistribution of 68Ga-SBMP showed that initially just after 5 min post injection major uptake was observed in the lungs following by blood, heart, liver, kidneys, bladder, urine, spleen, stomach, small intestine, colon, skin and skeleton, thymus and at last the smallest activity was found in brain. Radioactivity counts stayed stable in lungs with gradual decrease with the passage of time, and after 2h post injection, almost half of the activity were seen in lungs. This is a sufficient time to perform PET/CT lungs scanning in humans while activity in the liver, spleen, gut and urinary system decreased with time. The results showed that urinary system is the excretion pathways instead of hepatobiliary excretion. There was a high value of T/NT ratios which suggest fine tune images for PET/CT lung perfusion studies henceforth further pre-clinical studies and then clinical trials should be planned in order to utilize this potential lung perfusion agent.

Keywords: starch based microparticles, gallium-68, biodistribution, target organs, excretion pathways

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Authors: Chih-Hung Chen, Yih-Shyang Cheng, Yu-Hsin Tu

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Holographic optical elements (HOEs) have recently been one of the most suitable components in optoelectronic technology owing to the requirement of the product system with compact size. Computer-generated holography (CGH) is a well-known technology for HOEs production. In some cases, a well-designed diffractive optical element with multifunctional components is also an important issue and needed for an advanced optoelectronic system. Spatial light modulator (SLM) is one of the key components that has great capability to display CGH pattern and is widely used in various applications, such as an image projection system. As mentioned to multifunctional components, such as phase and amplitude modulation of light, high-resolution hologram with multiple-exposure procedure is also one of the suitable candidates. However, holographic recording under multiple exposures, the diffraction efficiency of the final hologram is inevitably lower than that with single exposure process. In this study, a two-step holographic recording method, including the master hologram fabrication and the replicated hologram production, will be designed. Since there exist a reduction factor M² of diffraction efficiency in multiple-exposure holograms (M multiple exposures), so it seems that single exposure would be more efficient for holograms replication. In the second step of holographic replication, a stable optical system with one-shot copying is introduced. For commercial application, one may utilize this concept of holographic copying to obtain duplications of HOEs with higher optical performance.

Keywords: holographic replication, holography, one-shot copying, optical element

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Authors: Atousa Ataieyan, Salvador A. Gomez-Lopera, Gennaro Sepede

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Today, due to the growing urban population and consequently, the increasing water demand in cities, the amount of contaminants entering the water resources is increasing. This can impose harmful effects on the quality of the downstream water. Therefore, predicting the concentration of discharged pollutants at different times and distances of the interested area is of high importance in order to carry out preventative and controlling measures, as well as to avoid consuming the contaminated water. In this paper, the concentration distribution of an injected conservative pollutant in a square reservoir containing four symmetric blocks and three sources using Finite Volume Method (FVM) is simulated. For this purpose, after estimating the flow velocity, classical Advection-Diffusion Equation (ADE) has been discretized over the studying domain by Backward Time- Backward Space (BTBS) scheme. Then, the discretized equations for each node have been derived according to the initial condition, boundary conditions and point contaminant sources. Finally, taking into account the appropriate time step and space step, a computational code was set up in MATLAB. Contaminant concentration was then obtained at different times and distances. Simulation results show how using BTBS differentiating scheme and FVM as a numerical method for solving the partial differential equation of transport is an appropriate approach in the case of two-dimensional contaminant transfer in an advective-diffusive flow.

Keywords: BTBS differentiating scheme, contaminant concentration, finite volume, mass transfer, water pollution

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Authors: Rahul Singha, D. Vakula

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This paper presents a corrugated antipodal vivaldi antenna with improved performance by using negative index metamaterial (NIM) of the Archimedean spiral design. A single layer NIM piece is placed perpendicular middle of the two arm of the proposed antenna. The antenna size is 30×60×0.787 mm3 operating at 8GHz. The simulated results of NIM corrugated antipodal vivaldi antenna show that the gain and directivity has increased up to 1.2dB and 1dB respectively. The HPBW is increased by 90 with the reflection coefficient less than ‒10 dB from 4.7 GHz to 11 GHz for UWB application.

Keywords: Negative Index Metamaterial (NIM), Ultra Wide Band (UWB), Half Power Beam Width (HPBW), vivaldi antenna

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Authors: Siti Nur Syazni Mohd Zuki, Tan Ling Ling, Nina Suhaity Azmi, Chong Kwok Feng, Lee Yook Heng

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Nitrite (NO2-) ion is used prevalently as a preservative in processed meat. Elevated levels of nitrite also found in edible bird’s nests (EBNs). Consumption of NO2- ion at levels above the health-based risk may cause cancer in humans. Spectrophotometric Griess test is the simplest established standard method for NO2- ion detection, however, it requires careful control of pH of each reaction step and susceptible to strong oxidants and dyeing interferences. Other traditional methods rely on the use of laboratory-scale instruments such as GC-MS, HPLC and ion chromatography, which cannot give real-time response. Therefore, it is of significant need for devices capable of measuring nitrite concentration in-situ, rapidly and without reagents, sample pretreatment or extraction step. Herein, we constructed a microspheres-based microbial optode for visual quantitation of NO2- ion. Raoutella planticola, the bacterium expressing NAD(P)H nitrite reductase (NiR) enzyme has been successfully extracted by microbial technique from EBN collected from local birdhouse. The whole cells and the lipophilic Nile Blue chromoionophore were physically absorbed on the photocurable poly(n-butyl acrylate-N-acryloxysuccinimide) [poly (nBA-NAS)] microspheres, whilst the reduced coenzyme NAD(P)H was covalently immobilized on the succinimide-functionalized acrylic microspheres to produce a reagentless biosensing system. Upon the NiR enzyme catalyzes the oxidation of NAD(P)H to NAD(P)+, NO2- ion is reduced to ammonium hydroxide, and that a colour change from blue to pink of the immobilized Nile Blue chromoionophore is perceived as a result of deprotonation reaction increasing the local pH in the microspheres membrane. The microspheres-based optosensor was optimized with a reflectance spectrophotometer at 639 nm and pH 8. The resulting microbial bio-optode membrane could quantify NO2- ion at 0.1 ppm and had a linear response up to 400 ppm. Due to the large surface area to mass ratio of the acrylic microspheres, it allows efficient solid state diffusional mass transfer of the substrate to the bio-recognition phase, and achieve the steady state response as fast as 5 min. The proposed optical microbial biosensor requires no sample pre-treatment step and possesses high stability as the whole cell biocatalyst provides protection to the enzymes from interfering substances, hence it is suitable for measurements in contaminated samples.

Keywords: acrylic microspheres, microbial bio-optode, nitrite ion, reflectometric

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Authors: Meng Xu, Alexis K. H. Lau, Ming Xu, Bill Barron, Narges Shahraki

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As an emerging unconventional energy, shale gas has been an economically viable step towards a cleaner energy future in U.S. China also has shale resources that are estimated to be potentially the largest in the world. In addition, China has enormous unmet for a clean alternative to substitute coal. Nonetheless, the geological complexity of China’s shale basins and issues of water scarcity potentially impose serious constraints on shale gas development in China. Further, even if China could replicate to a significant degree the U.S. shale gas boom, China faces the problem of transporting the gas efficiently overland with its limited pipeline network throughput capacity and coverage. The aim of this study is to identify the potential bottlenecks in China’s gas transmission network, as well as to examine the shale gas development affecting particular supply locations and demand centers. We examine this through application of three scenarios with projecting domestic shale gas supply by 2020: optimistic, medium and conservative shale gas supply, taking references from the International Energy Agency’s (IEA’s) projections and China’s shale gas development plans. Separately we project the gas demand at provincial level, since shale gas will have more significant impact regionally than nationally. To quantitatively assess each shale gas development scenario, we formulated a gas pipeline optimization model. We used ArcGIS to generate the connectivity parameters and pipeline segment length. Other parameters are collected from provincial “twelfth-five year” plans and “China Oil and Gas Pipeline Atlas”. The multi-objective optimization model uses GAMs and Matlab. It aims to minimize the demands that are unable to be met, while simultaneously seeking to minimize total gas supply and transmission costs. The results indicate that, even if the primary objective is to meet the projected gas demand rather than cost minimization, there’s a shortfall of 9% in meeting total demand under the medium scenario. Comparing the results between the optimistic and medium supply of shale gas scenarios, almost half of the shale gas produced in Sichuan province and Chongqing won’t be able to be transmitted out by pipeline. On the demand side, the Henan province and Shanghai gas demand gap could be filled as much as 82% and 39% respectively, with increased shale gas supply. To conclude, the pipeline network in China is currently not sufficient in meeting the projected natural gas demand in 2020 under medium and optimistic scenarios, indicating the need for substantial pipeline capacity expansion for some of the existing network, and the importance of constructing new pipelines from particular supply to demand sites. If the pipeline constraint is overcame, Beijing, Shanghai, Jiangsu and Henan’s gas demand gap could potentially be filled, and China could thereby reduce almost 25% its dependency on LNG imports under the optimistic scenario.

Keywords: energy policy, energy systematic analysis, scenario analysis, shale gas in China

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Authors: Hoda Mahgoub, Abeer Hanafy

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Linagliptin (LNG) belongs to dipeptidyl-peptidase-4 (DPP-4) inhibitor class. DPP-4 inhibitors represent a new therapeutic approach for the treatment of type 2 diabetes in adults. The aim of this work was to develop and validate an accurate and reproducible HPLC method for the determination of LNG with high sensitivity in rat plasma. The method involved separation of both LNG and pindolol (internal standard) at ambient temperature on a Zorbax Eclipse XDB C18 column and a mobile phase composed of 75% methanol: 25% formic acid 0.1% pH 4.1 at a flow rate of 1.0 mL.min-1. UV detection was performed at 254nm. The method was validated in compliance with ICH guidelines and found to be linear in the range of 5–1000ng.mL-1. The limit of quantification (LOQ) was found to be 5ng.mL-1 based on 100µL of plasma. The variations for intra- and inter-assay precision were less than 10%, and the accuracy values were ranged between 93.3% and 102.5%. The extraction recovery (R%) was more than 83%. The method involved a single extraction step of a very small plasma volume (100µL). The assay was successfully applied to an in-vivo pharmacokinetic study of LNG in rats that were administered a single oral dose of 10mg.kg-1 LNG. The maximum concentration (Cmax) was found to be 927.5 ± 23.9ng.mL-1. The area under the plasma concentration-time curve (AUC0-72) was 18285.02 ± 605.76h.ng.mL-1. In conclusion, the good accuracy and low LOQ of the bioanalytical HPLC method were suitable for monitoring the full pharmacokinetic profile of LNG in rats. The main advantages of the method were the sensitivity, small sample volume, single-step extraction procedure and the short time of analysis.

Keywords: HPLC, linagliptin, pharmacokinetic study, rat plasma

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Authors: Marian Sagat, Mariana Remesikova

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In civil engineering, there is a problem how to industrially produce tensile membrane structures that are non-developable surfaces. Nondevelopable surfaces can only be developed with a certain error and we want to minimize this error. To that goal, the non-developable surfaces are cut into plates along to the geodesic curves. We propose a numerical algorithm for finding approximations of open geodesics on meshes and surfaces based on geodesic curvature flow. For practical reasons, it is important to automatize the choice of the time step. We propose a method for automatic setting of the time step based on the diagonal dominance criterion for the matrix of the linear system obtained by discretization of our partial differential equation model. Practical experiments show reliability of this method. Because approximation of the model is made by numerical method based on classic derivatives, it is necessary to solve obstacles which occur for meshes with sharp corners. We solve this problem for big family of meshes with sharp corners via special rotations which can be seen as partial unfolding of the mesh. In practical applications, it is required that the approximation of geodesic has its vertices only on the edges of the mesh. This problem is solved by a specially designed pointing tracking algorithm. We also partially solve the problem of finding geodesics on meshes with holes. We implemented the whole algorithm in Rhinoceros (commercial 3D computer graphics and computer-aided design software ). It is done by using C# language as C# assembly library for Grasshopper, which is plugin in Rhinoceros.

Keywords: geodesic, geodesic curvature flow, mesh, Rhinoceros software

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Authors: Haiqiang Song, Huiqing Liu

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The Doseo basin in Chad, Central Africa is one of the most important oil and gas blocks in the world. However, the low degree of oil and gas exploration and the lack of relevant geological data restrict the understanding and resource evaluation of the basin. To further develop the Doseo basin efficiently, it is urgent to deeply analyze the source rock characteristics and hydrocarbon generation potential of the Doseo basin. Based on seismic and drilling data in recent years, this paper systematically evaluates the geochemical characteristics of source rocks and their generated oils in Doseo Basin, explores the development, distribution, and evolution characteristics of source rocks, and evaluates the exploration potential of Doseo Basin according to the hydrocarbon enrichment law. The results show that the Lower Cretaceous Baliemian and Apudian source rocks in Doseo Basin are well developed, with high organic matter abundance (average TOC≥3%) and good organic matter types (type I~II), which are the main development layers of source rocks, but the organic matter maturity is generally low (Ro of the drilled source rocks is mainly between 0.4%~0.8%). The planar structure also shows that the main hydrocarbon accumulation mode in Doseo sag is the forward tectonic reservoirs such as near source anticlines and faulted noses. Finally, it is estimated that the accumulative resources of the main source rocks in the Doseo Basin are about 4.33× 108T in Apudite and Balim terrace layers. The results of this study will help guide the next step of oil and gas exploration, which is expected to drive the next step of oil and gas development.

Keywords: Doseo basin, lower cretaceous, source rock characteristics, developmental characteristics, hydrocarbon generation potential

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Authors: Camille Perréard, Yoann Ladner, Fanny D'Orlyé, Stéphanie Descroix, Vélan Taniga, Anne Varenne, Cédric Guyon, Michael. Tatoulian, Frédéric Kanoufi, Cyrine Slim, Sophie Griveau, Fethi Bedioui

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The development of micro total analysis systems is of major interest for contaminant and biomarker analysis. As a lab-on-chip integrates all steps of an analysis procedure in a single device, analysis can be performed in an automated format with reduced time and cost, while maintaining performances comparable to those of conventional chromatographic systems. Moreover, these miniaturized systems are either compatible with field work or glovebox manipulations. This work is aimed at developing an analytical microsystem for trace and ultra trace quantitation in complex matrices. The strategy consists in the integration of a sample pretreatment step within the lab-on-chip by a confinement zone where selective ligands are immobilized for target extraction and preconcentration. Aptamers were chosen as selective ligands, because of their high affinity for all types of targets (from small ions to viruses and cells) and their ease of synthesis and functionalization. This integrated target extraction and concentration step will be followed in the microdevice by an electrokinetic separation step and an on-line detection. Polymers consisting of cyclic olefin copolymer (COC) or fluoropolymer (Dyneon THV) were selected as they are easy to mold, transparent in UV-visible and have high resistance towards solvents and extreme pH conditions. However, because of their low chemical reactivity, surface treatments are necessary. For the design of this miniaturized diagnostics, we aimed at modifying the microfluidic system at two scales : (1) on the entire surface of the microsystem to control the surface hydrophobicity (so as to avoid any sample wall adsorption) and the fluid flows during electrokinetic separation, or (2) locally so as to immobilize selective ligands (aptamers) on restricted areas for target extraction and preconcentration. We developed different novel strategies for the surface functionalization of COC and Dyneon, based on plasma, chemical and /or electrochemical approaches. In a first approach, a plasma-induced immobilization of brominated derivatives was performed on the entire surface. Further substitution of the bromine by an azide functional group led to covalent immobilization of ligands through “click” chemistry reaction between azides and terminal alkynes. COC and Dyneon materials were characterized at each step of the surface functionalization procedure by various complementary techniques to evaluate the quality and homogeneity of the functionalization (contact angle, XPS, ATR). With the objective of local (micrometric scale) aptamer immobilization, we developed an original electrochemical strategy on engraved Dyneon THV microchannel. Through local electrochemical carbonization followed by adsorption of azide-bearing diazonium moieties and covalent linkage of alkyne-bearing aptamers through click chemistry reaction, typical dimensions of immobilization zones reached the 50 µm range. Other functionalization strategies, such as sol-gel encapsulation of aptamers, are currently investigated and may also be suitable for the development of the analytical microdevice. The development of these functionalization strategies is the first crucial step in the design of the entire microdevice. These strategies allow the grafting of a large number of molecules for the development of new analytical tools in various domains like environment or healthcare.

Keywords: alkyne-azide click chemistry (CuAAC), electrochemical modification, microsystem, plasma bromination, surface functionalization, thermoplastic polymers

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Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

Procedia PDF Downloads 165

Authors: Ömer Faruk Ada, Türker Baş, M. Yaman Öztek

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In this study, we aim to investigate the skills to be owned by procurement professionals in order to fulfill their developing and changing role completely. Market conditions, competitive pressure, and high financial costs make it more important than ever for organizations to be able to use resources more efficiently. Research shows that procurement expenses consist more than 50 % of the operating expenses. With increasing profit impact of procurement, reviewing the position of the procurement function within the organization has become inevitable. This study is significant as it indicates the necessary skills that procurement professionals must have to keep in step with the transformation of procurement units from transaction oriented to value chain oriented. In this study, the transformation of procurement is investigated from the perspective of procurement professionals and we aim to answer following research questions: • How do procurement professionals perceive their role within the organization? • How has their role changed and what challenges have they had to face? • What portfolio of skills do they believe will enable them to fulfill their role effectively? Literature review consists of the first part of the study by investigating the changing role of procurement from different perspectives. In the second part, we present the results of the in-depth interviews with 15 procurement professionals and we used descriptive analysis as a methodology. In the light of these results, we classified procurement skills under operational, tactical and strategic levels and Procurement Skills Framework has been developed. This study shows the differences in the perception of purchasing by professionals and the organizations. The differences in the perception are considered as an important barrier beyond the procurement transformation. Although having the necessary skills has a significant effect for procurement professionals to fulfill their role completely and keep in step with the transformation of the procurement function, It is not the only factor and the degree of high-level management and organizational support has also a direct impact during this transformation.

Keywords: procuement skills, procurement transformation, strategic procurement, value chain

Procedia PDF Downloads 412