Search results for: mathematical biology

Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Shaolin Allen Liao, Hual-Te Chien

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Various THz phase extraction algorithms have been developed for a novel THz Modulating Interferometric Doppler Radar (THz-MIDR) developed recently by the author. The THz-MIDR differs from the well-known FTIR technique in that it introduces a continuously modulating reference branch, compared to the time-consuming discrete FTIR stepping reference branch. Such change allows real-time tracking of a moving object and capturing of its Doppler signature. The working principle of the THz-MIDR is similar to the FTIR technique: the incoming THz emission from the scene is split by a beam splitter/combiner; one of the beams is continuously modulated by a vibrating mirror or phase modulator and the other split beam is reflected by a reflection mirror; finally both the modulated reference beam and reflected beam are combined by the same beam splitter/combiner and detected by a THz intensity detector (for example, a pyroelectric detector). In order to extract THz phase from the single intensity measurement signal, we have derived rigorous mathematical formulas for 3 Frequency Banded (FB) signals: 1) DC Low-Frequency Banded (LFB) signal; 2) Fundamental Frequency Banded (FFB) signal; and 3) Harmonic Frequency Banded (HFB) signal. The THz phase extraction algorithms are then developed based combinations of 2 or all of these 3 FB signals with efficient algorithms such as Levenberg-Marquardt nonlinear fitting algorithm. Numerical simulation has also been performed in Matlab with simulated THz-MIDR interferometric signal of various Signal to Noise Ratio (SNR) to verify the algorithms.

Keywords: algorithm, modulation, THz phase, THz interferometry doppler radar

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Authors: Joao Garretto, R. J. Yarwood, Vamsi Borra, Frank Li

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Bluetooth Low Energy (BLE) has emerged as one of the main wireless communication technologies used in low-power electronics, such as wearables, beacons, and Internet of Things (IoT) devices. BLE’s energy efficiency characteristic, smart mobiles interoperability, and Over the Air (OTA) capabilities are essential features for ultralow-power devices, which are usually designed with size and cost constraints. Most current research regarding the power analysis of BLE devices focuses on the theoretical aspects of the advertising and scanning cycles, with most results being presented in the form of mathematical models and computer software simulations. Such computer modeling and simulations are important for the comprehension of the technology, but hardware measurement is essential for the understanding of how BLE devices behave in real operation. In addition, recent literature focuses mostly on the BLE technology, leaving possible applications and its analysis out of scope. In this paper, a coin cell battery-powered BLE Data Acquisition Device, with a 4-in-1 sensor and one accelerometer, is proposed and evaluated with respect to its Power Consumption. First, evaluations of the device in advertising mode with the sensors turned off completely, followed by the power analysis when each of the sensors is individually turned on and data is being transmitted, and concluding with the power consumption evaluation when both sensors are on and respectively broadcasting the data to a mobile phone. The results presented in this paper are real-time measurements of the electrical current consumption of the BLE device, where the energy levels that are demonstrated are matched to the BLE behavior and sensor activity.

Keywords: bluetooth low energy, power analysis, BLE advertising cycle, wireless sensor node

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Authors: Anne Bubriski

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Despite improvements in gender inequalities, women and girls continue to face glass ceilings, underrepresentation, and harmful stereotypes that can limit their aspirations and opportunities in STEM. While girls are taking similar high school math and science classes, boys are more likely to take physics and six times more likely to take an engineering course. The gap becomes even larger for minority or low-income girls. This gender gap is not due to biology; rather, it is due to cultural, social, and institutional forces. As girls get older, these forces often ‘teach’ them ‘STEM is more for boys’. The STEM gender gap widens in college, with only 20% of engineering degrees being awarded to women, and by the time women enter the workforce, they only occupy about 13% of engineering jobs. At the University of Central Florida, the Women’s and Gender Studies Program has developed a unique mentoring program to address these issues, Science Leadership and Mentoring (SLAM). What is unique about the approach of SLAM is that we look to address this problem through leadership and STEM. We look to help girls make connections between leadership and STEM—that young women can be leaders as scientists and that scientists are leaders making a change. This is particularly needed and relevant to our community because while there are mentoring programs to our knowledge, SLAM is one of the only, if not only, mentoring programs pairing college women and 7th-grade girls that includes a focus both on STEM and leadership in the United States. SLAM is a curriculum-based mentoring program pairing one 7th-grade girl with one UCF undergraduate STEM major. SLAM empowers young women to be assertive, brave, confident, independent, inquisitive and proud leaders in STEM. SLAM seeks to promote young women’s inspiration and excitement into STEM fields and careers while also building leadership abilities such as problem-solving, teamwork and cooperation, cultural identity and ethnic pride, advocacy for positive change, and goals for the future. SLAM serves about fifteen 7th-grade girls for the academic year and about 20 UCF students. SLAM holds weekly mentoring meetings lasting about 90 minutes, covering topics on leadership, STEM majors and careers, and STEM leadership. This past year, SLAM received a Community Action Grant from the American Association of University Women (AAUW) to run a sub-program, SLAM-Space. SLAM-Space focused on exposing SLAM participants to aerospace engineering and other space-related STEM fields, such as physics and astronomy, through guest speakers, workshops and field trips, including the Kenndy Space Center. The proposed paper presentation will present an overview of SLAM-Space and the data findings from pre and post-surveys, in-depth interviews and focus groups from the SLAM participants' experiences in the program.

Keywords: gender, leadership, STEM, empowerment

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Authors: Nadish Anand, Richard D. Gould

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A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: numerical simulation, immiscible, finite difference, IADI, IDE, waterflooding

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Authors: Meenu Kaushik, Ayon K. Bandhoyadhayay, Lalit M. Joshi

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Inductive output tubes (IOTs) are widely used as microwave power amplifiers for broadcast and scientific applications. It is capable of amplifying radio frequency (RF) power with very good efficiency. Its compactness, reliability, high efficiency, high linearity and low operating cost make this device suitable for various applications. The device consists of an integrated structure of electron gun and RF cavity, collector and focusing structure. The working principle of IOT is a combination of triode and klystron. The cathode lies in the electron gun produces a stream of electrons. A control grid is placed in close proximity to the cathode. Basically, the input part of IOT is the integrated structure of gridded electron gun which acts as an input cavity thereby providing the interaction gap where the input RF signal is applied to make it interact with the produced electron beam for supporting the amplification phenomena. The paper presents the design, fabrication and testing of a radial re-entrant cavity for implementing in the input structure of IOT at 350 MHz operating frequency. The model’s suitability has been discussed and a generalized mathematical relation has been introduced for getting the proper transverse magnetic (TM) resonating mode in the radial narrow gap RF cavities. The structural modeling has been carried out in CST and SUPERFISH codes. The cavity is fabricated with the Aluminum material and the RF characterization is done using vector network analyzer (VNA) and the results are presented for the resonant frequency peaks obtained in VNA.

Keywords: inductive output tubes, IOT, radial cavity, coaxial cavity, particle accelerators

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Authors: A. Gopala Krishna, M. Lakshmi Chaitanya, V. Kalyana Manohar

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In the existent analysis, laser micro machining (LMM) of Silicon carbide (SiCp) reinforced Aluminum 7075 Metal Matrix Composite (Al7075/SiCp MMC) was studied. While machining, Because of the intense heat generated, A layer gets formed on the work piece surface which is called recast layer and this layer is detrimental to the surface quality of the component. The recast layer needs to be as small as possible for precise applications. Therefore, The height of recast layer and the depth of groove which are conflicting in nature were considered as the significant manufacturing criteria, Which determines the pursuit of a machining process obtained in LMM of Al7075/10%SiCp composite. The present work formulates the depth of groove and height of recast layer in relation to the machining parameters using the Response Surface Methodology (RSM) and correspondingly, The formulated mathematical models were put to use for optimization. Since the effect of machining parameters on the depth of groove and height of recast layer was contradictory, The problem was explicated as a multi objective optimization problem. Moreover, An evolutionary Non-dominated sorting genetic algorithm (NSGA-II) was employed to optimize the model established by RSM. Subsequently this algorithm was also adapted to achieve the Pareto optimal set of solutions that provide a detailed illustration for making the optimal solutions. Eventually experiments were conducted to affirm the results obtained from RSM and NSGA-II.

Keywords: Laser Micro Machining (LMM), depth of groove, Height of recast layer, Response Surface Methodology (RSM), non-dominated sorting genetic algorithm

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Authors: Afshin Keshvadi, Johari Endan, Haniff Harun, Desa Ahmad, Farah Saleena

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Experiments were conducted to develop a model for analyzing the ripening process of oil palm fresh fruits in relation to oil yield and oil quality of palm oil produced. This research was carried out on 8-year-old Tenera (Dura × Pisifera) palms planted in 2003 at the Malaysian Palm Oil Board Research Station. Fresh fruit bunches were harvested from designated palms during January till May of 2010. The bunches were divided into three regions (top, middle and bottom), and fruits from the outer and inner layers were randomly sampled for analysis at 8, 12, 16 and 20 weeks after anthesis to establish relationships between maturity and oil development in the mesocarp and kernel. Computations on data related to ripening time, oil content and oil quality were performed using several computer software programs (MSTAT-C, SAS and Microsoft Excel). Nine nonlinear mathematical models were utilized using MATLAB software to fit the data collected. The results showed mean mesocarp oil percent increased from 1.24 % at 8 weeks after anthesis to 29.6 % at 20 weeks after anthesis. Fruits from the top part of the bunch had the highest mesocarp oil content of 10.09 %. The lowest kernel oil percent of 0.03 % was recorded at 12 weeks after anthesis. Palmitic acid and oleic acid comprised of more than 73 % of total mesocarp fatty acids at 8 weeks after anthesis, and increased to more than 80 % at fruit maturity at 20 weeks. The Logistic model with the highest R2 and the lowest root mean square error was found to be the best fit model.

Keywords: oil palm, oil yield, ripening process, anthesis, fatty acids, modeling

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Authors: Yarhands Dissou Arthur, Samuel Asiedu Addo, Jonathan Annan

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Interest in subject specific is very essential in the quest to ensure effective teaching and learning. In building interest in subject specific areas requires certain factors and strategies well-spelled out.The factors such as the gender of the student, the type of basic school attended, the parent interest as well as the scare of the basic school mathematics teacher is very important to consider. The relational effect and the contribution these above mentioned variables on student have not been fully investigated and this paper address the effect of these factors on the student interest. In the attainment of this goal, the current paper addresses the effect of parent interest, the type of basic school attended, the scare by basic school mathematics teacher and its effect on student’s interest in mathematics. A cross sectional data collected from two hundred and sixty post-secondary school student were analyzed using descriptive and inferential statistical methods by aid of SPSS version 16. The study found that parent interest and value for mathematics significantly influenced students interest and joy in solving mathematical problems. Moreover, we also observed that the fear imposed by basic school mathematics teachers was found to significantly influence students’ interest. The study further found that the type of basic school attended and gender are factors that do not influence students’ interest in mathematics. In addition to concluding that a student’s interest is influenced by both parent interest and the fear of basic school mathematics teacher, the study also showed that the type of basic school attended and gender does not affect the students’ interest in mathematics.

Keywords: gender, mathematics interest, teacher interest, teacher interest, student interest

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Authors: Eko Adhi Setiawan, Duli Asih Siregar, Aiman Setiawan

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Solar energy is abundant in nature, particularly in the tropics which have peak sun hour that can reach 8 hours per day. In the fabrication process, Photovoltaic’s (PV) performance are tested in standard test conditions (STC). It specifies a module temperature of 25°C, an irradiance of 1000 W/ m² with an air mass 1.5 (AM1.5) spectrum and zero wind speed. Thus, the results of the performance testing of PV at STC conditions cannot fully represent the performance of PV in the tropics. For example Indonesia, which has a temperature of 20-40°C. In this paper, the effect of temperature on the choice of the 5 kW AC inverter topology on the PV system such as the Central Inverter, String Inverter and AC-Module specifically for the tropics will be discussed. The proper inverter topology can be determined by analysis of the effect of temperature and irradiation on the PV panel. The effect of temperature and irradiation will be represented in the characteristics of I-V and P-V curves. PV’s characteristics on high temperature would be analyzed using Solar panel modeling through MATLAB Simulink based on mathematical equations that form Solar panel’s characteristic curve. Based on PV simulation, it is known then that temperature coefficients of short circuit current (ISC), open circuit voltage (VOC), and maximum output power (PMAX) consecutively as high as 0.56%/oC, -0.31%/oC and -0.4%/oC. Those coefficients can be used to calculate PV’s electrical parameters such as ISC, VOC, and PMAX in certain earth’s surface’s certain point. Then, from the parameters, the utility of the 5 kW AC inverter system can be determined. As the result, for tropical area, string inverter topology has the highest utility rates with 98, 80 %. On the other hand, central inverter and AC-Module Topology has utility rates of 92.69 % and 87.7 % eventually.

Keywords: Photovoltaic, PV-Inverter Configuration, PV Modeling, Solar Panel Characteristics.

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Authors: Leyla Noroozbabaee, David Nickerson

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We introduce a modular, consistent, reusable bond graph model of the renal nephron’s proximal convoluted tubule (PCT), which can reproduce biological behaviour. In this work, we focus on ion and volume transport in the proximal convoluted tubule of the renal nephron. Modelling complex systems requires complex modelling problems to be broken down into manageable pieces. This can be enabled by developing models of subsystems that are subsequently coupled hierarchically. Because they are based on a graph structure. In the current work, we define two modular subsystems: the resistive module representing the membrane and the capacitive module representing solution compartments. Each module is analyzed based on thermodynamic processes, and all the subsystems are reintegrated into circuit theory in network thermodynamics. The epithelial transport system we introduce in the current study consists of five transport membranes and four solution compartments. Coupled dissipations in the system occur in the membrane subsystems and coupled free-energy increasing, or decreasing processes appear in solution compartment subsystems. These structural subsystems also consist of elementary thermodynamic processes: dissipations, free-energy change, and power conversions. We provide free and open access to the Python implementation to ensure our model is accessible, enabling the reader to explore the model through setting their simulations and reproducibility tests.

Keywords: Bond Graph, Epithelial Transport, Water Transport, Mathematical Modeling

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Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Lian Yang

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Object-oriented programming (OOP) is the dominant programming paradigm in today’s software industry and it has literally enabled average software developers to develop millions of commercial strength software applications in the era of INTERNET revolution over the past three decades. On the other hand, the lack of strict mathematical model and domain constraint features at the language level has long perplexed the computer science academia and OOP engineering community. This situation resulted in inconsistent system qualities and hard-to-understand designs in some OOP projects. The difficulties with regards to fix the current situation are also well known. Although the power of OOP lies in its unbridled flexibility and enormously rich data modeling capability, we argue that the ambiguity and the implicit facade surrounding the conceptual model of a class and an object should be eliminated as much as possible. We listed the five major usage of class and propose to separate them by proposing new language constructs. By using well-established theories of set and FSM, we propose to apply certain simple, generic, and yet effective constraints at OOP language level in an attempt to find a possible solution to the above-mentioned issues regarding OOP. The goal is to make OOP more theoretically sound as well as to aid programmers uncover warning signs of irregularities and domain-specific issues in applications early on the development stage and catch semantic mistakes at runtime, improving correctness verifiability of software programs. On the other hand, the aim of this paper is more practical than theoretical.

Keywords: new language constructs, set theory, FSM theory, user defined value type, function groups, membership qualification attribute (MQA), check-constraint (CC)

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

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Authors: Nihan Nugay, Nur Cicek Kekec, Kalman Toth, Turgut Nugay, Joseph P. Kennedy

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In recent years, polyurethane structures are paving the way for elastomer usage in biology, human medicine, and biomedical application areas. Polyurethanes having a combination of high oxidative and hydrolytic stability and excellent mechanical properties are focused due to enhancing the usage of PUs especially for implantable medical device application such as cardiac-assist. Currently, unique polyurethanes consisting of polyisobutylenes as soft segments and conventional hard segments, named as PIB-based PUs, are developed with precise NCO/OH stoichiometry (∽1.05) for obtaining PIB-based PUs with enhanced properties (i.e., tensile stress increased from ∽11 to ∽26 MPa and elongation from ∽350 to ∽500%). Static and dynamic mechanical properties were optimized by examining stress-strain graphs, self-organization and crystallinity (XRD) traces, rheological (DMA, creep) profiles and thermal (TGA, DSC) responses. Annealing procedure was applied for PIB-based PUs. Annealed PIB-based PU shows ∽26 MPa tensile strength, ∽500% elongation, and ∽77 Microshore hardness with excellent hydrolytic and oxidative stability. The surface characters of them were examined with AFM and contact angle measurements. Annealed PIB-based PU exhibits the higher segregation of individual segments and surface hydrophobicity thus annealing significantly enhances hydrolytic and oxidative stability by shielding carbamate bonds by inert PIB chains. According to improved surface and microstructure characters, greater efforts are focused on analyzing protein adsorption and calcification profiles. In biomedical applications especially for cardiological implantations, protein adsorption inclination on polymeric heart valves is undesirable hence protein adsorption from blood serum is followed by platelet adhesion and subsequent thrombus formation. The protein adsorption character of PIB-based PU examines by applying Bradford assay in fibrinogen and bovine serum albumin solutions. Like protein adsorption, calcium deposition on heart valves is very harmful because vascular calcification has been proposed activation of osteogenic mechanism in the vascular wall, loss of inhibitory factors, enhance bone turnover and irregularities in mineral metabolism. The calcium deposition on films are characterized by incubating samples in simulated body fluid solution and examining SEM images and XPS profiles. PIB-based PUs are significantly more resistant to hydrolytic-oxidative degradation, protein adsorption and calcium deposition than ElastEonTM E2A, a commercially available PDMS-based PU, widely used for biomedical applications.

Keywords: biomedical application, calcification, polyisobutylene, polyurethane, protein adsorption

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Authors: Omar Alzeley, Sergey Utev

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Minimizing a constrained multivariate function is the fundamental of Machine learning, and these algorithms are at the core of data mining and data visualization techniques. The decision function that maps input points to output points is based on the result of optimization. This optimization is the central of learning theory. One approach to complex systems where the dynamics of the system is inferred by a statistical analysis of the fluctuations in time of some associated observable is time series analysis. The purpose of this paper is a mathematical transition from the autoregressive model of classical time series to the matrix formalization of quantum theory. Firstly, we have proposed a quantum time series model (QTS). Although Hamiltonian technique becomes an established tool to detect a deterministic chaos, other approaches emerge. The quantum probabilistic technique is used to motivate the construction of our QTS model. The QTS model resembles the quantum dynamic model which was applied to financial data. Secondly, various statistical methods, including machine learning algorithms such as the Kalman filter algorithm, are applied to estimate and analyses the unknown parameters of the model. Finally, simulation techniques such as Markov chain Monte Carlo have been used to support our investigations. The proposed model has been examined by using real and simulated data. We establish the relation between quantum statistical machine and quantum time series via random matrix theory. It is interesting to note that the primary focus of the application of QTS in the field of quantum chaos was to find a model that explain chaotic behaviour. Maybe this model will reveal another insight into quantum chaos.

Keywords: machine learning, simulation techniques, quantum probability, tensor product, time series

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Authors: Zeinab Haji Abolhasani, Romeo Marian, Lee Luong

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This paper and its companions (Part II, Part III) will concentrate on optimizing a class of supply chain problems known as Multi- Commodities Consumer Supply Chain (MCCSC) problem. MCCSC problem belongs to production-distribution (P-D) planning category. It aims to determine facilities location, consumers’ allocation, and facilities configuration to minimize total cost (CT) of the entire network. These facilities can be manufacturer units (MUs), distribution centres (DCs), and retailers/end-users (REs) but not limited to them. To address this problem, three major tasks should be undertaken. At the first place, a mixed integer non-linear programming (MINP) mathematical model is developed. Then, system’s behaviors under different conditions will be observed using a simulation modeling tool. Finally, the most optimum solution (minimum CT) of the system will be obtained using a multi-objective optimization technique. Due to the large size of the problem, and the uncertainties in finding the most optimum solution, integration of modeling and simulation methodologies is proposed followed by developing new approach known as GASG. It is a genetic algorithm on the basis of granular simulation which is the subject of the methodology of this research. In part II, MCCSC is simulated using discrete-event simulation (DES) device within an integrated environment of SimEvents and Simulink of MATLAB® software package followed by a comprehensive case study to examine the given strategy. Also, the effect of genetic operators on the obtained optimal/near optimal solution by the simulation model will be discussed in part III.

Keywords: supply chain, genetic algorithm, optimization, simulation, discrete event system

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Authors: Sharmeen Rahman, Daniel Schmidt, Jane Hughes

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Paratya australiensis Kemp (Decapoda: Atyidae) is a widely distributed indigenous freshwater shrimp, highly abundant in eastern Australia. This species has been considered as a model stream organism to study genetics, dispersal, biology, behaviour and evolution in Atyids. Paratya has a filter feeding and scavenging habit which plays a significant role in the formation of lotic community structure. It has been shown to reduce periphyton and sediment from hard substrates of coastal streams and hence acts as a strongly-interacting ecosystem macroconsumer. Besides, Paratya is one of the major food sources for stream dwelling fishes. Paratya australiensis is a cryptic species complex consisting of 9 highly divergent mitochondrial DNA lineages. Among them, one lineage has been observed to favour upstream sites at higher altitudes, with cooler water temperatures. This study aims to identify local adaptation in upstream and downstream populations of this lineage in three streams in the Conondale Range, North-eastern Brisbane, Queensland, Australia. Two populations (up and down stream) from each stream have been chosen to test for local adaptation, and a parallel pattern of adaptation is expected across all streams. Six populations each consisting of 24 individuals were sequenced using the Restriction Site Associated DNA-seq (RAD-seq) technique. Genetic markers (SNPs) were developed using double digest RAD sequencing (ddRAD-seq). These were used for de novo assembly of Paratya genome. De novo assembly was done using the STACKs program and produced 56, 344 loci for 47 individuals from one stream. Among these individuals, 39 individuals shared 5819 loci, and these markers are being used to test for local adaptation using Fst outlier tests (Arlequin) and Bayesian analysis (BayeScan) between up and downstream populations. Fst outlier test detected 27 loci likely to be under selection and the Bayesian analysis also detected 27 loci as under selection. Among these 27 loci, 3 loci showed evidence of selection at a significance level using BayeScan program. On the other hand, up and downstream populations are strongly diverged at neutral loci with a Fst =0.37. Similar analysis will be done with all six populations to determine if there is a parallel pattern of adaptation across all streams. Furthermore, multi-locus among population covariance analysis will be done to identify potential markers under selection as well as to compare single locus versus multi-locus approaches for detecting local adaptation. Adaptive genes identified in this study can be used for future studies to design primers and test for adaptation in related crustacean species.

Keywords: Paratya australiensis, rainforest streams, selection, single nucleotide polymorphism (SNPs)

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Authors: Zohreh Mohammadi, Jan Kaspar, Peter Lohmander, Robert Marusak, Harald Vacik, Ljusk Ola Eriksson

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Storms are important damaging agents in European forest ecosystems. In the latest decades, significant economic losses in European forestry occurred due to storms. This study investigates the problem of optimal harvest planning when forest stands risk to be felled by storms. One of the most applicable mathematical methods which are being used to optimize forest management is stochastic dynamic programming (SDP). This method belongs to the adaptive optimization class. Sequential decisions, such as harvest decisions, can be optimized based on sequential information about events that cannot be perfectly predicted, such as the future storms and the future states of wind protection from other forest stands. In this paper, stochastic dynamic programming is used to maximize the expected present value of the profits from an area consisting of several forest stands. The region of analysis is the Czech Republic. The harvest decisions, in a particular time period, should be simultaneously taken in all neighbor stands. The reason is that different stands protect each other from possible winds. The optimal harvest age of a particular stand is a function of wind speed and different wind protection effects. The optimal harvest age often decreases with wind speed, but it cannot be determined for one stand at a time. When we consider a particular stand, this stand also protects other stands. Furthermore, the particular stand is protected by neighbor stands. In some forest stands, it may even be rational to increase the harvest age under the influence of stronger winds, in order to protect more valuable stands in the neighborhood. It is important to integrate wind risk in forestry decision-making.

Keywords: Czech republic, forest stands, stochastic dynamic programming, wind risk

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Authors: Andre F. A. Cyrino

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Knowing that the technological advance is the focus on the efficient extraction of energy from wind, and therefore in the design of wind turbine structures, this work aims the study of the fluid-structure interaction of an idealized wind turbine. The blade was studied as a beam attached to a cylindrical Hub with rotation axis pointing the air flow that passes through the rotor. Using the calculus of variations and the finite difference method the blade will be simulated by a discrete number of nodes and the aerodynamic forces were evaluated. The study presented here was written on Matlab and performs a numeric simulation of a simplified model of windmill containing a Hub and three blades modeled as Euler-Bernoulli beams for small strains and under the constant and uniform wind. The mathematical approach is done by Hamilton’s Extended Principle with the aerodynamic loads applied on the nodes considering the local relative wind speed, angle of attack and aerodynamic lift and drag coefficients. Due to the wide range of angles of attack, a wind turbine blade operates, the airfoil used on the model was NREL SERI S809 which allowed obtaining equations for Cl and Cd as functions of the angle of attack, based on a NASA study. Tridimensional flow effects were no taken in part, as well as torsion of the beam, which only bends. The results showed the dynamic response of the system in terms of displacement and rotational speed as the turbine reached the final speed. Although the results were not compared to real windmills or more complete models, the resulting values were consistent with the size of the system and wind speed.

Keywords: blade aerodynamics, fluid–structure interaction, wind turbine aerodynamics, wind turbine blade

Procedia PDF Downloads 244

Authors: Tien-Ching Yao, Ching-Ching Lu

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Understanding human language processing is one of the main challenges of current cognitive neuroscience. The aims of the present study were to use a sentence decision task combined with event-related potentials to investigate the psychological reality of "cross-sentence patterns." Therefore, we take the math word problems the experimental materials and use the ERPs' P600 component to verify. In this study, the experimental material consisted of 200 math word problems with three different conditions were used ( multiplication word problems、division word problems type 1、division word problems type 2 ). Eighteen Mandarin native speakers participated in the ERPs study (14 of whom were female). The result of the grand average waveforms suggests a later posterior positivity at around 500ms - 900ms. These findings were tested statistically using repeated measures ANOVAs at the component caused by the stimulus type of different questions. Results suggest that three conditions present significant (P < 0.05) on the Mean Amplitude, Latency, and Peak Amplitude. The result showed the characteristic timing and posterior scalp distribution of a P600 effect. We interpreted these characteristic responses as the psychological reality of "cross-sentence patterns." These results provide insights into the sentence processing issues in linguistic theory and psycholinguistic models of language processing and advance our understanding of how people make sense of information during language comprehension.

Keywords: language processing, sentence comprehension, event-related potentials, cross-sentence patterns

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Authors: Ntalamagka N., Sanchis-Benlloch P. J., Mayoral-Serrano R., Tena-Medialdea J., García-March J. R.

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The pen shell Pinna nobilis population has declined dramatically since 2016 due to die-off events observed in the whole extent of the Mediterranean Sea associated with the protozoan Haplosporidium pinnae. As of 2019, it is considered a critically endangered species. Due to its ecological importance and its endangered status, several initiatives have been developed for its salvation and recovery. This research is an effort to understand and control its reproduction under captivity. As a limited number of Pinna nobilis individuals could be used for experimentation, the possibility of using the Pinna rudis as a model animal was explored. The molecular mechanism that regulates the reproduction of both species is unknown; consequently, transcriptomic analysis was performed to identify neuropeptides that are expressed in the key regulatory tissues of the visceral ganglia and gonads of both species. Neuropeptides form an important group of signaling peptides that regulate reproductive, behavioral and physiological functions in molluscs. In total, 17 neuropeptide precursors were identified in P. nobilis and 14 in P. rudis transcriptomes; 14 of them were identical in both species. This affinity verified the genetic similarity of these species at the reproduction level. APGWamide, buccalin, ELH and GnRH were tested in P. rudis and demonstrated their capacity to advance gonadal maturation and trigger spawning while spawning was recorded in P. nobilis after the usage of APGWamide and buccalin. The neuropeptides were administered using intramuscular injection and cholesterol implants following relative literature as well as a new method was developed for external administration without the use of anesthesia using a mathematical model. The know-how of this research will not only lead to the survival of the species but also will narrow the horizons of broodstock conditioning of other similar species.

Keywords: neuropeptides, Pinna nobilis, reproduction, transcriptomics

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Authors: K. G. R. M. Jayathilake, S. Rudra

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Wood degradation in hot compressed water is modeled with a Computational Fluid Dynamics (CFD) code using cellulose, xylan, and lignin as model compounds. Model compounds are reacted under catalyst-free conditions in a temperature range from 250 to 370 °C. Using a simplified reaction scheme where water soluble products, methanol soluble products, char like compounds and gas are generated through intermediates with each model compound. A modified multistage shrinking core model is developed to simulate particle degradation. In the modified shrinking core model, each model compound is hydrolyzed in separate stages. Cellulose is decomposed to glucose/oligomers before producing degradation products. Xylan is decomposed through xylose and then to degradation products where lignin is decomposed into soluble products before producing the total guaiacol, organic carbon (TOC) and then char and gas. Hydrolysis of each model compound is used as the main reaction of the process. Diffusion of water monomers to the particle surface to initiate hydrolysis and dissolution of the products in water is given importance during the modeling process. In the developed model the temperature variation depends on the Arrhenius relationship. Kinetic parameters from the literature are used for the mathematical model. Meanwhile, limited initial fast reaction kinetic data limit the development of more accurate CFD models. Liquefaction results of the CFD model are analyzed and validated using the experimental data available in the literature where it shows reasonable agreement.

Keywords: computational fluid dynamics, liquefaction, shrinking-core, wood

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Authors: Umar Salisu

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This research presents the development of a hot air tomatoes drying system. To provide a more efficient and continuous temperature control, microcontroller-based optimal controller was developed. The system is based on a power control principle to achieve smooth power variations depending on a feedback temperature signal of the process. An LM35 temperature sensor and LM399 differential comparator were used to measure the temperature. The mathematical model of the system was developed and the optimal controller was designed and simulated and compared with the PID controller transient response. A controlled environment suitable for fruit drying is developed within a closed chamber and is a three step process. First, the infrared light is used internally to preheated the fruit to speedily remove the water content inside the fruit for fast drying. Second, hot air of a specified temperature is blown inside the chamber to maintain the humidity below a specified level and exhaust the humid air of the chamber. Third, the microcontroller disconnects the power to the chamber after the moisture content of the fruits is removed to minimal. Experiments were conducted with 1kg of fresh tomatoes at three different temperatures (40, 50 and 60 °C) at constant relative humidity of 30%RH. The results obtained indicate that the system is significantly reducing the drying time without affecting the quality of the fruits. In the context of temperature control, the results obtained showed that the response of the optimal controller has zero overshoot whereas the PID controller response overshoots to about 30% of the set-point. Another performance metric used is the rising time; the optimal controller rose without any delay while the PID controller delayed for more than 50s. It can be argued that the optimal controller performance is preferable than that of the PID controller since it does not overshoot and it starts in good time.

Keywords: drying, microcontroller, optimum controller, PID controller

Procedia PDF Downloads 270

Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner

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Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.

Keywords: USB, device, cyber security, attack, detection

Procedia PDF Downloads 370

Authors: Magdalena Zabrocka

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The terror of women throughout the governance of the current populist ruling party in Poland, PiS, has been a subject of a heated debate alongside the issues of minorities’ rights, the rule of law, and democracy in the country. The challenges that women and other vulnerable groups are currently facing, however, come down to more than just a lack of comprehensive equality laws, severely limited reproductive rights, hateful slogans, and messages propagated by the central authority and its sympathisers, or a common disregard for women’s fundamental rights. Many sources and media reports are available only in Polish, while international rapporteurs fail to acknowledge the whole picture of the tragedy happening in the country and the variety of factors affecting it. Starting with the authorities’ and Polish catholic church’s propaganda concerning CEDAW and the Istanbul Convention Action against Violence against Women and Domestic Violence by spreading strategic disinformation that it codifies ‘gender ideology’ and ‘anti-Christian values’ in order to convince the electorate that the legal instruments should be ‘abandoned’. Alongside severely restricted abortion rights, bullying medical professionals helping women exercise their reproductive rights, violating women’s privacy by introducing a mandatory registry of pregnancies (so that one’s pregnancy or its ‘loss’ can be tracked and traced), restricting access to the ‘day after pill’ and real sex education at schools (most schools have a subject of ‘knowledge of living in a family’), introducing prison punishment for teachers accused of spreading ‘sex education’, and many other, the current tyrant government, has now decided to target the youngest with its misinformation and indoctrination, via strategically designed textbooks and curriculum. Biology books have seen a big restriction on the size of the chapters devoted to evolution, reproductive system, and sexual health. Approved religion books (which are taught 2-3 times a week as compared to 1 a week sciences) now cover false information about Darwin’s theory and arguments ‘against it’. Most recently, however, the public spoke up against the absurd messages contained in the politically rewritten history books, where the material about some figures not liked by the governing party has already been manipulated. In the recently approved changes to the history textbook, one can find a variety of strongly biased and politically-charged views representative of the conservatives in the states, most notably, equating the ‘gender ideology’ and feminism with Nazism. Thus, this work, by employing a human rights approach, would focus on the right to education and development as well as the considerate obstacles to access to scientific information by the youth.

Keywords: Poland, right to education, right to development, authoritarianism, access to information

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Authors: Rama Bhargava, Surabhi Nishad

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The infusion of nanofluids has dramatically enhanced the heat-carrying capacity of the fluids, applicable to many engineering and medical process where the temperature below freezing is required. Cryosurgery is an efficient therapy for the treatment of cancer, but sometimes the excessive cooling may harm the nearby healthy cells. Efforts are therefore done to develop a model which can cause to generate the low temperature as required. In the present study, a mathematical model is developed based on the bioheat transfer equation to simulate the heat transfer from the probe on a tumor (with irregular domain) using the hybrid technique consisting of element free Galerkin method with αα-family of approximation. The probe is loaded will nano-particles. The effects of different nanoparticles, namely Al₂O₃, Fe₃O₄, Au on the heat-producing rate, is obtained. It is observed that the temperature can be brought to (60°C)-(-30°C) at a faster freezing rate on the infusion of different nanoparticles. Besides increasing the freezing rate, the volume of the nanoparticle can also control the size and growth of ice crystals formed during the freezing process. The study is also made to find the time required to achieve the desired temperature. The problem is further extended for multi tumors of different shapes and sizes. The irregular shape of the frozen domain and the direction of ice growth are very sensitive issues, posing a challenge for simulation. The Meshfree method has been one of the accurate methods in such problems as a domain is naturally irregular. The discretization is done using the nodes only. MLS approximation is taken in order to generate the shape functions. Sufficiently accurate results are obtained.

Keywords: cryosurgery, EFGM, hybrid, nanoparticles

Procedia PDF Downloads 103

Authors: Sofia Papadimitriou

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INTRODUCTION: The differential diagnosis between acute viral and bacterial infections is an important cost-effectiveness parameter at the stage of the treatment process in order to achieve the maximum benefits in therapeutic intervention by combining the minimum cost to ensure the proper use of antibiotics.The discovery of sensitive and robust molecular diagnostic tests in response to the role of the host in infections has enhanced the accurate diagnosis and differentiation of infections. METHOD: The study used a sample of six independent blood samples (total=756) which are associated with human proteins-proteins, each of which at the transcription stage expresses a different response in the host network between viral and bacterial infections.Τhe individual blood samples are subjected to a sequence of computer filters that identify a gene panel corresponding to an autonomous diagnostic score. The data set and the correspondence of the gene panel to the diagnostic patents a new Bangalore -Viral Bacterial (BL-VB). FINDING: We use a biomarker based on the blood of 10 genes(Panel-VB) that are an important prognostic value for the detection of viruses from bacterial infections with a weighted average AUROC of 0.97(95% CL:0.96-0.99) in eleven independent samples (sets n=898). We discovered a base with a patient score (VB 10 ) according to the table, which is a significant diagnostic value with a weighted average of AUROC 0.94(95% CL: 0.91-0.98) in 2996 patient samples from 56 public sets of data from 19 different countries. We also studied VB 10 in a new cohort of South India (BL-VB,n=56) and found 97% accuracy in confirmed cases of viral and bacterial infections. We found that VB 10 (a)accurately identifies the type of infection even in unspecified cases negative to the culture (b) shows its clinical condition recovery and (c) applies to all age groups, covering a wide range of acute bacterial and viral infectious, including non-specific pathogens. We applied our VB 10 rating to publicly available COVID 19 data and found that our rating diagnosed viral infection in patient samples. RESULTS: Τhe results of the study showed the diagnostic power of the biomarker VB 10 as a diagnostic test for the accurate diagnosis of acute infections in recovery conditions. We look forward to helping you make clinical decisions about prescribing antibiotics and integrating them into your policies management of antibiotic stewardship efforts. CONCLUSIONS: Overall, we are developing a new property of the RNA-based biomarker and a new blood test to differentiate between viral and bacterial infections to assist a physician in designing the optimal treatment regimen to contribute to the proper use of antibiotics and reduce the burden on antimicrobial resistance, AMR.

Keywords: acute infections, antimicrobial resistance, biomarker, blood transcriptome, systems biology, classifier diagnostic score

Procedia PDF Downloads 131