Search results for: online range monitoring

Authors: Hashini E. Mohottala

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We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS.

Keywords: group problem solving (GPS), wikispace (WikiS), physics education, learning

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Authors: Mostafa Shahriari, Sergio Rojas, David Pardo, Angel Rodriguez- Rozas, Shaaban A. Bakr, Victor M. Calo, Ignacio Muga

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Logging-While Drilling (LWD) is a technique to record down-hole logging measurements while drilling the well. Nowadays, LWD devices (e.g., nuclear, sonic, resistivity) are mostly used commercially for geo-steering applications. Modern borehole resistivity tools are able to measure all components of the magnetic field by incorporating tilted coils. The depth of investigation of LWD tools is limited compared to the thickness of the geological layers. Thus, it is a common practice to approximate the Earth’s subsurface with a sequence of 1D models. For a 1D model, we can reduce the dimensionality of the problem using a Hankel transform. We can solve the resulting system of ordinary differential equations (ODEs) either (a) analytically, which results in a so-called semi-analytic method after performing a numerical inverse Hankel transform, or (b) numerically. Semi-analytic methods are used by the industry due to their high performance. However, they have major limitations, namely: -The analytical solution of the aforementioned system of ODEs exists only for piecewise constant resistivity distributions. For arbitrary resistivity distributions, the solution of the system of ODEs is unknown by today’s knowledge. -In geo-steering, we need to solve inverse problems with respect to the inversion variables (e.g., the constant resistivity value of each layer and bed boundary positions) using a gradient-based inversion method. Thus, we need to compute the corresponding derivatives. However, the analytical derivatives of cross-bedded formation and the analytical derivatives with respect to the bed boundary positions have not been published to the best of our knowledge. The main contribution of this work is to overcome the aforementioned limitations of semi-analytic methods by solving each 1D model (associated with each Hankel mode) using an efficient multi-scale finite element method. The main idea is to divide our computations into two parts: (a) offline computations, which are independent of the tool positions and we precompute only once and use them for all logging positions, and (b) online computations, which depend upon the logging position. With the above method, (a) we can consider arbitrary resistivity distributions along the 1D model, and (b) we can easily and rapidly compute the derivatives with respect to any inversion variable at a negligible additional cost by using an adjoint state formulation. Although the proposed method is slower than semi-analytic methods, its computational efficiency is still high. In the presentation, we shall derive the mathematical variational formulation, describe the proposed multi-scale finite element method, and verify the accuracy and efficiency of our method by performing a wide range of numerical experiments and comparing the numerical solutions to semi-analytic ones when the latest are available.

Keywords: logging-While-Drilling, resistivity measurements, multi-scale finite elements, Hankel transform

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Authors: Said Fares, Mary Fares

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It is well documented that introductory computer programming courses are difficult and that failure rates are high. The aim of this project was to reduce the high failure and withdrawal rates in learning to program. This paper presents a number of changes in module organization and instructional delivery system in teaching CS1. Daily out of class help sessions and tutoring services were applied, interactive lectures and laboratories, online resources, and timely feedback were introduced. Five years of data of 563 students in 21 sections was collected and analyzed. The primary results show that the failure and withdrawal rates were cut by more than half. Student surveys indicate a positive evaluation of the modified instructional approach, overall satisfaction with the course and consequently, higher success and retention rates.

Keywords: failure rate, interactive learning, student engagement, CS1

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Authors: D. Zahran, M. AlKhazindar, M. Khalil, E. T. A. Sayed

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Streptomyces scabies is a pathogenic actinomycete that infects potato crop causing severe production losses. Actinophages affect the composition and diversity of the bacterial population, thereby, can be used as a biological control. Samples of actinomycetes and phages were collected from different cultivated soils including farms of Faculty of Science, Faculty of Agriculture and different locations in Giza, Egypt. Actinomycetes were identified by using biochemical, morphological tests and molecular studies using 16S rRNA sequencing. Two specific phages (E1 and E2) against Streptomyces scabies and other hosts were isolated. Phages were identified using dilution end point (DEP), longevity in vitro (LIV), thermal inactivation point (TIP), host range and electron microscopy. PhageE1 was characterized by 10-8 (DEP),180 days(LIV), 95°C(TIP), narrow host range and electron microscopy showed ahead (59.9 nm) and neck (10.4nm). On the other hand phageE2 had 10-20 (DEP),180 days(LIV), 90°C(TIP), and the size of head was (67.2 nm) and tail (114nm). Antiviral activity was also studied using different chemicals (NaCL, KCL, CaCL2, BaCL2, CoCL2, AgNO3, ALCL3and HgCL2) with different concentrations and different plant extracts with different concentrations (star anise, tea, tillia, peppermint, ginger, cumin, chamomile, turmeric cinnamon, marjoram and black cumin). Both Phage E1and phage E2 were vulnerable to (cumin, ginger, chamomile, guavas leaves and star anise) but resistant to (Tillie, marjoram, fennelflower seeds, peppermint, and cinnamon).

Keywords: potato scab, actinophages, biological control, electron microscopy, TIP, DEP, LIV, antiviral activity

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Authors: Younghoon Kim, Seoung Bum Kim

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One-class classification plays an important role in detecting outlier and abnormality from normal observations. In the previous research, several attempts were made to extend the scope of application of the one-class classification techniques to statistical process control problems. For most previous approaches, such as support vector data description (SVDD) control chart, the design of the control limits is commonly based on the assumption that the proportion of abnormal observations is approximately equal to an expected Type I error rate in Phase I process. Because of the limitation of the one-class classification techniques based on convex optimization, we cannot make the proportion of abnormal observations exactly equal to expected Type I error rate: controlling Type I error rate requires to optimize constraints with integer decision variables, but convex optimization cannot satisfy the requirement. This limitation would be undesirable in theoretical and practical perspective to construct effective control charts. In this work, to address the limitation of previous approaches, we propose the one-class classification algorithm based on the mixed integer programming technique, which can solve problems formulated with continuous and integer decision variables. The proposed method minimizes the radius of a spherically shaped boundary subject to the number of normal data to be equal to a constant value specified by users. By modifying this constant value, users can exactly control the proportion of normal data described by the spherically shaped boundary. Thus, the proportion of abnormal observations can be made theoretically equal to an expected Type I error rate in Phase I process. Moreover, analogous to SVDD, the boundary can be made to describe complex structures by using some kernel functions. New multivariate control chart applying the effectiveness of the algorithm is proposed. This chart uses a monitoring statistic to characterize the degree of being an abnormal point as obtained through the proposed one-class classification. The control limit of the proposed chart is established by the radius of the boundary. The usefulness of the proposed method was demonstrated through experiments with simulated and real process data from a thin film transistor-liquid crystal display.

Keywords: control chart, mixed integer programming, one-class classification, support vector data description

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Authors: Tolulope Babawarun, Harry Ngwangwa

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The wind turbine blade may sustain structural damage from external loads such as high winds or collisions, which could compromise its aerodynamic efficiency. The wind turbine blade vibrates at significant intensities and amplitudes under these conditions. The effect of these vibrations on the dynamic flow field surrounding the blade changes the forces operating on it. The structural dynamic analysis of a small wind turbine blade is considered in this study. It entails creating a finite element model, validating the model, and doing structural analysis on the verified finite element model. The analysis is based on the structural reaction of a small-scale wind turbine blade to various loading sources. Although there are many small-scale off-shore wind turbine systems in use, only preliminary structural analysis is performed during design phases; these systems' performance under various loading conditions as they are encountered in real-world situations has not been properly researched. This will allow us to record the same Equivalent von Mises stress and deformation that the blade underwent. A higher stress contour was found to be more concentrated near the middle span of the blade under the various loading scenarios studied. The highest stress that the blade in this study underwent is within the range of the maximum stress that blade material can withstand. The maximum allowable stress of the blade material is 1,770 MPa. The deformation of the blade was highest at the blade tip. The critical speed of the blade was determined to be 4.3 Rpm with a rotor speed range of 0 to 608 Rpm. The blade's mode form under loading conditions indicates a bending mode, the most prevalent of which is flapwise bending.

Keywords: ANSYS, finite element analysis, static loading, dynamic analysis

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Authors: Vikram Munjal, Harpreet Munjal

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A few years ago we could hardly think of Libraries' strategic plan that includes the bold and amazing prediction of a mostly digital environment for a library system. However, sheer hard work by the engineers, academicians, and librarians made it feasible. However, it requires huge expenditure and now a day‘s spending for electronic resources (e-resources) have been growing much more rapidly than have the materials budgets of which such resources are usually a part. And many libraries are spending a huge amount on e-resources. Libraries today are in the midst of a profound shift toward reliance on e-resources, and this reliance seems to have deepened in recent years as libraries have shed paper journal subscriptions to help pay for online access. This has been exercised only to cater user behavior and attitudes that seem to be changing even more quickly in this dynamic scenario.

Keywords: radio frequency identification, management, scanning, barcodes, checkout and tags

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Authors: Swati Bishnoi, D. Haranath, Vinay Gupta

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In this work, we demonstrate that the power conversion efficiency (PCE) of organic solar cells (OSCs) could be improved significantly by using ZnO doped with Aluminum (Al) and Europium (Eu) as cathode buffer layer (CBL). The ZnO:Al,Eu nanoparticle layer has broadband absorption in the ultraviolet (300-400 nm) region. The Al doping contributes to the enhancement in the conductivity whereas Eu doping significantly improves emission in the visible region. Moreover, this emission overlaps with the absorption range of polymer poly [N -9′-heptadecanyl-2,7-carbazole-alt-5,5-(4′,7′-di-2-thienyl-2′,1′,3′- benzothiadiazole)] (PCDTBT) significantly and results in an enhanced absorption by the active layer and hence high photocurrent. An increase in the power conversion efficiency (PCE) of 6.8% has been obtained for ZnO: Al,Eu CBL as compared to 5.9% for pristine ZnO, in the inverted device configuration ITO/CBL/active layer/MoOx/Al. The active layer comprises of a blend of PCDTBT donor and [6-6]-phenyl C71 butyric acid methyl ester (PC71BM) acceptor. In the reference device pristine ZnO has been used as CBL, whereas in the other one ZnO:Al,Eu has been used as CBL. The role of the luminescent CBL layer is to down-shift the UV light into visible range which overlaps with the absorption of PCDTBT polymer, resulting in an energy transfer from ZnO:Al,Eu to PCDTBT polymer and the absorption by active layer is enhanced as revealed by transient spectroscopy. This enhancement resulted in an increase in the short circuit current which contributes in an increased PCE in the device employing ZnO: Al,Eu CBL. Thus, the luminescent ZnO: Al, Eu nanoparticle CBL has great potential in organic solar cells.

Keywords: cathode buffer layer, energy transfer, organic solar cell, power conversion efficiency

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Authors: S. Jamshidi, E. Feizi Ashtiani, M. Ardestani, A. Feizi Ashtiani

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Waste load allocation (WLA) strategies usually intend to find economical policies for water resource management. Water quality trading (WQT) is an approach that uses discharge permit market to reduce total environmental protection costs. This primarily requires assigning discharge limits known as total maximum daily loads (TMDLs). These are determined by monitoring organizations with respect to the receiving water quality and remediation capabilities. The purpose of this study is to compare two approaches of TMDL assignment for WQT policy in small catchment area of Haraz River, in north of Iran. At first, TMDLs are assigned uniformly for the whole point sources to keep the concentrations of BOD and dissolved oxygen (DO) at the standard level at checkpoint (terminus point). This was simply simulated and controlled by Qual2kw software. In the second scenario, TMDLs are assigned using multi objective particle swarm optimization (MOPSO) method in which the environmental violation at river basin and total treatment costs are minimized simultaneously. In both scenarios, the equity index and the WLA based on trading discharge permits (TDP) are calculated. The comparative results showed that using economically optimized TMDLs (2nd scenario) has slightly more cost savings rather than uniform TMDL approach (1st scenario). The former annually costs about 1 M$ while the latter is 1.15 M$. WQT can decrease these annual costs to 0.9 and 1.1 M$, respectively. In other word, these approaches may save 35 and 45% economically in comparison with command and control policy. It means that using multi objective decision support systems (DSS) may find more economical WLA, however its outcome is not necessarily significant in comparison with uniform TMDLs. This may be due to the similar impact factors of dischargers in small catchments. Conversely, using uniform TMDLs for WQT brings more equity that makes stakeholders not feel that much envious of difference between TMDL and WQT allocation. In addition, for this case, determination of TMDLs uniformly would be much easier for monitoring. Consequently, uniform TMDL for TDP market is recommended as a sustainable approach. However, economical TMDLs can be used for larger watersheds.

Keywords: waste load allocation (WLA), water quality trading (WQT), total maximum daily loads (TMDLs), Haraz River, multi objective particle swarm optimization (MOPSO), equity

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Authors: Doris Lacej, Eni Bushi

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Cleaning and disinfection procedures are essential for maintaining the cleanliness status of the pharmaceutical manufacturing environment particularly of the cleanrooms and sterile unit area. The Good Manufacturing Practice (GMP) Annex 1 recommendation highly requires the implementation of the standard and validated cleaning and disinfection protocols. However, environmental monitoring has shown that even a validated cleaning method with certified agents may result in the presence of atypical microorganisms’ colony that exceeds GMP limits for a specific cleanroom area. In response to this issue, this case study aims to arrive at the root cause of the microbial contamination observed in the sterile production environment in Profarma pharmaceutical industry in Albania through applying a problem-solving practical approach that ensures the appropriate sterility grade. The guidelines and literature emphasize the importance of several factors in the prevention of possible microbial contamination occurring in cleanrooms, grade A and C. These factors are integrated into a practical framework, to identify the root cause of the presence of Aspergillus Niger colony in the sterile production environment in Profarma pharmaceutical industry in Albania. In addition, the application of a semi-automatic disinfecting system such as H2O2 FOG into sterile grade A and grade C cleanrooms has been an effective solution in eliminating the atypical colony of Aspergillus Niger. Selecting the appropriate detergents and disinfectants at the right concentration, frequency, and combination; the presence of updated and standardized guidelines for cleaning and disinfection as well as continuous training of operators on these practices in accordance with the updated GMP guidelines are some of the identified factors that influence the success of achieving sterility grade. However, to ensure environmental sustainability it is important to be prepared for identifying the source of contamination and making the appropriate decision. The proposed case-based practical approach may help pharmaceutical companies to achieve sterile production and cleanliness environmental sustainability in challenging situations. Apart from the integration of valid agents and standardized cleaning and disinfection protocols according to GMP Annex 1, pharmaceutical companies must be careful and investigate the source and all the steps that can influence the results of an abnormal situation. Subsequently apart from identifying the root cause it is important to solve the problem with a successful alternative approach.

Keywords: cleanrooms, disinfectants, environmental monitoring, GMP Annex 1

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Authors: Salwa Aftab, Sehrish Riaz

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The objective of this study was to check the impact of grade sensitivity on learning motivation and academic performance of students and to remove the degree of difference that exists among students regarding the cause of their learning motivation and also to gain knowledge about this matter since it has not been adequately researched. Data collection was primarily done through the academic sector of Pakistan and was depended upon the responses given by students solely. A sample size of 208 university students was selected. Both paper and online surveys were used to collect data from respondents. The results of the study revealed that grade sensitivity has a positive relationship with the learning motivation of students and their academic performance. These findings were carried out through systematic correlation and regression analysis.

Keywords: academic performance, correlation, grade sensitivity, learning motivation, regression

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Authors: Salima Bella, Assia Belbachir, Ghalem Belalem

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This paper deals with the problem of monitoring and cleaning dirty zones of oceans using unmanned vehicles. We present a centralized cooperative architecture for unmanned aerial vehicles (UAVs) to monitor ocean regions and clean dirty zones with the help of unmanned surface vehicles (USVs). Due to the rapid deployment of these unmanned vehicles, it is convenient to use them in oceanic regions where the water pollution zones are generally unknown. In order to optimize this process, our solution aims to detect and reduce the pollution level of the ocean zones while taking into account the problem of fault tolerance related to these vehicles.

Keywords: centralized architecture, fault tolerance, UAV, USV

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

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A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

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Authors: P. Prasannakumar, L. Myoung Young, G. Seung Kye, P. Sang Hun, S. Chul Gyu

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In this paper, we discussed the coupling medium in the optoacoustic imaging. The coupling medium is placed between the scanned object and the ultrasound transducers. Water with varying temperature was used as the coupling medium. The water temperature is gradually varied between 25 to 40 degrees. This heating process is taken with care in order to avoid the bubble formation. Rise in the photoacoustic signal is noted through an unfocused transducer with frequency of 2.25 MHz as the temperature increases. The temperature rise is monitored using a NTC thermistor and the values in degrees are calculated using an embedded evaluation kit. Also the temperature is transmitted to PC through a serial communication. All these processes are synchronized using a trigger signal from the laser source.

Keywords: embedded, optoacoustic, ultrasound , unfocused transducer

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Authors: Vladimir Messerle, Alexandr Ustimenko, Oleg Lavrichshev

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To enhance the efficiency of solid fuels’ use, to decrease the fuel oil rate in the thermal power plants fuel balance and to minimize harmful emissions, a plasma technology of coal ignition, gasification and incineration is successfully applied. This technology is plasma thermochemical preparation of fuel for burning (PTCPF). In the framework of this concept, some portion of pulverized solid fuel (PF) is separated from the main PF flow and undergone the activation by arc plasma in a specific chamber with plasma torch – PFS. The air plasma flame is a source of heat and additional oxidation, it provides a high-temperature medium enriched with radicals, where the fuel mixture is heated, volatile components of coal are extracted, and carbon is partially gasified. This active blended fuel can ignite the main PF flow supplied into the furnace. This technology provides the boiler start-up and stabilization of PF flame and eliminates the necessity for addition of highly reactive fuel. In the report, a model of PTCPF, implemented as a program PlasmaKinTherm for the PFS calculation is described. The model combines thermodynamic and kinetic methods for describing the process of PTCPF in PFS. The numerical investigation of operational parameters of PFS depending on the electric power of the plasma generator and steam coal ash content revealed the temperature and velocity of gas and coal particles, and concentrations of PTCPF products dependences on the PFS length. Main mechanisms of PTCPF were disclosed. It was found that in the range of electric power of plasma generator from 40 to 100 kW high ash bituminous coal, having consumption 1667 kg/h is ignited stably. High level of temperature (1740 K) and concentration of combustible components (44%) at the PFS exit is a confirmation of it. Augmentation in power of plasma generator results displacement maxima temperatures and speeds of PTCPF products upstream (in the direction of the plasma source). The maximum temperature and velocity vary in a narrow range of values and practically do not depend on the power of the plasma torch. The numerical study of indicators of the process of PTCPF depending on the ash content in the range of its values 20-70% demonstrated that at the exit of PFS concentration of combustible components decreases with an increase in coal ash, the temperature of the gaseous products is increasing, and coal carbon conversion rate is increased to a maximum value when the ash content of 60%, dramatically decreasing with further increase in the ash content.

Keywords: coal, efficiency, ignition, numerical modeling, plasma generator, plasma-fuel system

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: M. Al-Majidi, A. Lampropoulos, A. Cundy

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Geopolymer (cement-free) concrete is the most promising green alternative to ordinary Portland cement concrete and other cementitious materials. While a range of different geopolymer concretes have been produced, a common feature of these concretes is heat curing treatment which is essential in order to provide sufficient mechanical properties in the early age. However, there are several practical issues with the application of heat curing in large-scale structures. The purpose of this study is to develop cement-free concrete without heat curing treatment. Experimental investigations were carried out in two phases. In the first phase (Phase A), the optimum content of water, polycarboxylate based superplasticizer contents and potassium silicate activator in the mix was determined. In the second stage (Phase B), the effect of ground granulated blast furnace slag (GGBFS) incorporation on the compressive strength of fly ash (FA) and Slag based geopolymer mixtures was evaluated. Setting time and workability were also conducted alongside with compressive tests. The results showed that as the slag content was increased the setting time was reduced while the compressive strength was improved. The obtained compressive strength was in the range of 40-50 MPa for 50% slag replacement mixtures. Furthermore, the results indicated that increment of water and superplasticizer content resulted to retarding of the setting time and slight reduction of the compressive strength. The compressive strength of the examined mixes was considerably increased as potassium silicate content was increased.

Keywords: fly ash, geopolymer, potassium silicate, slag

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Jhuang Jin-Jhong, Hsieh Wei-Fan

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Climate change causes natural disasters persistently. Therefore, nowadays environmental planning objective tends to the issues of respecting nature and coexisting with nature. As a result, the natural environment analysis, e.g., the analysis of topography, soil, hydrology, climate, vegetation, is highly emphasized. On the other hand, Feng Shui has been a criterion of site selection for residence in Eastern since the ancient times and has had farther influence on site selection for castles and even for temples and tombs. The primary criterion of site selection is judging the quality of Long: mountain range, Sha: nearby mountains, Shui: hydrology, Xue: foundation, Xiang: aspect, which are similar to the environmental variables of mountain range, topography, hydrology and aspect. For the reason, a lot researchers attempt to probe into the connection between the criterion of Feng Shui and environmental planning factors. Most researches only discussed with the composition and theory of space of Feng Shui, but there is no research which explained Feng Shui through the environmental field. Consequently, this study reviewed the theory of Feng Shui through the environmental planning viewpoint and assembled essential composition factors of Feng Shui. The results of this study point. From literature review and comparison of theoretical meanings, we find that the ideal principles for planning the Feng Shui environment can also be used for environmental planning. Therefore, this article uses 12 ideal environmental features used in Feng Shui to contrast the natural aspects of the environment and make comparisons with previous research and classifies the environmental factors into climate, topography, hydrology, vegetation, and soil.

Keywords: the composition of Feng Shui, environmental planning, site selection, main components of the Feng Shui environment

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Authors: Shekher Kummari, V. Sunil Kumar, K. Vengatajalabathy Gobi

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A simple, cost-effective, reusable and reagent-free electrochemical biosensor is developed with functionalized multiwall carbon nanotube paste electrode (f-CNTPE) for the sensitive and selective determination of the important chemotherapeutic drug methotrexate (MTX), which is widely used for the treatment of various cancer and autoimmune diseases. The electrochemical response of the fabricated electrode towards the detection of MTX is examined by cyclic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). CV studies have shown that f-CNTPE electrode system exhibited an excellent electrocatalytic activity towards the oxidation of MTX in phosphate buffer (0.2 M) compared with a conventional carbon paste electrode (CPE). The oxidation peak current is enhanced by nearly two times in magnitude. Applying the DPV method under optimized conditions, a linear calibration plot is achieved over a wide range of concentration from 4.0×10⁻⁷ M to 5.5×10⁻⁶ M with the detection limit 1.6×10⁻⁷ M. further, by applying the SWV method a parabolic calibration plot was achieved starting from a very low concentration of 1.0×10⁻⁸ M, and the sensor could detect as low as 2.9×10⁻⁹ M MTX in 10 s and 10 nM were detected in steady state current-time analysis. The f-CNTPE shows very good selectivity towards the specific recognition of MTX in the presence of important biological interference. The electrochemical biosensor detects MTX in-vitro directly from pharmaceutical sample, undiluted urine and human blood serum samples at a concentration range 5.0×10⁻⁷ M with good recovery limits.

Keywords: amperometry, electrochemical detection, human blood serum, methotrexate, MWCNT, SWV

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Authors: T. Ghatauray, J. Ingram, P. Holborn

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The transition from a ‘carbon rich’ fossil fuel dependent to a ‘sustainable’ and ‘renewable’ hydrogen based society will see the deployment of hydrogen fuel cells (HFC) in transport applications and in the generation of heat and power for buildings, as part of a decentralised power network. Many deployments will be low power HFCs for domestic combined heat and power (CHP) and commercial ‘transportable’ HFCs for environmental situations, such as lighting and telephone towers. For broad commercialisation of small fuel cells to be achieved there needs to be significant confidence in their safety in both domestic and environmental applications. Low power HFCs are housed in protective steel enclosures. Standard enclosures have plain rectangular ventilation openings intended for thermal management of electronics and not the dispersion of a buoyant gas. Degradation of the HFC or supply pipework in use could lead to a low-level leak and a build-up of hydrogen gas in the enclosure. Hydrogen’s wide flammable range (4-75%) is a significant safety concern, with ineffective enclosure ventilation having the potential to cause flammable mixtures to develop with the risk of explosion. Mechanical ventilation is effective at managing enclosure hydrogen concentrations, but drains HFC power and is vulnerable to failure. This is undesirable in low power and remote installations and reliable passive ventilation systems are preferred. Passive ventilation depends upon buoyancy driven flow, with the size, shape and position of ventilation openings critical for producing predictable flows and maintaining low buoyant gas concentrations. With environmentally sited enclosures, ventilation openings with pressed horizontal and angled louvres are preferred to protect the HFC and electronics inside. There is an economic cost to adding louvres, but also a safety concern. A question arises over whether the use of pressed louvre vents impairs enclosure passive ventilation performance, when compared to same opening area plain vents. Comparison small enclosure (0.144m³) tests of same opening area pressed louvre and plain vents were undertaken. A displacement ventilation arrangement was incorporated into the enclosure with opposing upper and lower ventilation openings. A range of vent areas were tested. Helium (used as a safe analogue for hydrogen) was released from a 4mm nozzle at the base of the enclosure to simulate a hydrogen leak at leak rates from 1 to 10 lpm. Helium sensors were used to record concentrations at eight heights in the enclosure. The enclosure was otherwise empty. These tests determined that the use of pressed and angled louvre ventilation openings on the enclosure impaired the passive ventilation flow and increased helium concentrations in the enclosure. High-level stratified buoyant gas layers were also found to be deeper than with plain vent openings and were within the flammable range. The presence of gas within the flammable range is of concern, particularly as the addition of the fuel cell and electronics in the enclosure would further reduce the available volume and increase concentrations. The opening area of louvre vents would need to be greater than equivalent plain vents to achieve comparable ventilation flows or alternative schemes would need to be considered.

Keywords: enclosure, fuel cell, helium, hydrogen safety, louvre vent, passive ventilation

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Authors: Sadiq J. Abou-Loukh

Abstract:

The present work deals with implementation of Petri nets, which own the perfect ability of modeling, are used to establish a fault diagnosis model. Fault diagnosis of a control system received considerable attention in the last decades. The formalism of representing neural networks based on Petri nets has been presented. Neural Petri Net (NPN) reasoning model is investigated and developed for the fault diagnosis process of electric control system. The proposed NPN has the characteristics of easy establishment and high efficiency, and fault status within the system can be described clearly when compared with traditional testing methods. The proposed system is tested and the simulation results are given. The implementation explains the advantages of using NPN method and can be used as a guide for different online applications.

Keywords: petri net, neural petri net, electric control system, fault diagnosis

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Authors: Vivek Vaishnav, Shamim Akhtar Ansari

Abstract:

Teak (Tectona grandis L.f.) belonging to plant family Lamiaceae and the most commercialized timber species is endemic to South-Asia. The adaptive fitness of the species metapopulation was evaluated through its genetic differentiation and assessing the influence of geo-climatic conditions. 290 genotypes were sampled from 29 locations of its natural distribution and the genetic data was incorporated with geo-climatic parameters. Through Bayesian approach based analysis of 43 highly polymorphic ISSR markers, six homogeneous clusters (0.8% genetic variability) were identified. The six clusters were found with the various regimes of the temperature range, i.e., I - 9.10±1.35⁰C, II -6.35±0.21⁰C, III -12.21±0.43⁰C, IV - 10.8±1.06⁰C, V - 11.67±3.04⁰C, and VI - 12.35±0.21⁰C. The population had a very high percentage of LD (21.48%) among the amplified loci possibly due to experiencing restricted gene flow as well as co-adaptation and association of distant/diverse loci/alleles as a result of the stabilized climatic conditions and countless cycles of historical recombination events on a large geological timescale. The same possibly accounts for the narrow distribution of teak as a climax species in the tropical deciduous forests of the country. The regions of strong LD in teak genome significantly associated with climatic parameters also reflect that the species is tolerant to the wide regimes of the temperature range and may possibly withstand global warming and climate change in the coming millennium.

Keywords: Bayesian analysis, inter simple sequence repeat, linkage disequilibrium, marker-geoclimatic association

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Authors: Pongsawee Supanonth

Abstract:

This research is the study of Spectrum Management and the increase in efficiency of Spectrum Utilization. It also proves that Cognitive Radio is a newer technology that will change the face of e-communications network today. This study used qualitative research methods by using in-depth interviews to collect data from a sample specific to those who work in Radio channel from 6 key informant and literature review from the related documents in online database. The result is the technique of Dynamic Spectrum Allocation that is the most suitable for Thailand. We conduct in-depth research for future purposes. Moreover, we can also develop a model that can be used in regulating and managing spectrum that is most suitable for Thailand. And also develop an important tool which can be of importance to allocation of spectrum as a natural resource appropriately. It will also guarantee quality and high benefit in a substantial way.

Keywords: cognitive radio, management of radio spectrum, spectrum management, spectrum scarcity

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Authors: Mohamed Gouda

Abstract:

Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.

Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing

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Authors: Heather E. Ewart, Keith Jensen, Rebecca N. Cliffe

Abstract:

Fragmentation and changes in the structural composition of tropical forests – as a result of intensifying anthropogenic disturbance – are increasing pressures on local biodiversity. Species with low dispersal abilities have some of the highest extinction risks in response to environmental change, as even small-scale environmental variation can substantially impact their space use and energetic balance. Understanding the implications of forest disturbance is therefore essential, ultimately allowing for more effective and targeted conservation initiatives. Here, the impact of different levels of forest disturbance on the space use, energetics, movement and behavior of 18 brown-throated sloths (Bradypus variegatus) were assessed in the South Caribbean of Costa Rica. A multi-scale framework was used to measure forest disturbance, including large-scale (landscape-level classifications) and fine-scale (within and surrounding individual home ranges) forest composition. Three landscape-level classifications were identified: primary forests (undisturbed), secondary forests (some disturbance, regenerating) and urban forests (high levels of disturbance and fragmentation). Finer-scale forest composition was determined using measurements of habitat structure and quality within and surrounding individual home ranges for each sloth (home range estimates were calculated using autocorrelated kernel density estimation [AKDE]). Measurements of forest quality included tree connectivity, density, diameter and height, species richness, and percentage of canopy cover. To determine space use, energetics, movement and behavior, six sloths in urban forests, seven sloths in secondary forests and five sloths in primary forests were tracked using a combination of Very High Frequency (VHF) radio transmitters and Global Positioning System (GPS) technology over an average period of 120 days. All sloths were also fitted with micro data-loggers (containing tri-axial accelerometers and pressure loggers) for an average of 30 days to allow for behavior-specific movement analyses (data analysis ongoing for data-loggers and primary forest sloths). Data-loggers included determination of activity budgets, circadian rhythms of activity and energy expenditure (using the vector of the dynamic body acceleration [VeDBA] as a proxy). Analyses to date indicate that home range size significantly increased with the level of forest disturbance. Female sloths inhabiting secondary forests averaged 0.67-hectare home ranges, while female sloths inhabiting urban forests averaged 1.93-hectare home ranges (estimates are represented by median values to account for the individual variation in home range size in sloths). Likewise, home range estimates for male sloths were 2.35 hectares in secondary forests and 4.83 in urban forests. Sloths in urban forests also used nearly double (median = 22.5) the number of trees as sloths in the secondary forest (median = 12). These preliminary data indicate that forest disturbance likely heightens the energetic requirements of sloths, a species already critically limited by low dispersal ability and rates of energy acquisition. Energetic and behavioral analyses from the data-loggers will be considered in the context of fine-scale forest composition measurements (i.e., habitat quality and structure) and are expected to reflect the observed home range and movement constraints. The implications of these results are far-reaching, presenting an opportunity to define a critical index of habitat connectivity for low dispersal species such as sloths.

Keywords: biodiversity conservation, forest disturbance, movement ecology, sloths

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Authors: Djelloul Benatiallah, Ali Benatiallah, Abdelkader Harouz

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Geographic Information Systems (GIS) include various methods and computer techniques to model, capture digitally, store, manage, view and analyze. Geographic information systems have the characteristic to appeal to many scientific and technical field, and many methods. In this article we will present a complete and operational geographic information system, following the theoretical principles of data management and adapting to spatial data, especially data concerning the monitoring of drinking water supply wells (DWS) Adrar region. The expected results of this system are firstly an offer consulting standard features, updating and editing beneficiaries and geographical data, on the other hand, provides specific functionality contractors entered data, calculations parameterized and statistics.

Keywords: GIS, DWS, drilling, Adrar

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Authors: Yasser O. Abualnaja1, Alexandra Pavlidou2, Taha Boksmati3, Ahmad Alharbi3, Hammad Alsulmi3, Saleh Omar Maghrabi3, Hassan Mowalad3, Rayan Mutwalli3, James H. Churchill4, Afroditi Androni2, Dionysios Ballas2, Ioannis Hatzianestis2, Harilaos Kontoyiannis2, Angeliki Konstantinopoulou2, Georgios Krokkos1, 5, Georgios Pappas2, Vassilis P. Papadopoulos2, Konstantinos Parinos2, Elvira Plakidi2, Eleni Rousselaki2, Dimitris Velaoras2, Panagiota Zachioti2, Theodore Zoulias2, Ibrahim Hoteit5.

Abstract:

The coastal areas along the Kingdom of Saudi Arabia on both the Red Sea and Arabian Gulf have been witnessing in the past decades an unprecedented economic growth and a rapid increase in anthropogenic activities. Therefore, the Saudi Arabian government has decided to frame a strategy for sustainable development of the coastal and marine environments, which comes in the context of the Vision 2030, aimed at providing the first comprehensive ‘Status Quo Assessment’ of the Kingdom’s coastal and marine environments. This strategy will serve as a baseline assessment for future monitoring activities; this baseline is relied on scientific evidence of the drivers, pressures, and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressures of the hotspots analysis, which was developed following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. Ten hotspot sites were identified, eight in the Red Sea and two in the Arabian Gulf. Thus, multidisciplinary research cruises were conducted throughout the Red Sea and the Arabian Gulf coastal and marine environments in June/July 2021 and September 2021, respectively, in order to understand the relative impact of hydrography and the various pressures on the quality of seawater and sediments. The main objective was to record the physical and biogeochemical parameters along the coastal waters of the Kingdom, tracing the dispersion of contaminants related to specific pressures. The assessment revealed the effect of hydrography on the trophic status of the southern marine coastal areas of the Red Sea. Jeddah Lagoon system seems to face significant eutrophication and pollution challenges, whereas sediments are enriched in some heavy metals in many areas of the Red Sea and the Arabian Gulf. This multidisciplinary research in the Red Sea and the Arabian Gulf coastal waters will pave the way for future detailed environmental monitoring strategies for the Saudi Arabian marine environment.

Keywords: arabian gulf, contaminants, hotspot, red sea

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Authors: Charlie Jeffkins

Abstract:

Sickle cell disease is a serious life-limiting condition which can reduce the quality of life for many patients. Public Health England (PHE), in partnership with the Sickle Cell Society (SCS), has created guidelines to prevent severe complications from sickle cell disease. Data was collected from Children’s Hospital for Wales between 15/03/21-26/03/21. Methods: A manual search of patient records for children under the care of Rocket Ward and a key term search of online records was used. Results: Penicillin prophylaxis was given at 90 days for 89%, 77% of TCDs scans were done at 2-3 years, and 72% have had a scan in the last year. 53% of patients have had discussions about hydroxycarbamide, whilst 65% have started it. PPV vaccination was documented for 19%. Conclusion: Overall, none of the four standards were reached; however, TCD uptake has improved. There is a need for better documentation of treatment and annual re-audits.

Keywords: paediatric, haematology, sickle cell, audit

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