Search results for: mode prediction

Authors: Diana C. El Assal, Fatima Monteiro, Caroline May, Peter Barbuti, Silvia Bolognin, Averina Nicolae, Hulda Haraldsdottir, Lemmer R. P. El Assal, Swagatika Sahoo, Longfei Mao, Jens Schwamborn, Rejko Kruger, Ines Thiele, Kathrin Marcus, Ronan M. T. Fleming

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Degeneration of substantia nigra pars compacta dopaminergic neurons is one of the hallmarks of Parkinson's disease. These neurons have a highly complex axonal arborisation and a high energy demand, so any reduction in ATP synthesis could lead to an imbalance between supply and demand, thereby impeding normal neuronal bioenergetic requirements. Synaptic mitochondria exhibit increased vulnerability to dysfunction in Parkinson's disease. After biogenesis in and transport from the cell body, synaptic mitochondria become highly dependent upon oxidative phosphorylation. We applied a systems biochemistry approach to identify the metabolic pathways used by neuronal mitochondria for energy generation. The mitochondrial component of an existing manual reconstruction of human metabolism was extended with manual curation of the biochemical literature and specialised using omics data from Parkinson's disease patients and controls, to generate reconstructions of synaptic and somal mitochondrial metabolism. These reconstructions were converted into stoichiometrically- and fluxconsistent constraint-based computational models. These models predict that Parkinson's disease is accompanied by an increase in the rate of glycolysis and a decrease in the rate of oxidative phosphorylation within synaptic mitochondria. This is consistent with independent experimental reports of a compensatory switching of bioenergetic pathways in the putamen of post-mortem Parkinson's disease patients. Ongoing work, in the context of the SysMedPD project is aimed at computational prediction of mitochondrial drug targets to slow the progression of neurodegeneration in the subset of Parkinson's disease patients with overt mitochondrial dysfunction.

Keywords: bioenergetics, mitochondria, Parkinson's disease, systems biochemistry

Procedia PDF Downloads 294

Authors: Chen Liu, Dawit Negussey

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EPS (Expanded Polystyrene) geofoam as light-weight material in geotechnical applications are made of pre-expanded resin beads that form fused cellular micro-structures. The strength and deformation properties of geofoam blocks are determined by unconfined compression of small test samples between rigid loading plates. Applied loads are presumed to be supported uniformly over the entire mating end areas. Predictions of field performance on the basis of such laboratory tests widely over-estimate actual post-construction settlements and exaggerate predictions of long-term creep deformations. This investigation examined the development of contact pressures at a large number of discrete points at low and large strain levels for different densities of geofoam. Development of pressure patterns for fine and coarse interface material textures as well as for molding skin and hot wire cut geofoam surfaces were examined. The lab testing showed that I-Scan tactile sensors are useful for detailed observation of contact pressures at a large number of discrete points simultaneously. At low strain level (1%), the lower density EPS block presents low variations in localized stress distribution compared to higher density EPS. At high strain level (10%), the dense geofoam reached the sensor cut-off limit. The imprint and pressure patterns for different interface textures can be distinguished with tactile sensing. The pressure sensing system can be used in many fields with real-time pressure detection. The research findings provide a better understanding of EPS geofoam behavior for improvement of design methods and performance prediction of critical infrastructures, which will be anticipated to guide future improvements in design and rapid construction of critical transportation infrastructures with geofoam in geotechnical applications.

Keywords: geofoam, pressure distribution, tactile pressure sensors, interface

Procedia PDF Downloads 173

Authors: Maneesh Kumar, Roshan Kamal Topno, Manas Ranjan Dikhit, Vahab Ali, Ganesh Chandra Sahoo, Bhawana, Major Madhukar, Rishikesh Kumar, Krishna Pandey, Pradeep Das

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Chandipura vesiculovirus is an emerging (-) ssRNA viral entity belonging to the genus Vesiculovirus of the family Rhabdoviridae, associated with fatal encephalitis in tropical regions. The multi-functionally active viral RNA-dependent RNA polymerase (vRdRp) that has been incorporated with conserved amino acid residues in the pathogens, assigned to synthesize distinct viral polypeptides. The lack of proofreading ability of the vRdRp produces many mutated variants. Here, we have performed the evolutionary analysis of 20 viral protein sequences of vRdRp of different strains of Chandipura vesiculovirus along with other viral species from genus Vesiculovirus inferred in MEGA6.06, employing the Neighbour-Joining method. The p-distance algorithmic method has been used to calculate the optimum tree which showed the sum of branch length of about 1.436. The percentage of replicate trees in which the associated taxa are clustered together in the bootstrap test (1000 replicates), is shown next to the branches. No mutation was observed in the Indian strains of Chandipura vesiculovirus. In vRdRp, 1230(His) and 1231(Arg) are actively participated in catalysis and, are found conserved in different strains of Chandipura vesiculovirus. Both amino acid residues were also conserved in the other viral species from genus Vesiculovirus. Many isolates exhibited maximum number of mutations in catalytic regions in strains of Chandipura vesiculovirus at position 26(Ser→Ala), 47 (Ser→Ala), 90(Ser→Tyr), 172(Gly→Ile, Val), 172(Ser→Tyr), 387(Asn→Ser), 1301(Thr→Ala), 1330(Ala→Glu), 2015(Phe→Ser) and 2065(Thr→Val) which make them variants under different tropical conditions from where they evolved. The result clarifies the actual concept of RNA evolution using vRdRp to develop as an evolutionary marker. Although, a limited number of vRdRp protein sequence similarities for Chandipura vesiculovirus and other species. This might endow with possibilities to identify the virulence level during viral multiplication in a host.

Keywords: Chandipura, (-) ssRNA, viral RNA-dependent RNA polymerase, neighbour-joining method, p-distance algorithmic, evolutionary marker

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Kuo-Wei Hsu, Wei-Chin Lo

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In these years, urban agriculture development has been wide spreading all over the world. The development of urban agriculture is an evolution process of highly urbanization, as well as an agricultural phenomenon closely related to the development of economy, society and culture in urban areas. It provides densely populated areas with multi-functional uses of land, impacting strategic development of both large and small towns in the area. In addition, the participation of social enterprises keeps industrial competitiveness and makes gains when facing rapid transformation of industrial structures and new patterns of lifestyles in urban areas. They create better living conditions as well as protect the environment with innovative business beliefs, which give new ways for development of urban agriculture. Also, through building up the value chain, these social enterprises are capable of creating value for urban agriculture. Most of research regarding to social enterprises currently explore the relationship between corporate responsibilities and its role play, operational mode and performance and organizational patterns. Merely some of them discuss the function of social entrepreneurship in the development of urban agriculture. Moreover, none of them have explored the value creation for development of urban agriculture processed by social enterprises, as well as how social enterprises operate to increase competitive advantages, which make it possible to achieve industrial innovation, increase corporate value and even provide services with value creation. Therefore, this research mainly reviews current business patterns and operational conditions of social enterprises. This research endowed social responsibilities, and discusses current development process of urban agriculture. This research adopts Value Chain perspective to discuss key factors for value creation with respect to the development of urban agriculture processed by social enterprises. Thereby after organization and integration this research develops the prospect of value creation referring to urban agriculture processed by social enterprises and builds the value chain for urban agriculture. In conclusion, this research explored the relationship between value chain and value creation, which relates to values of customer, enterprise, society and economy referring to the development of urban agriculture uniquely, in consideration of the participation of social enterprises, and hence built the connection between value chain and value creation in the development of urban agriculture by social enterprises. The research found, social enterprises help to enhance the connection between the enterprise value and society value, mold corporate image with social responsibility and create brand value, and therefore impact the increase of economic value.

Keywords: urban agriculture development, value chain, social enterprise, urban systems

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Authors: Hasna Elalaoui Elabdallaoui, Abdelaziz Elfazziki, Mohamed Sadgal

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Outlines: The social economy is a moral approach to solidarity applied to the projects’ development. To reconcile economic activity and social equity, crowdfunding is as an alternative means of financing social projects. Several collaborative blockchain platforms exist. It eliminates the need for a central authority or an inconsiderate middleman. Also, the costs for a successful crowdfunding campaign are reduced, since there is no commission to be paid to the intermediary. It improves the transparency of record keeping and delegates authority to authorities who may be prone to corruption. Objectives: The objectives are: to define a software infrastructure for projects’ participatory financing within a social and solidarity economy, allowing transparent, secure, and fair management and to have a financial mechanism that improves financial inclusion. Methodology: The proposed methodology is: crowdfunding platforms literature review, financing mechanisms literature review, requirements analysis and project definition, a business plan, Platform development process and implementation technology, and testing an MVP. Contributions: The solution consists of proposing a new approach to crowdfunding based on Islamic financing, which is the principle of Mousharaka inspired by Islamic financing, which presents a financial innovation that integrates ethics and the social dimension into contemporary banking practices. Conclusion: Crowdfunding platforms need to secure projects and allow only quality projects but also offer a wide range of options to funders. Thus, a framework based on blockchain technology and Islamic financing is proposed to manage this arbitration between quality and quantity of options. The proposed financing system, "Musharaka", is a mode of financing that prohibits interests and uncertainties. The implementation is offered on the secure Ethereum platform as investors sign and initiate transactions for contributions using their digital signature wallet managed by a cryptography algorithm and smart contracts. Our proposal is illustrated by a crop irrigation project in the Marrakech region.

Keywords: social economy, Musharaka, blockchain, smart contract, crowdfunding

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Authors: F. Mohammadsadeghi

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Relevance of research: Axial compressors are used in both aircraft engine construction and ground-based gas turbine engines. The compressor is considered to be one of the main gas turbine engine units, which define absolute and relative indicators of engine in general. Failure of compressor often leads to drastic consequences. Therefore, safe (stable) operation must be maintained when using axial compressor. Currently, we can observe a tendency of increase of power unit, productivity, circumferential velocity and compression ratio of axial compressors in gas turbine engines of aircraft and ground-based application whereas metal consumption of their structure tends to fall. This causes the increase of dynamic loads as well as danger of damage of high load compressor or engine structure elements in general due to transient processes. In operating practices of aeronautical engineering and ground units with gas turbine drive the operational stability failure of gas turbine engines is one of relatively often failure causes what can lead to emergency situations. Surge occurrence is considered to be an absolute buckling failure. This is one of the most dangerous and often occurring types of instability. However detailed were the researches of this phenomenon the development of measures for surge before-the-fact prevention is still relevant. This is why the research of transient processes for axial compressors is necessary in order to provide efficient, stable and secure operation. The paper addresses the problem of automatic control system improvement by integrating the anti-surge algorithms for axial compressor of aircraft gas turbine engine. Paper considers dynamic exhaustion of gas dynamic stability of compressor stage, results of numerical simulation of airflow flowing through the airfoil at design and stalling modes, experimental researches to form the criteria that identify the compressor state at pre-surge mode detection. Authors formulated basic ways for developing surge preventing systems, i.e. forming the algorithms that allow detecting the surge origination and the systems that implement the proposed algorithms.

Keywords: axial compressor, rotation stall, Surg, unstable operation of gas turbine engine

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Authors: Yi Zhang, Yuan Tian, Jiehua Chen, Sihong Gu

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Chip-scale spin-exchange relaxation free (SERF) atomic magnetometer makes use of millimeter-scale vapor cells micro-fabricated by Micro-electromechanical Systems (MEMS) technique and SERF mechanism, resulting in the characteristics of high spatial resolution and high sensitivity. It is useful for biomagnetic imaging including magnetoencephalography and magnetocardiography. In a prevailing scheme, circularly polarized on-resonance laser beam is adapted for both pumping and probing the atomic polarization. And the magnetic-field-sensitive signal is extracted by transmission laser intensity enhancement as a result of atomic polarization increase on zero field level crossing resonance. The scheme is very suitable for integration, however, the laser amplitude modulation (AM) noise and laser frequency modulation to amplitude modulation (FM-AM) noise is superimposed on the photon shot noise reducing the signal to noise ratio (SNR). To suppress AM and FM-AM noise the paper puts forward a novel scheme which adopts circularly polarized on-resonance light pumping and linearly polarized frequency-detuning laser probing. The transmission beam is divided into transmission and reflection beams by a polarization analyzer, the angle between the analyzer's transmission polarization axis and frequency-detuning laser polarization direction is set to 45°. The magnetic-field-sensitive signal is extracted by polarization rotation enhancement of frequency-detuning laser which induces two beams intensity difference increase as the atomic polarization increases. Therefore, AM and FM-AM noise in two beams are common-mode and can be almost entirely canceled by differential detection. We have carried out an experiment to study our scheme. The experiment reveals that the noise in the differential signal is obviously smaller than that in each beam. The scheme is promising to be applied for developing more sensitive chip-scale magnetometer.

Keywords: atomic magnetometer, chip scale, differential detection, spin-exchange relaxation free

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Authors: Venkateswara R. Naira, Debasish Das, Soumen K. Maiti

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Achieving high cell densities of microalgae under obligatory light-limiting and high light conditions of diurnal (low-high-low variations of daylight intensity) sunlight are further limited by CO₂ supply and dissolved oxygen (DO) accumulation in large-scale photobioreactors. High DO levels cause low growth due to photoinhibition and/or photorespiration. Hence, scalable elevated CO₂ levels (% in air) and their effect on DO accumulation in a 10 L cylindrical membrane photobioreactor (a vertical tubular type) are studied in the present study. The CO₂ elevation strategies; biomass-based, pH control based (types II & I) and diurnal light based, were explored to study the growth of Chlorella sp. FC2 IITG under single-sided LED lighting in the laboratory, mimicking diurnal sunlight. All the experiments were conducted in fed-batch mode by maintaining N and P sources at least 50% of initial concentrations of the optimized BG-11 medium. It was observed that biomass-based (2% - 1st day, 2.5% - 2nd day and 3% - thereafter) and well-known pH control based, type-I (5.8 pH throughout) strategies were found lethal for FC2 growth. In both strategies, the highest peak DO accumulation of 150% air saturation was resulted due to high photosynthetic activity caused by higher CO₂ levels. In the pH control based type-I strategy, automatically resulted CO₂ levels for pH control were recorded so high (beyond the inhibition range, 5%). However, pH control based type-II strategy (5.8 – 2 days, 6.3 – 3 days, 6.7 – thereafter) showed final biomass titer up to 4.45 ± 0.05 g L⁻¹ with peak DO of 122% air saturation; high CO₂ levels beyond 5% (in air) were recorded thereafter. Thus, it became sustainable for obtaining high biomass. Finally, a diurnal light based (2% - low light, 2.5 % - medium light and 3% - high light) strategy was applied on the basis of increasing/decreasing photosynthesis due to increase/decrease in diurnal light intensity. It has resulted in maximum final biomass titer of 5.33 ± 0.12 g L⁻¹, with total biomass productivity of 0.59 ± 0.01 g L⁻¹ day⁻¹. The values are remarkably higher than constant 2% CO₂ level (final biomass titer: 4.26 ± 0.09 g L⁻¹; biomass productivity: 0.27 ± 0.005 g L⁻¹ day⁻¹). However, 135% air saturation of peak DO was observed. Thus, the diurnal light based elevation should be further improved by using CO₂ enriched N₂ instead of air. To the best of knowledge, the light-based CO₂ elevation strategy is not reported elsewhere.

Keywords: Chlorella sp., CO₂ elevation strategy, dissolved oxygen accumulation, diurnal light based CO₂ elevation, high cell density, microalgae, scale-up

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Authors: Shreyas Srinivas Rangan, Jurgis Porins

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The internet traffic has increased exponentially due to the high demand for data rates by the users, and the constantly increasing metro networks and access networks are focused on improving the maximum transmit distance of the long-reach optical networks. One of the common methods to improve the maximum transmit distance of the long-reach optical networks at the component level is to use broadband optical amplifiers. The Erbium Doped Fiber Amplifier (EDFA) provides high amplification with low noise figure but due to the characteristics of EDFA, its operation is limited to C-band and L-band. In contrast, the Raman amplifier exhibits a wide amplification spectrum, and negative noise figure values can be achieved. To obtain such results, high powered pumping sources are required. Operating Raman amplifiers with such high-powered optical sources may cause fire hazards and it may damage the optical system. In this paper, we implement a hybrid optical amplifier configuration. EDFA and Raman amplifiers are used in this hybrid setup to combine the advantages of both EDFA and Raman amplifiers to improve the reach of the system. Using this setup, we analyze the maximum transmit distance of the network by obtaining a correlation diagram between the length of the single-mode fiber (SMF) and the Bit Error Rate (BER). This hybrid amplifier configuration is implemented in a Wavelength Division Multiplexing (WDM) system with a BER of 10⁻⁹ by using NRZ modulation format, and the gain uniformity noise ratio (signal-to-noise ratio (SNR)), the efficiency of the pumping source, and the optical signal gain efficiency of the amplifier are studied experimentally in a mathematical modelling environment. Numerical simulations were implemented in RSoft OptSim simulation software based on the nonlinear Schrödinger equation using the Split-Step method, the Fourier transform, and the Monte Carlo method for estimating BER.

Keywords: Raman amplifier, erbium doped fibre amplifier, bit error rate, hybrid optical amplifiers

Procedia PDF Downloads 70

Authors: Ravi Verma

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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

Procedia PDF Downloads 89

Authors: Mohammed S. Bhader, Abdullah A. Ghaddaf, Anas Alamoudi, Amal Abualola, Renad Kalantan, Noura Alkhulaifi, Ibrahim Halawani, Mohammed Alhindi

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Background: Noninvasive neurally adjusted ventilatory assist (NAVA) is a relatively new mode of noninvasive ventilation with promising clinical and patient-ventilator outcomes for preterm infants. The aim of this systematic review was to compare NAVA to nasal continuous or positive airway pressure (NCPAP) or intermittent positive airway pressure (NIPP) for preterm infants. Methods: We searched the online databases Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared NAVA to NCPAP or NIPP for preterm infants < 37 weeks gestational age. We sought to evaluate the following outcomes: noninvasive intubation failure rate, desaturation rate, the fraction of inspired oxygen (FiO2), and length of stay in the neonatal intensive care unit (NICU). We used the mean difference (MD) to represent continuous outcomes, while the odds ratio (OR) was used to represent dichotomous outcomes. Results: A total of 11 RCTs that enrolled 429 preterm infants were deemed eligible. NAVA showed similar clinical outcomes to NCPAP or NIPP with respect to noninvasive intubation failure (RR for NAVA versus NCPAP: 0.82, 95% confidence interval (CI): 0.49 to 1.37), desaturation rate (RR for NAVA versus NCPAP: 0.69, 95%CI: 0.36 to 1.29; RR for NAVA versus NIPP: 0.58, 95%CI: 0.08 to 4.25), FiO2 (MD for NAVA versus NCPAP: –0.01, 95%CI: –0.04 to 0.02; MD for NAVA versus NIPP: –7.16, 95%CI: –22.63 to 8.31), and length of stay in the NICU (MD for NAVA versus NCPAP: 1.34, 95%CI: –4.17 to 6.85). Conclusion: NAVA showed similar clinical and ventilator-related outcomes compared to the usual care noninvasive respiratory support measures NCPAP or NIPP for preterm infants.

Keywords: preterm infants, noninvasive neurally adjusted ventilatory assist, NIV-NAVA, non-invasive ventilation, nasal continuous or positive airway pressure, NCPAP, intermittent positive airway pressure ventilation, NIPP, respiratory distress syndrome, RDS

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Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

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Authors: Pierre van Tonder, Dinesh Muthoo, Kim twiname

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Many existing and newly built structures are constructed on the design basis of the engineer and the workmanship of the construction company. However, when considering larger structures where more people are exposed to the building, its structural integrity is of great importance considering the safety of its occupants (Raghu, 2013). But how can the structural integrity of a building be monitored efficiently and effectively. This is where the fourth industrial revolution step in, and with minimal human interaction, data can be collected, analysed, and stored, which could also give an indication of any inconsistencies found in the data collected, this is where the Fibre Bragg Grating (FBG) monitoring system is introduced. This paper illustrates how data can be collected and converted to develop stress – strain behaviour and to produce bending moment diagrams for the utilisation and prediction of the structure’s integrity. Embedded fibre optic sensors were used in this study– fibre Bragg grating sensors in particular. The procedure entailed making use of the shift in wavelength demodulation technique and an inscription process of the phase mask technique. The fibre optic sensors considered in this report were photosensitive and embedded in the slab and beams for data collection and analysis. Two sets of fibre cables have been inserted, one purposely to collect temperature recordings and the other to collect strain and temperature. The data was collected over a time period and analysed used to produce bending moment diagrams to make predictions of the structure’s integrity. The data indicated the fibre Bragg grating sensing system proved to be useful and can be used for structural health monitoring in any environment. From the experimental data for the slab and beams, the moments were found to be64.33 kN.m, 64.35 kN.m and 45.20 kN.m (from the experimental bending moment diagram), and as per the idealistic (Ultimate Limit State), the data of 133 kN.m and 226.2 kN.m were obtained. The difference in values gave room for an early warning system, in other words, a reserve capacity of approximately 50% to failure.

Keywords: fibre bragg grating, structural health monitoring, fibre optic sensors, beams

Procedia PDF Downloads 139

Authors: Esam Jassim

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Industries using conventional fossil fuels have an interest in better understanding the mechanism of particulate formation during combustion since such is responsible for emission of undesired inorganic elements that directly impact the atmospheric pollution level. Fine and ultrafine particulates have tendency to escape the flue gas cleaning devices to the atmosphere. They also preferentially collect on surfaces in power systems resulting in ascending in corrosion inclination, descending in the heat transfer thermal unit, and severe impact on human health. This adverseness manifests particularly in the regions of world where coal is the dominated source of energy for consumption. This study highlights the behavior of calcium transformation as mineral grains verses organically associated inorganic components during pulverized coal combustion. The influence of existing type of calcium on the coarse, fine and ultrafine mode formation mechanisms is also presented. The impact of two sub-bituminous coals on particle size and calcium composition evolution during combustion is to be assessed. Three mixed blends named Blends 1, 2, and 3 are selected according to the ration of coal A to coal B by weight. Calcium percentage in original coal increases as going from Blend 1 to 3. A mathematical model and a new approach of describing constituent distribution are proposed. Analysis of experiments of calcium distribution in ash is also modeled using Poisson distribution. A novel parameter, called elemental index λ, is introduced as a measuring factor of element distribution. Results show that calcium in ash that originally in coal as mineral grains has index of 17, whereas organically associated calcium transformed to fly ash shown to be best described when elemental index λ is 7. As an alkaline-earth element, calcium is considered the fundamental element responsible for boiler deficiency since it is the major player in the mechanism of ash slagging process. The mechanism of particle size distribution and mineral species of ash particles are presented using CCSEM and size-segregated ash characteristics. Conclusions are drawn from the analysis of pulverized coal ash generated from a utility-scale boiler.

Keywords: coal combustion, inorganic element, calcium evolution, fluid dynamics

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

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Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a Matlab environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry

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Authors: Sofiya Rao, Sagnik Dey

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Aerosol-cloud-precipitation interaction continues to be one of the largest sources of uncertainty in quantifying the aerosol climate forcing. The uncertainty is increasing from global to regional scale. This problem remains unresolved due to the large discrepancy in the representation of cloud processes in the climate models. Most of the studies on aerosol-cloud-climate interaction and aerosol-cloud-precipitation over Indian Ocean (like INDOEX, CAIPEEX campaign etc.) are restricted to either particular to one season or particular to one region. Here we developed a theoretical framework to quantify aerosol indirect radiative forcing using Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol and cloud products of 15 years (2000-2015) period over the Indian Ocean. This framework relies on the observationally constrained estimate of the aerosol-induced change in cloud albedo. We partitioned the change in cloud albedo into the change in Liquid Water Path (LWP) and Effective Radius of Clouds (Reff) in response to an aerosol optical depth (AOD). Cloud albedo response to an increase in AOD is most sensitive in the range of LWP between 120-300 gm/m² for a range of Reff varying from 8-24 micrometer, which means aerosols are most sensitive to this range of LWP and Reff. Using this framework, aerosol forcing during a transition from indirect to semi-direct effect is also calculated. The outcome of this analysis shows best results over the Arabian Sea in comparison with the Bay of Bengal and the South Indian Ocean because of heterogeneity in aerosol spices over the Arabian Sea. Over the Arabian Sea during Winter Season the more absorbing aerosols are dominating, during Pre-monsoon dust (coarse mode aerosol particles) are more dominating. In winter and pre-monsoon majorly the aerosol forcing is more dominating while during monsoon and post-monsoon season meteorological forcing is more dominating. Over the South Indian Ocean, more or less same types of aerosol (Sea salt) are present. Over the Arabian Sea the Aerosol Indirect Radiative forcing are varying from -5 ± 4.5 W/m² for winter season while in other seasons it is reducing. The results provide observationally constrained estimates of aerosol indirect forcing in the Indian Ocean which can be helpful in evaluating the climate model performance in the context of such complex interactions.

Keywords: aerosol-cloud-precipitation interaction, aerosol-cloud-climate interaction, indirect radiative forcing, climate model

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Authors: Markus Pajones, Theresa Steiner, Matthias Neubauer

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Selecting a logistics location is vital for logistics providers, food retailing and other trading companies since the selection poses an essential factor for economic success. Therefore various location search methods like cost-benefit analysis and others are well known and under usage. The development of a logistics location can be related to considerable negative effects for the eco system such as sealing the surface, wrecking of biodiversity or CO2 and noise emissions generated by freight and commuting traffic. The increasing importance of sustainability demands for taking an informed decision when selecting a logistics location for the future. Sustainability considers economic, ecologic and social aspects which should be equally integrated in the process of location search. Objectives of this paper are to define various methods which support the selection of sustainable logistics locations and to generate knowledge about the suitability, assets and limitations of the methods within the selection process. This paper investigates the role of economical, ecological and social aspects when searching for new logistics locations. Thereby, related work targeted towards location search is analyzed with respect to encoded sustainability aspects. In addition, this research aims to gain knowledge on how to include aspects of sustainability and take an informed decision when searching for a logistics location. As a result, a decomposition of the various location search methods in there components leads to a comparative analysis in form of a matrix. The comparison within a matrix enables a transparent overview about the mentioned assets and limitations of the methods and their suitability for selecting sustainable logistics locations. A further result is to generate knowledge on how to combine the separate methods to a new method for a more efficient selection of logistics locations in the context of sustainability. Future work will especially investigate the above mentioned combination of various location search methods. The objective is to develop an innovative instrument, which supports the search for logistics locations with a focus on a balanced sustainability (economy, ecology, social). Because of an ideal selection of logistics locations, induced traffic should be reduced and a mode shift to rail and public transport should be facilitated.

Keywords: commuting traffic, freight traffic, logistics location search, location search method

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Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

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Authors: Frederic Heymes, Michael Albrecht Birk, Roland Eyssette

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Boiling Liquid Expanding Vapor Explosion (BLEVE) has been a well know industrial accident for over 6 decades now, and yet it is still poorly predicted and avoided. BLEVE is created when a vessel containing a pressure liquefied gas (PLG) is engulfed in a fire until the tank rupture. At this time, the pressure drops suddenly, leading the liquid to be in a superheated state. The vapor expansion and the violent boiling of the liquid produce several shock waves. This works aimed at understanding the contribution of vapor ad liquid phases in the overpressure generation in the near field. An experimental work was undertaken at a small scale to reproduce realistic BLEVE explosions. Key parameters were controlled through the experiments, such as failure pressure, fluid mass in the vessel, and weakened length of the vessel. Thirty-four propane BLEVEs were then performed to collect data on scenarios similar to common industrial cases. The aerial overpressure was recorded all around the vessel, and also the internal pressure changed during the explosion and ground loading under the vessel. Several high-speed cameras were used to see the vessel explosion and the blast creation by shadowgraph. Results highlight how the pressure field is anisotropic around the cylindrical vessel and highlights a strong dependency between vapor content and maximum overpressure from the lead shock. The time chronology of events reveals that the vapor phase is the main contributor to the aerial overpressure peak. A prediction model is built upon this assumption. Secondary flow patterns are observed after the lead. A theory on how the second shock observed in experiments forms is exposed thanks to an analogy with numerical simulation. The phase change dynamics are also discussed thanks to a window in the vessel. Ground loading measurements are finally presented and discussed to give insight into the order of magnitude of the force.

Keywords: phase change, superheated state, explosion, vapor expansion, blast, shock wave, pressure liquefied gas

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Authors: Snigdha Sahai, Devaki Chikkavenkatappa Yellappa

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This study outlines approaches for testing and validating stochastic models used in epidemiology, focusing on the integration and functional testing of simulation code. It details methods for combining simple functions into comprehensive simulations, distinguishing between deterministic and stochastic components, and applying tests to ensure robustness. Techniques include isolating stochastic elements, utilizing large sample sizes for validation, and handling special cases. Practical examples are provided using R code to demonstrate integration testing, handling of incorrect inputs, and special cases. The study emphasizes the importance of both functional and defensive programming to enhance code reliability and user-friendliness.

Keywords: computational epidemiology, epidemiology, public health, infectious disease modeling, statistical analysis, health data analysis, disease transmission dynamics, predictive modeling in health, population health modeling, quantitative public health, random sampling simulations, randomized numerical analysis, simulation-based analysis, variance-based simulations, algorithmic disease simulation, computational public health strategies, epidemiological surveillance, disease pattern analysis, epidemic risk assessment, population-based health strategies, preventive healthcare models, infection dynamics in populations, contagion spread prediction models, survival analysis techniques, epidemiological data mining, host-pathogen interaction models, risk assessment algorithms for disease spread, decision-support systems in epidemiology, macro-level health impact simulations, socioeconomic determinants in disease spread, data-driven decision making in public health, quantitative impact assessment of health policies, biostatistical methods in population health, probability-driven health outcome predictions

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Authors: Ahmet Erdoğan, Şahin Kesici, Mustafa Baloğlu

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Information technologies have lead to changes in the areas of communication, learning, and teaching. Besides offering many opportunities to the learners, these technologies have changed the teaching methods and beliefs of teachers. What the Technological Pedagogical Content Knowledge (TPACK) means to the teachers is considerably important to integrate technology successfully into teaching processes. It is necessary to understand how to plan and apply teacher training programs in order to balance students’ pedagogical and technological knowledge. Because of many inefficient teacher training programs, teachers have difficulties in relating technology, pedagogy and content knowledge each other. While providing an efficient training supported with technology, understanding the three main components (technology, pedagogy and content knowledge) and their relationship are very crucial. The purpose of this study is to determine whether motivational beliefs and self-regulated learning strategies are significant predictors of mathematics teacher candidates' TPACK perceptions. A hundred seventy five Turkish mathematics teachers candidates responded to the Motivated Strategies for Learning Questionnaire (MSLQ) and the Technological Pedagogical And Content Knowledge (TPACK) Scale. Of the group, 129 (73.7%) were women and 46 (26.3%) were men. Participants' ages ranged from 20 to 31 years with a mean of 23.04 years (SD = 2.001). In this study, a multiple linear regression analysis was used. In multiple linear regression analysis, the relationship between the predictor variables, mathematics teacher candidates' motivational beliefs, and self-regulated learning strategies, and the dependent variable, TPACK perceptions, were tested. It was determined that self-efficacy for learning and performance and intrinsic goal orientation are significant predictors of mathematics teacher candidates' TPACK perceptions. Additionally, mathematics teacher candidates' critical thinking, metacognitive self-regulation, organisation, time and study environment management, and help-seeking were found to be significant predictors for their TPACK perceptions.

Keywords: candidate mathematics teachers, motivational beliefs, self-regulated learning strategies, technological and pedagogical knowledge, content knowledge

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Authors: Bojana Horvat, Barbara Karleusa, Goran Volf, Nevenka Ozanic, Ivica Kisic

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Forest fire is a major threat in many regions in Croatia, especially in coastal areas. Although they are often caused by natural processes, the most common cause is the human factor, intentional or unintentional. Forest fires drastically transform landscapes and influence natural processes. The main goal of the presented research is to analyse and quantify the impact of the forest fire on hydrological processes and propose the model that best describes changes in hydrological patterns in the analysed catchments. Keeping in mind the spatial component of the processes, geospatial analysis is performed to gain better insight into the spatial variability of the hydrological response to disastrous events. In that respect, two catchments that experienced severe forest fire were delineated, and various hydrological and meteorological data were collected both attribute and spatial. The major drawback is certainly the lack of hydrological data, common in small torrential karstic streams; hence modelling results should be validated with the data collected in the catchment that has similar characteristics and established hydrological monitoring. The event chosen for the modelling is the forest fire that occurred in July 2019 and burned nearly 10% of the analysed area. Surface (land use/land cover) conditions before and after the event were derived from the two Sentinel-2 images. The mapping of the burnt area is based on a comparison of the Normalized Burn Index (NBR) computed from both images. To estimate and compare hydrological behaviour before and after the event, curve number (CN) values are assigned to the land use/land cover classes derived from the satellite images. Hydrological modelling resulted in surface runoff generation and hence prediction of hydrological responses in the catchments to a forest fire event. The research was supported by the Croatian Science Foundation through the project 'Influence of Open Fires on Water and Soil Quality' (IP-2018-01-1645).

Keywords: Croatia, forest fire, geospatial analysis, hydrological response

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Authors: Tarek Duzan

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Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

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Authors: L. Guevara, Glória L. S., Corea E. E, A. Ramírez-Zamora M., Salinas-Martinez J. A., Angeles-Hernandez J. C.

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Mathematical models are useful for identifying the characteristics of sheep lactation curves to develop and implement improved strategies. However, the accuracy of these models is influenced by factors such as the recording regime, mainly the intervals between test day records (TDR). The current study aimed to evaluate the effect of different TDR intervals on the goodness of fit of the Wood model (WM) applied to dairy sheep lactations. A total of 4,494 weekly TDRs from 156 lactations of dairy crossbred sheep were analyzed. Three new databases were generated from the original weekly TDR data (7D), comprising intervals of 14(14D), 21(21D), and 28(28D) days. The parameters of WM were estimated using the “minpack.lm” package in the R software. The shape of the lactation curve (typical and atypical) was defined based on the WM parameters. The goodness of fit was evaluated using the mean square of prediction error (MSPE), Root of MSPE (RMSPE), Akaike´s Information Criterion (AIC), Bayesian´s Information Criterion (BIC), and the coefficient of correlation (r) between the actual and estimated total milk yield (TMY). WM showed an adequate estimate of TMY regardless of the TDR interval (P=0.21) and shape of the lactation curve (P=0.42). However, we found higher values of r for typical curves compared to atypical curves (0.9vs.0.74), with the highest values for the 28D interval (r=0.95). In the same way, we observed an overestimated peak yield (0.92vs.6.6 l) and underestimated time of peak yield (21.5vs.1.46) in atypical curves. The best values of RMSPE were observed for the 28D interval in both lactation curve shapes. The significant lowest values of AIC (P=0.001) and BIC (P=0.001) were shown by the 7D interval for typical and atypical curves. These results represent the first approach to define the adequate interval to record the regime of dairy sheep in Latin America and showed a better fitting for the Wood model using a 7D interval. However, it is possible to obtain good estimates of TMY using a 28D interval, which reduces the sampling frequency and would save additional costs to dairy sheep producers.

Keywords: gamma incomplete, ewes, shape curves, modeling

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Authors: Amaal Ali Al-Gamde

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The Syrian revolution is a major issue in the Middle East, which draws in world powers and receives a great focus in international mass media since 2011. The heavy global reliance on cyber news and digital sources plays a key role in conveying a sense of bias to a wide range of online readers. Thus, based on the assumption that media discourse possesses ideological implications, this study investigates the representation of Syrian revolution in online media. The paper explores the discursive constructions of anti and pro-government powers in Syrian revolution in 1000,000-word corpus of Fars online reports (an Iranian news agency), issued between 2013 and 2015. Taking a corpus assisted discourse analysis approach, the analysis investigates three types of lexicosemantic relations, the semantic macrostructures within which the two social actors are framed, the lexical collocations characterizing the news discourse and the discourse prosodies they tell about the two sides of the conflict. The study utilizes computer-based approaches, sketch engine and AntConc software to minimize the bias of the subjective analysis. The analysis moves from the insights of lexical frequencies and keyness scores to examine themes and the collocational patterns. The findings reveal the Fars agency’s ideological mode of representations in reporting events of Syrian revolution in two ways. The first is by stereotyping the opposition groups under the umbrella of terrorism, using words such as (law breakers, foreign-backed groups, militant groups, terrorists) to legitimize the atrocities of security forces against protesters and enhance horror among civilians. The second is through emphasizing the power of the government and depicting it as the defender of the Arab land by foregrounding the discourse of international conspiracy against Syria. The paper concludes discussing the potential importance of triangulating corpus linguistic tools with critical discourse analysis to elucidate more about discourses and reality.

Keywords: discourse prosody, ideology, keyness, semantic macrostructure

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Authors: Hala Raslan, Noha Eltaweel, Hanaa Rasmi, Solaf Kamel, May Magdy, Sherif Ismail, Khalda Amr

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Introduction: Rheumatoid arthritis (RA) is an inflammatory, autoimmune disorder with progressive joint damage. Osteoarthritis (OA) is a degenerative disease of the articular cartilage that shows multiple clinical manifestations or symptoms resembling those of RA. Genetic predisposition is believed to be a principal etiological factor for RA and OA. In this study, we aimed to measure the expression of the top deregulated miRNAs that might be the cause of pathogenesis in both diseases, according to our latest NGS analysis. Six of the deregulated miRNAs were selected as they had multiple target genes in the RA pathway, so they are more likely to affect the RA pathogenesis.Methods: Eighty cases were recruited in this study; 45 rheumatoid arthiritis (RA), 30 osteoarthiritis (OA) patients, as well as 20 healthy controls. The selection of the miRNAs from our latest NGS study was done using miRwalk according to the number of their target genes that are members in the KEGG RA pathway. Total RNA was isolated from plasma of all recruited cases. The cDNA was generated by the miRcury RT Kit then used as a template for real-time PCR with miRcury Primer Assays and the miRcury SYBR Green PCR Kit. Fold changes were calculated from CT values using the ΔΔCT method of relative quantification. Results were compared RA vs Controls and OA vs Controls. Target gene prediction and functional annotation of the deregulated miRNAs was done using Mienturnet. Results: Six miRNAs were selected. They were miR-15b-3p, -128-3p, -194-3p, -328-3p, -542-3p and -3180-5p. In RA samples, three of the measured miRNAs were upregulated (miR-194, -542, and -3180; mean Rq= 2.6, 3.8 and 8.05; P-value= 0.07, 0.05 and 0.01; respectively) while the remaining 3 were downregulated (miR-15b, -128 and -328; mean Rq= 0.21, 0.39 and 0.6; P-value= <0.0001, <0.0001 and 0.02; respectively) all with high statistical significance except miR-194. While in OA samples, two of the measured miRNAs were upregulated (miR-194 and -3180; mean Rq= 2.6 and 7.7; P-value= 0.1 and 0.03; respectively) while the remaining 4 were downregulated (miR-15b, -128, -328 and -542; mean Rq= 0.5, 0.03, 0.08 and 0.5; P-value= 0.0008, 0.003, 0.006 and 0.4; respectively) with statistical significance compared to controls except miR-194 and miR-542. The functional enrichment of the selected top deregulated miRNAs revealed the highly enriched KEGG pathways and GO terms. Conclusion: Five of the studied miRNAs were greatly deregulated in RA and OA, they might be highly involved in the disease pathogenesis and so might be future therapeutic targets. Further functional studies are crucial to assess their roles and actual target genes.

Keywords: MiRNAs, expression, rheumatoid arthritis, osteoarthritis

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Authors: Aliseydi Bozkurt

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Objectives: Benign prostatic hyperplasia (BPH) is the most common benign disease, and prostate cancer (PC) is malign disease of the prostate gland. Transrectal ultrasound-guided biopsy (TRUS-bx) is one of the most important diagnostic tools in PC diagnosis. Identifying men at increased risk for having a biopsy detectable prostate cancer should consider prostate specific antigen density (PSAD), f/t PSA Ratio, an estimate of prostate volume. Method: We retrospectively studied 269 patients who had a prostate specific antigen (PSA) score of 4 or who had suspected rectal examination at any PSA level and received TRUS-bx between January 2015 and June 2018 in our clinic. TRUS-bx was received by 12 experienced urologists with 12 quadrants. Prostate volume was calculated prior to biopsy together with TRUS. Patients were classified as malignant and benign at the end of pathology. Age, PSA value, prostate volume in transrectal ultrasonography, corpuscle biopsy, biopsy pathology result, the number of cancer core and Gleason score were evaluated in the study. The success rates of PV, PSAD, and f/tPSA were compared in all patients and those with PSA 2.5-10 ng/mL and 10.1-30 ng/mL tp foresee prostate cancer. Result: In the present study, in patients with PSA 2.5-10 ng/ml, PV cut-off value was 43,5 mL (n=42 < 43,5 mL and n=102 > 43,5 mL) while in those with PSA 10.1-30 ng/mL prostate volüme (PV) cut-off value was found 61,5 mL (n=31 < 61,5 mL and n=36 > 61,5 mL). Total PSA values in the group with PSA 2.5-10 ng/ml were found lower (6.0 ± 1.3 vs 6.7 ± 1.7) than that with PV < 43,5 mL, this value was nearly significant (p=0,043). In the group with PSA value 10.1-30 ng/mL, no significant difference was found (p=0,117) in terms of total PSA values between the group with PV < 61,5 mL and that with PV > 61,5 mL. In the group with PSA 2.5-10 ng/ml, in patients with PV < 43,5 mL, f/t PSA value was found significantly lower compared to the group with PV > 43,5 mL (0.21 ± 0.09 vs 0.26 ± 0.09 p < 0.001 ). Similarly, in the group with PSA value of 10.1-30 ng/mL, f/t PSA value was found significantly lower in patients with PV < 61,5 mL (0.16 ± 0.08 vs 0.23 ± 0.10 p=0,003). In the group with PSA 2.5-10 ng/ml, PSAD value in patients with PV < 43,5 mL was found significantly higher compared to those with PV > 43,5 mL (0.17 ± 0.06 vs 0.10 ± 0.03 p < 0.001). Similarly, in the group with PSA value 10.1-30 ng/mL PSAD value was found significantly higher in patients with PV < 61,5 mL (0.47 ± 0.23 vs 0.17 ± 0.08 p < 0.001 ). The biopsy results suggest that in the group with PSA 2.5-10 ng/ml, in 29 of the patients with PV < 43,5 mL (69%) cancer was detected while in 13 patients (31%) no cancer was detected. While in 19 patients with PV > 43,5 mL (18,6%) cancer was found, in 83 patients (81,4%) no cancer was detected (p < 0.001). In the group with PSA value 10.1-30 ng/mL, in 21 patients with PV < 61,5 mL (67.7%) cancer was observed while only in10 patients (32.3%) no cancer was seen. In 5 patients with PV > 61,5 mL (13.9%) cancer was found while in 31 patients (86.1%) no cancer was observed (p < 0.001). Conclusions: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider PSA, f/t PSA Ratio, an estimate of prostate volume. Prostate volume in PC was found lower.

Keywords: prostate cancer, prostate volume, prostate specific antigen, free/total PSA ratio

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Authors: Shishay Kidanu, Abdullah Alhaj

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Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

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Authors: Ola Jon Mork, Lars Andre Giske, Emil Bjørlykhaug

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Stabilization of critical processes in order to have the right quality of the products, more efficient production and smoother flow is a key issue in lean production. This paper presents how simulation of key welding processes can stabilize complicated welding processes in small scale production, and how simulation can impact the entire production concept seen from the perspective of lean production. First, a field study was made to learn the production processes in the factory, and subsequently the field study was transformed into a value stream map to get insight into each operation, the quality issues, operation times, lead times and flow of materials. Valuable practical knowledge of how the welding operations were done by operators, appropriate tools and jigs, and type of robots that could be used, was collected. All available information was then implemented into a simulation environment for further elaboration and development. Three researchers, the management of the company and skilled operators at the work floor where working on the project over a period of eight months, and a detailed description of the process was made by the researchers. The simulation showed that simulation could solve a number of technical challenges, the robot program can be tuned in off line mode, and the design and testing of the robot cell could be made in the simulator. Further on the design of the product could be optimized for robot welding and the jigs could be designed and tested in simulation environment. This means that a key issue of lean production can be solved; the welding operation will work with almost 100% performance when it is put into real production. Stabilizing of one key process is critical to gain control of the entire value chain, then a Takt Time can be established and the focus can be directed towards the next process in the production which should be stabilized. Results show that industrial parameters like welding time, welding cost and welding quality can be defined on the simulation stage. Further on, this gives valuable information for calculation of the factories business performance, like manufacturing volume and manufacturing efficiency. Industrial impact from simulation is more efficient implementation of lean manufacturing, since the welding process can be stabilized. More research should be done to gain more knowledge about simulation as a tool for implementation of lean, especially where there complex processes.

Keywords: simulation, lean, stabilization, welding process

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