Search results for: plug-in hybrid electric vehicle

Authors: Karen G. Bastidas Gomez, Hugo R. Zea Ramirez, Manuel F. Ribeiro Pereira, Cesar A. Sierra Avila, Juan A. Clavijo Morales

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The contamination of water sources with heavy metals such as mercury has been an environmental problem; it has generated a high impact on the environment and human health. In countries such as Colombia, mercury contamination due to mining has reached levels much higher than the world average. This work proposes the use of fique fibers as adsorbent in mercury removal. The evaluation of the material was carried out under five different conditions (raw, pretreated by organosolv, functionalized by TEMPO oxidation, fiber functionalized plus MOF-199 and fiber functionalized plus MOF-199-SH). All the materials were characterized using FTIR, SEM, EDX, XRD, and TGA. Regarding the mercury removal, it was done under room pressure and temperature, also pH = 7 for all materials presentations, followed by Atomic Absorption Spectroscopy. The high cellulose content in fique is the main particularity of this lignocellulosic biomass since the degree of oxidation depends on the number of hydroxyl groups on the surface capable of oxidizing into carboxylic acids, a functional group capable of increasing ion exchange with mercury in solution. It was also expected that the impregnation of the MOF would increase the mercury removal; however, it was found that the functionalized fique achieved a greater percentage of removal, resulting in 81.33% of removal, 44% for the fique with the MOF-199 and 72% for the MOF-199-SH with. The pretreated fiber and raw also showed 74% and 56%, respectively, which indicates that fique does not require considerable modifications in its structure to achieve good performances. Even so, the functionalized fiber increases the percentage of removal considerably compared to the pretreated fique, which suggests that the functionalization process is a feasible procedure to apply with the purpose of improving the removal percentage. In addition, this is a procedure that follows a green approach since the reagents involved have low environmental impact, and the contribution to the remediation of natural resources is high.

Keywords: biomass, nanotechnology, science materials, wastewater treatment

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Authors: Padmini S. Navalgund, Manasi Naik, Ujwala Patil

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Road hump is a semi-cylindrical elevation on the road made across specific locations of the road. The vehicle needs to maneuver the hump by reducing the speed to avoid car damage and pass over the road hump safely. Road Humps on road surfaces, if identified in advance, help to maintain the security and stability of vehicles, especially in adverse visibility conditions, viz. night scenarios. We have proposed a deep learning architecture adaptation by implementing the MISH activation function and developing a new classification loss function called "Effective Focal Loss" for Indian road humps detection in adverse light scenarios. We captured images comprising of marked and unmarked road humps from two different types of cameras across South India to build a heterogeneous dataset. A heterogeneous dataset enabled the algorithm to train and improve the accuracy of detection. The images were pre-processed, annotated for two classes viz, marked hump and unmarked hump. The dataset from these images was used to train the single-stage object detection algorithm. We utilised an algorithm to synthetically generate reduced visible road humps scenarios. We observed that our proposed framework effectively detected the marked and unmarked hump in the images in clear and ad-verse light environments. This architectural adaptation sets up an option for early detection of Indian road humps in reduced visibility conditions, thereby enhancing the autonomous driving technology to handle a wider range of real-world scenarios.

Keywords: Indian road hump, reduced visibility condition, low light condition, adverse light condition, marked hump, unmarked hump, YOLOv9

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Authors: Yaping Gao

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With the increasing globalization of education and the continued momentum and wider adoption of online and digital learning all over the world, post pandemic, how could best practices and extensive experience gained from the higher education community over the past few decades be adopted and adapted to benefit international communities, which can be vastly different culturally and pedagogically? How can schools and institutions adopt, adapt and apply these proven practices to develop strategic plans for digital transformation at institutional levels, and to improve or create quality online or digital learning environments at course and program levels to help all students succeed? The presenter will introduce the primary components of the US-based quality assurance process, including : 1) five sets of research-supported standards to guide the design, development and review of online and hybrid courses; 2) professional development offerings and pathways for administrators, faculty and instructional support staff; 3) a peer-review process for course/program reviews resulting in constructive recommendations for continuous improvement, certification of quality and international recognition; and 4) implementation of the quality assurance process on a continuum to program excellence, achievement of institutional goals, and facilitation of accreditation process and success. Regardless language, culture, pedagogical practices, or technological infrastructure, the core elements of quality teaching and learning remain the same across all delivery formats. What is unique is how to ensure quality of teaching and learning in online education and digital learning. No one knows all the answers to everything but no one needs to reinvent the wheel either. Together the international education community can support and learn from each other to achieve institutional goals and ensure all students succeed in the digital learning environments.

Keywords: Online Education, Digital Learning, Quality Assurance, Standards and Best Practices

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Luiz G. Véras, Felipe L. Medeiros, Lamartine F. Guimarães

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This work approaches the automatic planning of paths for Unmanned Aerial Vehicles (UAVs) through the application of the Rapidly Exploring Random Tree Star-Smart (RRT*-Smart) algorithm. RRT*-Smart is a sampling process of positions of a navigation environment through a tree-type graph. The algorithm consists of randomly expanding a tree from an initial position (root node) until one of its branches reaches the final position of the path to be planned. The algorithm ensures the planning of the shortest path, considering the number of iterations tending to infinity. When a new node is inserted into the tree, each neighbor node of the new node is connected to it, if and only if the extension of the path between the root node and that neighbor node, with this new connection, is less than the current extension of the path between those two nodes. RRT*-smart uses an intelligent sampling strategy to plan less extensive routes by spending a smaller number of iterations. This strategy is based on the creation of samples/nodes near to the convex vertices of the navigation environment obstacles. The planned paths are smoothed through the application of the method called quintic pythagorean hodograph curves. The smoothing process converts a route into a dynamically-viable one based on the kinematic constraints of the vehicle. This smoothing method models the hodograph components of a curve with polynomials that obey the Pythagorean Theorem. Its advantage is that the obtained structure allows computation of the curve length in an exact way, without the need for quadratural techniques for the resolution of integrals.

Keywords: path planning, path smoothing, Pythagorean hodograph curve, RRT*-Smart

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Authors: L. Tonia, I. Daglis, W. Kurth

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The sound of the universe creates an affinity with the sounds of music. The analysis of the sound of space focuses on the existence of a tone material, the microstructure and macrostructure, and the form of the sound through the signals recorded during the flight of the spacecraft Van Allen Probes and Cassini’s mission. The sound becomes from the frequencies that belong to electromagnetic waves. Plasma Wave Science Instrument and Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) recorded the signals from space. A transformation of that signals to audio gave the opportunity to study and analyze the sound. Due to the fact that the musical tone pitch has a frequency and every electromagnetic wave produces a frequency too, the creation of a musical score, which appears as the sound of space, can give information about the form, the symmetry, and the harmony of the sound. The conversion of space radio emissions to audio provides a number of tone pitches corresponding to the original frequencies. Through the process of these sounds, we have the opportunity to present a music score that “composed” from space. In this score, we can see some basic features associated with the music form, the structure, the tone center of music material, the construction and deconstruction of the sound. The structure, which was built through a harmonic world, includes tone centers, major and minor scales, sequences of chords, and types of cadences. The form of the sound represents the symmetry of a spiral movement not only in micro-structural but also to macro-structural shape. Multiple glissando sounds in linear and polyphonic process of the sound, founded in magnetic fields around Earth, Saturn, and Jupiter, but also a spiral movement appeared on the spectrogram of the sound. Whistles, Auroral Kilometric Radiations, and Chorus emissions reveal movements similar to musical excerpts of works by contemporary composers like Sofia Gubaidulina, Iannis Xenakis, EinojuhamiRautavara.

Keywords: space sound analysis, spiral, space music, analysis

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Susmita Roy, Madhavan Nallani

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In recent years' polymersomes, self-assembled polymeric vesicles emerge from block copolymers, have been widely investigated due to their enhance stability and unique advantageous properties compared to their phospholipid counterpart, liposomes, dendrimers, and micelles. It provides a distinctive platform for advanced therapeutics and the creation of complex (bio) catalytically active systems for research in Nanomedicine and synthetic biology. Inspired by nature, where compartmentalization of biological components is all ubiquitous, we are interested in developing a platform technology of self-assembled multifunctional compartments with applications in areas from targeted drug/gene delivery, biosensing, pharmaceutical to cosmetics. Polymersome surfaces can be a proper choice of derivatization with a controlled amount of functional groups. To achieve site-specific targeting of polymersomes, biological recognition motives can be attached to the polymersomes surface by standard bioconjugation techniques, (like esterification, amidation, thiol-maleimide coupling, click-chemistry routes or other coupling methods). Herein, we are developing easy going, one-step bioconjugation strategies for site-specific surface functionalized biodegradable polymeric and/or polymer-lipid hybrid vesicles for targeted drug delivery. Biodegradable polymer, polycaprolactone-b-polyethylene glycol (PCL-PEG), polylactic acid-b-polyethylene glycol (PLA-PEG) and phospholipid, 1-palmitoyl-2- oleoyl-sn-glycero-3-phosphocholine (POPC) has been widely used for numerous vesicle formulations. Some of these drug-loaded formulations are being tested on mice for controlled release. These surface functionalized polymersomes are also appropriate for membrane protein reconstitution/insertion, antibodies conjugation and various bioconjugation with diverse targeted molecules for controlled drug delivery.

Keywords: drug delivery, membrane protein, polymersome, surface modification

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Authors: Mahmoud Abdulhamid, Rifan Hardian, Prashant Bhatt, Shuvo Datta, Adrian Ramirez, Jorge Gascon, Mohamed Eddaoudi, Gyorgy Szekely

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Polybenzimidazole (PBI) is a high-performance polymer that exhibits high thermal and chemical stability. However, it suffers from low porosity and low fractional free volume, which hinder its application as separation material. Herein, we demonstrate the molecular engineering of gas separation materials by manipulating a PBI backbone possessing kinked moieties. PBI was selected as it contains NH groups which increase the affinity towards CO₂, increase sorption capacity, and favors CO₂ over other gasses. We have designed and synthesized an intrinsically microporous polybenzimidazole (iPBI) featuring a spirobisindane structure. Introducing a kinked moiety in conjunction with crosslinking enhanced the polymer properties, markedly increasing the gas separation performance. In particular, the BET surface area of PBI increased 30-fold by replacing a flat benzene ring with a kinked structure. iPBI displayed a good CO₂ uptake of 1.4 mmol g⁻¹ at 1 bar and 3.6 mmol g⁻¹ at 10 bar. Gas sorption uptake and breakthrough experiments were conducted using mixtures of CO₂/CH₄ (50%/50%) and CO₂/N₂ (50%/50%), which revealed the high selectivity of CO₂ over both CH₄ and N₂. The obtained CO₂/N₂ selectivity is attractive for power plant flue gas application requiring CO₂ capturing materials. Energy and process simulations of biogas CO₂ removal demonstrated that up to 70% of the capture energy could be saved when iPBI was used rather than the current amine technology (methyl diethanolamine [MDEA]). Similarly, the combination of iPBI and MDEA in a hybrid system exhibited the highest CO₂ capture yield (99%), resulting in nearly 50% energy saving. The concept of enhancing the porosity of PBI using kinked moieties provides new scope for designing highly porous polybenzimidazoles for various separation processes.

Keywords: polybenzimidazole (PBI), intrinsically microporous polybenzimidazole (iPBI), gas separation, pnergy and process simulations

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Authors: Bhat Geetalaxmi Jairam, D. V. Ashoka

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Wireless Sensor Networks are used in many applications to collect sensed data from different sources. Sensed data has to be delivered through sensors wireless interface using multi-hop communication towards the sink. The data collection in wireless sensor networks consumes energy. Energy consumption is the major constraints in WSN .Reducing the energy consumption while increasing the amount of generated data is a great challenge. In this paper, we have implemented two data gathering protocols with multiple mobile sinks/elements to collect data from sensor nodes. First, is Energy-Efficient Data Gathering with Tour Length-Constrained Mobile Elements in Wireless Sensor Networks (EEDG), in which mobile sinks uses vehicle routing protocol to collect data. Second is An Intelligent Agent-based Routing Structure for Mobile Sinks in WSNs (IAR), in which mobile sinks uses prim’s algorithm to collect data. Authors have implemented concepts which are common to both protocols like deployment of mobile sinks, generating visiting schedule, collecting data from the cluster member. Authors have compared the performance of both protocols by taking statistics based on performance parameters like Delay, Packet Drop, Packet Delivery Ratio, Energy Available, Control Overhead. Authors have concluded this paper by proving EEDG is more efficient than IAR protocol but with few limitations which include unaddressed issues likes Redundancy removal, Idle listening, Mobile Sink’s pause/wait state at the node. In future work, we plan to concentrate more on these limitations to avail a new energy efficient protocol which will help in improving the life time of the WSN.

Keywords: aggregation, consumption, data gathering, efficiency

Procedia PDF Downloads 497

Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Mfoniso Udofia Aka

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A seismic refraction and resistivity survey was conducted in Ini Local Government Area, South-South Nigeria, to evaluate the structural setting and groundwater potential. The study involved 20 Vertical Electrical Soundings (VES) using an ABEM Terrameter with a Schlumberger array and a 400-meter electrode spread, analyzed with WinResist software. Concurrently, 20 seismic refraction surveys were performed with a Geometric ES 3000 12-Channel seismograph, employing a 60-meter slant interval. The survey identified three distinct geological layers: top, middle, and lower. Seismic velocities (Vp) ranged from 209 to 500 m/s in the top layer, 221 to 1210 m/s in the middle layer, and 510 to 1700 m/s in the lower layer. Secondary seismic velocities (Vs) ranged from 170 to 410 m/s in the topsoil, 205 to 880 m/s in the middle layer, and 480 to 1120 m/s in the lower layer. Poisson’s ratios varied from -0.029 to -7.709 for the top layer, -0.027 to -6.963 for the middle layer, and -0.144 to -6.324 for the lower layer. The depths of these layers were approximately 1.0 to 3.0 meters for the top layer, 4.0 to 12.0 meters for the middle layer, and 8.0 to 14.5 meters for the lower layer. The topsoil consists of a surficial layer overlaid by reddish/clayey laterite and fine to medium coarse-grained sandy material, identified as the auriferous zone. Resistivity values were 1300 to 3215 Ωm for the topsoil, 720 to 1600 Ωm for the laterite, and 100 to 1350 Ωm for the sandy zone. Aquifer thickness and depth varied, with shallow aquifers ranging from 4.5 to 15.2 meters, medium-depth aquifers from 15.5 to 70.0 meters, and deep aquifers from 4.0 to 70.0 meters. Locations 1, 15, and 13 exhibited favorable water potential with shallow formations, while locations 5, 11, 9, and 14 showed less potential due to the lack of fractured or weathered zones. The auriferous sandy zone indicated significant potential for industrial development. Future surveys should consider using a more robust energy source to enhance data acquisition and accuracy.

Keywords: hydrogeological, aquifer, seismic section geo-electric section, stratigraphy

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Authors: Nicholas Pearce, Eun-jin Kim

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Pathologies of the cardiovascular (CV) system remain a serious and deadly health problem for human society. Computational modelling provides a relatively accessible tool for diagnosis, treatment, and research into CV disorders. However, numerical models of the CV system have largely focused on the function of the ventricles, frequently overlooking the behaviour of the atria. Furthermore, in the study of the pressure-volume relationship of the heart, which is a key diagnosis of cardiac vascular pathologies, previous works often evoke popular yet questionable time-varying elastance (TVE) method that imposes the pressure-volume relationship instead of calculating it consistently. Despite the convenience of the TVE method, there have been various indications of its limitations and the need for checking its validity in different scenarios. A model of the combined left ventricle (LV) and left atrium (LA) is presented, which consistently considers various feedback mechanisms in the heart without having to use the TVE method. Specifically, a synergistic model of the left ventricle is extended and modified to include the function of the LA. The synergy of the original model is preserved by modelling the electro-mechanical and chemical functions of the micro-scale myofiber for the LA and integrating it with the microscale and macro-organ-scale heart dynamics of the left ventricle and CV circulation. The atrioventricular node function is included and forms the conduction pathway for electrical signals between the atria and ventricle. The model reproduces the essential features of LA behaviour, such as the two-phase pressure-volume relationship and the classic figure of eight pressure-volume loops. Using this model, disorders in the internal cardiac electrical signalling are investigated by recreating the mechano-electric feedback (MEF), which is impossible where the time-varying elastance method is used. The effects of AV node block and slow conduction are then investigated in the presence of an atrial arrhythmia. It is found that electrical disorders and arrhythmia in the LA degrade the CV system by reducing the cardiac output, power, and heart rate.

Keywords: cardiovascular system, left atrium, numerical model, MEF

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Authors: Folong Tchoffo Marlyse Fabiola, Anaba Onana Achille Basile

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Located in the western region of Cameroon, in the BAMBOUTOS department, the city of Mbouda belongs to the Pan-African basement. The water resources exploited in this region consist of surface water and groundwater from weathered and fractured aquifers within the same basement. To study the factors determining the productivity of aquifers in the Mbouda area, we adopted a methodology based on collecting data from boreholes drilled in the region, identifying different types of rocks, analyzing structures, and conducting geophysical surveys in the field. The results obtained allowed us to distinguish two main types of rocks: metamorphic rocks composed of amphibolites and migmatitic gneisses and igneous rocks, namely granodiorites and granites. Several types of structures were also observed, including planar structures (foliation and schistosity), folded structures (folds), and brittle structures (fractures and lineaments). A structural synthesis combines all these elements into three major phases of deformation. Phase D1 is characterized by foliation and schistosity, phase D2 is marked by shear planes and phase D3 is characterized by open and sealed fractures. The analysis of structures (fractures in outcrops, Landsat lineaments, subsurface structures) shows a predominance of ENE-WSW and WNW-ESE directions. Through electrical surveys and borehole data, we were able to identify the sequence of different geological formations. Four geo-electric layers were identified, each with a different electrical conductivity: conductive, semi-resistive, or resistive. The last conductive layer is considered a potentially aquiferous zone. The flow rates of the boreholes ranged from 2.6 to 12 m3/h, classified as moderate to high according to the CIEH classification. The boreholes were mainly located in basalts, which are mineralogically rich in ferromagnesian minerals. This mineral composition contributes to their high productivity as they are more likely to be weathered. The boreholes were positioned along linear structures or at their intersections.

Keywords: Mbouda, Pan-African basement, productivity, west-Cameroon

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Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

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Authors: Belal Bakheet, John Beardall, Xiwang Zhang, David McCarthy

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The potential risks associated with toxic cyanobacteria have raised growing environmental and public health concerns leading to an increasing effort into researching ways to bring about their removal from water, together with destruction of their associated cyanotoxins. A variety of toxins are synthesized by cyanobacteria and include hepatotoxins, neurotoxins, and cytotoxins which can cause a range of symptoms in humans from skin irritation to serious liver and nerve damage. Therefore drinking water treatment processes should ensure the consumers’ safety by removing both cyanobacterial cells, and cyanotoxins from the water. Cyanobacterial cells and cyanotoxins presented challenges to the conventional water treatment systems; their accumulation within drinking water treatment plants has been reported leading to plants shut down. Thus, innovative and effective water purification systems to tackle cyanobacterial pollution are required. In recent years there has been increasing attention to the electrochemical oxidation process as a feasible alternative disinfection method which is able to generate in situ a variety of oxidants that would achieve synergistic effects in the water disinfection process and toxin degradation. By utilizing only electric current, the electrochemical process through electrolysis can produce reactive oxygen species such as hydroxyl radicals from the water, or other oxidants such as chlorine from chloride ions present in the water. From extensive physiological and morphological investigation of cyanobacterial cells during electrolysis, our results show that these oxidants have significant impact on cell inactivation, simultaneously with cyanotoxins removal without the need for chemicals addition. Our research aimed to optimize existing electrochemical oxidation systems and develop new systems to treat water containing toxic cyanobacteria and cyanotoxins. The research covers detailed mechanism study on oxidants production and cell inactivation in the treatment under environmental conditions. Overall, our study suggests that the electrochemical treatment process e is an effective method for removal of toxic cyanobacteria and cyanotoxins.

Keywords: toxic cyanobacteria, cyanotoxins, electrochemical process, oxidants

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Authors: Mohammadreza Salek Faramarzi, Touraj Taghikhany

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In this paper, seismic fragility assessment of a recently developed hybrid structural system, known as the strongback system (SBS) is investigated. In this system, to mitigate the occurrence of the soft-story mechanism and improve the distribution of story drifts over the height of the structure, an elastic vertical truss is formed. The strengthened members of the braced span are designed to remain substantially elastic during levels of excitation where soft-story mechanisms are likely to occur and impose a nearly uniform story drift distribution. Due to the distinctive characteristics of near-field ground motions, it seems to be necessary to study the effect of these records on seismic performance of the SBS. To this end, a set of 56 near-field ground motion records suggested by FEMA P695 methodology is used. For fragility assessment, nonlinear dynamic analyses are carried out in OpenSEES based on the recommended procedure in HAZUS technical manual. Four damage states including slight, moderate, extensive, and complete damage (collapse) are considered. To evaluate each damage state, inter-story drift ratio and floor acceleration are implemented as engineering demand parameters. Further, to extend the evaluation of the collapse state of the system, a different collapse criterion suggested in FEMA P695 is applied. It is concluded that SBS can significantly increase the collapse capacity and consequently decrease the collapse risk of the structure during its life time. Comparing the observing mean annual frequency (MAF) of exceedance of each damage state against the allowable values presented in performance-based design methods, it is found that using the elastic vertical truss, improves the structural response effectively.

Keywords: IDA, near-fault, probabilistic performance assessment, seismic fragility, strongback system, uncertainty

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Xingyu Peng, Qingyuan Hu, Xuebin Zhu, Xi Yuan

Abstract:

Neutron spectrometry has contributed much to the development of nuclear physics since 1932 and has also become an importance tool in several other fields, notably nuclear technology, fusion plasma diagnostics and radiation protection. Compared with neutron fluxes, neutron spectra can provide more detailed information on the internal physical process of neutron sources, such as fast neutron reactors, fusion plasma, fission-fusion hybrid reactors, and so on. However, high performance neutron spectrometer is not so commonly available as it requires the use of large and complex instrumentation. This work describes the development and characterization of a compact magnetic proton recoil (MPR) spectrometer for high-resolution measurements of fast neutron spectra. The compact MPR spectrometer is featured by its large recoil angle, small size permanent analysis magnet, short beam transport line and dual-purpose detector array for both steady state and pulsed neutron spectra measurement. A 3-dimensional electromagnetic particle transport code is developed to simulate the response function of the spectrometer. Simulation results illustrate that the performance of the spectrometer is mainly determined by n-p recoil foil and proton apertures, and an overall energy resolution of 3% is achieved for 14 MeV neutrons. Dedicated experiments using alpha source and mono-energetic neutron beam are employed to verify the simulated response function of the compact MPR spectrometer. These experimental results show a good agreement with the simulated ones, which indicates that the simulation code possesses good accuracy and reliability. The compact MPR spectrometer described in this work is a valuable tool for fast neutron spectra measurements for the fission or fusion devices.

Keywords: neutron spectrometry, magnetic proton recoil spectrometer, neutron spectra, fast neutron

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Authors: Nino Chomakhashvili, Nino Chikhladze, Nato Pitskhelauri, Maia Bitskhinashvili

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The dental practice is associated with occupational health challenges. Ergonomic risks in the workplace can significantly impair a dentist's work capacity and may even result in the premature end of their career. Implementing ergonomic principles in dental practice aims to prevent work-related musculoskeletal disorders. Many studies have been conducted in various countries such as Sweden, Denmark, Germany, Poland, and Australia to examine the prevalence of musculoskeletal disorders among dentists. However, to the best of authors knowledge there have been no studies on the application of ergonomic principles in dental practice in Georgia. This study focused on evaluating the ergonomic conditions of dental practice in Georgia and determining how common musculoskeletal disorders are among them. The survey was conducted using a random sampling method in selected dental clinics. A tailored questionnaire consisting of 40 questions, created using insights from international practices, was utilized for the study. Two hundred ninety-one filled questionnaires were used for the analysis. Most respondents reported that their workplaces adhered to ergonomic standards. However, 53.6% experienced frequent back pain, with 50.9% suffering from neck pain, 47.9% from shoulder pain, and 47.1% from lower back pain. Many noted that pain had caused them to reduce their working hours. Nearly all respondents expressed a desire to enhance their knowledge about ergonomics and the prevention of occupational diseases. They indicated a preference for participating in continuous professional development programs (61.5%), receiving information through leaflets (12.0%), and attending online webinars (26.6%). Integrating ergonomic principles into the dental practice is crucial for preventing work-related musculoskeletal disorders. It is essential to offer continuous professional development programs and provide information to dentists, via leaflets, thematic online or hybrid webinars.

Keywords: dental practice, ergonomic risks, musculoskeletal disorders, occupational health

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Authors: Intisar Al Busaidi, Rashid Al Maamari, Daowoud Al Mahroqi, Mahvash Karimi

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In recent years, some research studies have been performed on the hybrid application of polymer and low salinity water flooding (LSWF). Numerous technical and economic benefits of low salinity polymer flooding (LSPF) have been reported. However, as with any EOR technology, there are various risks involved in using LSPF. Ions exchange between porous media and brine is one of the Crude oil/ brine/ rocks (COBR) reactions that is identified as a potential risk in LSPF. To the best of our knowledge, this conclusion was drawn based on bulk rheology measurements, and no explanation was provided on how water chemistry changed in the presence of polymer. Therefore, this study aimed to understand rock/ brine interactions with high and low salinity brine in the absence and presence of polymer with Omani reservoir core plugs. Many single-core flooding experiments were performed with low and high salinity polymer solutions to investigate the influence of partially hydrolyzed polyacrylic amide with different brine salinities on cation exchange reactions. Ion chromatography (IC), total organic carbon (TOC), rheological, and pH measurements were conducted for produced aqueous phase. A higher increase in pH and lower polymer adsorption was observed in LSPF compared with conventional polymer flooding. In addition, IC measurements showed that all produced fluids in the absence and presence of polymer showed elevated Ca²⁺, Mg²⁺, K+, Cl- and SO₄²⁻ ions compared to the injected fluids. However, the divalent cations levels, mainly Ca²⁺, were the highest and remained elevated for several pore volumes in the presence of LSP. The results are in line with rheological measurements where the highest viscosity reduction was recorded with the highest level of Ca²⁺ production. Despite the viscosity loss due to cation exchange reactions, LSP can be an attractive alternative to conventional polymer flooding in the Marmul field.

Keywords: polymer, ions, exchange, recovery, low salinity

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Authors: Chang-Jen Lan

Abstract:

Current Level of Service (LOS) index adopted in Highway Capacity Manual (HCM) for signalized intersections on surface streets is based on the intersection average delay. The delay thresholds for defining LOS grades are subjective and is unrelated to critical traffic condition. For example, an intersection delay of 80 sec per vehicle for failing LOS grade F does not necessarily correspond to the intersection capacity. Also, a specific measure of average delay may result from delay minimization, delay equality, or other meaningful optimization criteria. To that end, a reliability version of the intersection critical degree of saturation (v/c) as the LOS index is introduced. Traditionally, the level of saturation at a signalized intersection is defined as the ratio of critical volume sum (per lane) to the average saturation flow (per lane) during all available effective green time within a cycle. The critical sum is the sum of the maximal conflicting movement-pair volumes in northbound-southbound and eastbound/westbound right of ways. In this study, both movement volume and saturation flow are assumed log-normal distributions. Because, when the conditions of central limit theorem obtain, multiplication of the independent, positive random variables tends to result in a log-normal distributed outcome in the limit, the critical degree of saturation is expected to be a log-normal distribution as well. Derivation of the risk index predictive limits is complex due to the maximum and absolute value operators, as well as the ratio of random variables. A fairly accurate functional form for the predictive limit at a user-specified significant level is yielded. The predictive limit is then compared with the designated LOS thresholds for the intersection critical degree of saturation (denoted as X

Keywords: reliability analysis, level of service, intersection critical degree of saturation, risk based index

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Authors: Calvin A. Omolo, Rahul S. Kalhapure, Mahantesh Jadhav, Sanjeev Rambharose, Chunderika Mocktar, Thirumala Govender

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Treatment of infections is compromised by limitations of conventional dosage forms and drug resistance. Nanocarrier system is a strategy to overcome these challenges and improve therapy. Thus, the development of novel materials for drug delivery via nanocarriers is essential. The aim of the study was to synthesize a multi-arm polymer (6-mPEPEA) for enhanced activity of vancomycin (VM) against susceptible and resistant Staphylococcus aureus (MRSA). The synthesis steps of the star polymer followed reported procedures. The synthesized 6-mPEPEA was characterized by FTIR, ¹H and ¹³CNMR and MTT assays. VM loaded micelles were prepared from 6-mPEPEA and characterized for size, polydispersity index (PI) and surface charge (ZP) (Dynamic Light Scattering), morphology by TEM, drug loading (UV Spectrophotometry), drug release (dialysis bag), in vitro and in vivo efficacy against sensitive and resistant S. aureus. 6-mPEPEA was synthesized, and its structure was confirmed. MTT assays confirmed its nontoxic nature with a high cell viability (77%-85%). Unimolecular spherical micelles were prepared. Size, PI, and ZP was 52.48 ± 2.6 nm, 0.103 ± 0.047, -7.3 ± 1.3 mV, respectively and drug loading was 62.24 ± 3.8%. There was a 91% drug release from VCM-6-mPEPEA after 72 hours. In vitro antibacterial test revealed that VM-6-mPEPEA had 8 and 16-fold greater activity against S. aureus and MRSA when compared to bare VM. Further investigations using flow cytometry showed that VM-6-mPEPEA had 99.5% killing rate of MRSA at the MIC concentration. In vivo antibacterial activity revealed that treatment with VM-6-mPEPEA had a 190 and a 15-fold reduction in the MRSA load in untreated and VM treated respectively. These findings confirmed the potential of 6-mPEPEA as a promising bio-degradable nanocarrier for antibiotic delivery to improve treatment of bacterial infections.

Keywords: biosafe, MRSA, nanocarrier, resistance, unimolecular-micelles

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Authors: Anil Koklu, Amin Mansoorifar, Ali Beskok

Abstract:

Dielectric spectroscopy (DS) is a noninvasive, label free technique for a long term real-time measurements of the impedance spectra of biological cells. DS enables characterization of cellular dielectric properties such as membrane capacitance and cytoplasmic conductivity. We have developed a lab-on-a-chip device that uses an electro-activated microwells array for loading, DS measurements, and unloading of biological cells. We utilized from dielectrophoresis (DEP) to capture target cells inside the wells and release them after DS measurement. DEP is a label-free technique that exploits differences among dielectric properties of the particles. In detail, DEP is the motion of polarizable particles suspended in an ionic solution and subjected to a spatially non-uniform external electric field. To the best of our knowledge, this is the first microfluidic chip that combines DEP and DS to analyze biological cells using electro-activated wells. Device performance is tested using two different cell lines of prostate cancer cells (RV122, PC-3). Impedance measurements were conducted at 0.2 V in the 10 kHz to 40 MHz range with 6 s time resolution. An equivalent circuit model was developed to extract the cell membrane capacitance and cell cytoplasmic conductivity from the impedance spectra. We report the time course of the variations in dielectric properties of PC-3 and RV122 cells suspended in low conductivity medium (LCB), which enhances dielectrophoretic and impedance responses, and their response to sudden pH change from a pH of 7.3 to a pH of 5.8. It is shown that microfluidic chip allowed online measurements of dielectric properties of prostate cancer cells and the assessment of the cellular level variations under external stimuli such as different buffer conductivity and pH. Based on these data, we intend to deploy the current device for single cell measurements by fabricating separately addressable N × N electrode platforms. Such a device will allow time-dependent dielectric response measurements for individual cells with the ability of selectively releasing them using negative-DEP and pressure driven flow.

Keywords: microfluidic, microfabrication, lab on a chip, AC electrokinetics, dielectric spectroscopy

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Authors: Ravi Verma

Abstract:

Cryosorption pump is the best solution to achieve clean, vibration free ultra-high vacuum. Furthermore, the operation of cryosorption pump is free from the influence of electric and magnetic fields. Due to these attributes, this pump is used in the space simulation chamber to create the ultra-high vacuum. The cryosorption pump comprises of three parts (a) panel which is cooled with the help of cryogen or cryocooler, (b) an adsorbent which is used to adsorb the gas molecules, (c) an epoxy which holds the adsorbent and the panel together thereby aiding in heat transfer from adsorbent to the panel. The performance of cryosorption pump depends on the temperature of the adsorbent and hence, on the thermal conductivity of the epoxy. Therefore we have made an attempt to increase the thermal conductivity of epoxy adhesive by mixing nano-sized graphene filler particles. The thermal conductivity of epoxy-graphene composite adhesive is measured with the help of indigenously developed experimental setup in the temperature range from 4.5 K to 7 K, which is generally the operating temperature range of cryosorption pump for efficiently pumping of hydrogen and helium gas. In this article, we have presented the experimental results of epoxy-graphene composite adhesive in the temperature range from 4.5 K to 7 K. We have also proposed an analytical heat conduction model to find the thermal conductivity of the composite. In this case, the filler particles, such as graphene, are randomly distributed in a base matrix of epoxy. The developed model considers the complete spatial random distribution of filler particles and this distribution is explained by Binomial distribution. The results obtained by the model have been compared with the experimental results as well as with the other established models. The developed model is able to predict the thermal conductivity in both isotropic regions as well as in anisotropic region over the required temperature range from 4.5 K to 7 K. Due to the non-empirical nature of the proposed model, it will be useful for the prediction of other properties of composite materials involving the filler in a base matrix. The present studies will aid in the understanding of low temperature heat transfer which in turn will be useful towards the development of high performance cryosorption pump.

Keywords: composite adhesive, computational modelling, cryosorption pump, thermal conductivity

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Authors: Keerthi Katam, Abhinav B. Tirunaghari, Vinod Vadithya, Toshiyuki Shimizu, Satoshi Soda, Debraj Bhattacharyya

Abstract:

Researchers worldwide are increasingly focusing on the removal of carbon and nutrient from wastewater using algal-bacterial hybrid systems. Algae produce oxygen during photosynthesis, which is taken up by heterotrophic bacteria for mineralizing organic carbon to carbon dioxide. This phenomenon reduces the net mechanical aeration requirement of aerobic biological wastewater treatment processes. Consequently, the treatment cost is also reduced. Microalgae also participate in the treatment process by taking up nutrient (N, P) from wastewater. Algal biomass, if harvested, can generate value-added by-products. The aim of the present study was to compare the performance of two systems - System A (mixed microalgae and bacteria) and System B (diatoms and bacteria) in treating kitchen wastewater (KWW). The test reactors were operated at five different solid retention times (SRTs) -2, 4, 6, 8, and 10-days in draw-and-fill mode. The KWW was collected daily from the dining hall-kitchen area of the Indian Institute of Technology Hyderabad. The influent and effluent samples were analyzed for total organic carbon (TOC), total nitrogen (TN) using TOC-L analyzer. A colorimetric method was used to analyze anionic surfactant. Phosphorus (P) and chlorophyll were measured by following standard methods. The TOC, TN, and P of KWW were in the range of 113.5 to 740 mg/L, 2 to 22.8 mg/L, and 1 to 4.5 mg/L, respectively. Both the systems gave similar results with 85% of TOC removal and 60% of TN removal at 10-d SRT. However, the anionic surfactant removal in System A was 99% and 60% in System B. The chlorophyll concentration increased with an increase in SRT in both the systems. At 2-d SRT, no chlorophyll was observed in System B, whereas 0.5 mg/L was observed in System A. At 10-d SRT, the chlorophyll concentration in System A was 7.5 mg/L, whereas it was 4.5 mg/L in System B. Although both the systems showed similar performance in treatment, the increase in chlorophyll concentration suggests that System A demonstrated a better algal-bacterial symbiotic relationship in treating KWW than System B.

Keywords: diatoms, microalgae, retention time, wastewater treatment

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Authors: Arun Prasad, Abhishek Tiwari, Rekha Jaiswal, Vivek Chaudhary

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Background: Robotic Roux en Y gastric bypass is being done for some time but is technically difficult, requiring operating in both the sub diaphragmatic and infracolic compartments of the abdomen. This can mean a dual docking of the robot or a hybrid partial laparoscopic and partial robotic surgery. The Mini /One anastomosis /omega loop gastric bypass (MGB) has the advantage of having all dissection and anastomosis in the supracolic compartment and is therefore suitable technically for robotic surgery. Methods: We have done 208 robotic mini gastric bypass surgeries. The robot is docked above the head of the patient in the midline. Camera port is placed supra umbilically. Two ports are placed on the left side of the patient and one port on the right side of the patient. An assistant port is placed between the camera port and right sided robotic port for use of stapler. Distal stomach is stapled from the lesser curve followed by a vertical sleeve upwards leading to a long sleeve pouch. Jejunum is taken at 200 cm from the duodenojejunal junction and brought up to do a side to side gastrojejunostomy. Results: All patients had a successful robotic procedure. Mean time taken was 85 minutes. There were major intraoperative or post operative complications. No patient needed conversion or re-explorative surgery. Mean excess weight loss over a period of 2 year was about 75%. There was no mortality. Patient satisfaction score was high and was attributed to the good weight loss and minimal dietary modifications that were needed after the procedure. Long term side effects were anemia and bile reflux in a small number of patients. Conclusions: MGB / OAGB is gaining worldwide interest as a short simple procedure that has been shown to very effective and safe bariatric surgery. The purpose of this study was to report on the safety and efficacy of robotic surgery for this procedure. This is the first report of totally robotic mini gastric bypass.

Keywords: MGB, mini gastric bypass, OAGB, robotic bariatric surgery

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Authors: Tania Tzong, Chao-Yi Teng, Tzong-Yuan Wu

Abstract:

Currently, Chikungunya virus (CHIKV) transmitted to humans by Aedes mosquitoes has distributed from Africa to Southeast Asia, South America, and South Europe. However, little is known about the antigenic targets for immunity, and there are no licensed vaccines or specific antiviral treatments for the disease caused by CHIKV. Baculovirus has been recognized as a novel vaccine vector with attractive characteristic features of an optional vaccine delivery vehicle. This approach provides the safety and efficacy of CHIKV vaccine. In this study, bi-cistronic recombinant baculoviruses vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP were produced. Both recombinant baculovirus can express EGFP reporter gene in insect cells to facilitate the recombinant virus isolation and purification. Examination of vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP showed that this recombinant baculovirus could induce syncytium formation in insect cells. Unexpectedly, the immunofluorescence assay revealed the expression of E1 and E2 of CHIKV structural proteins in insect cells infected by vAc-CMV-CHIKV26S-Rhir-EGFP. This result may imply that the CMV promoter can induce the transcription of CHIKV26S in insect cells. There are also E1 and E2 expression in mammalian cells transduced by vAc-CMV-CHIKV26S-Rhir-EGFP and vAc-CMV-pH-CHIKV26S-Lir-EGFP. The expression of E1 and E2 proteins of insect and mammalian cells was validated again by Western blot analysis. The vector construction with dual tandem promoters, which is polyhedrin and CMV promoter, has higher expression of the E1 and E2 of CHIKV structural proteins than the vector construction with CMV promoter only. Most of the E1 and E2 proteins expressed in mammalian cells were glycosylated. In the future, the expression of structural proteins of CHIKV in mammalian cells is expected can form virus-like particle, so it could be used as a vaccine for chikungunya virus.

Keywords: chikungunya virus, virus-like particle, vaccines, baculovirus expression vector system

Procedia PDF Downloads 423