Search results for: sensor monitoring

Authors: Mohammed Lamine Benaouda

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This paper seeks to shed light on the African continent role with the crisis of natural gas supplies to European countries, which resulted from the repercussions of the Russian-Ukrainian war, by examining the case of re-launching the Trans-Saharan Gas Pipeline project Nigeria-Algeria, and clarifying the strategic importance This project is mutually beneficial in the long run. The paper relied on the analytical and statistical method in order to find out the the impact that the project represents on the huge needs of the European gas market on the one hand, and monitoring the various economic gains for Algeria and Nigeria on the other hand, in addition, the comparative approach to assess the possible effects of the success and feasibility of the project economy for all its beneficiaries. The paper founds that the complexity has multiplied in the global energy market in general and the European one in particular, following what the world witnessed from the repercussions of the Russian-Ukrainian war, as well as the extreme importance of the poles of African countries in the arena of the international struggle over resources, which allows them a margin From maneuvering and regional and global influence in various fields. With regard to the research outcoms and the future scope, the researcher believes that the African continent, in light of international competition and conflict, as well as what the world is witnessing in terms of restoring balances of power in the current international system, will play very important roles, especially with its enormous natural and human capabilities, which enable it to Weighting future conflicts over energy and spheres of influence.

Keywords: algeria, nigeria, west africa, ECOWAS, gas supplies, russia, ukrain

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Authors: Jonghyuk Yoon, Hyoungwoon Song, Youngbae Kim, Eunju Kim

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Recently, with the rapid growth of semiconductor industry, lots of interests have been focused on after treatment system that remove the polluted gas produced from semiconductor manufacturing process, and a wet scrubber is the one of the widely used system. When it comes to mechanism of removing the gas, the polluted gas is removed firstly by chemical reaction in a reactor part. After that, the polluted gas stream is brought into contact with the scrubbing liquid, by spraying it with the liquid. Effective design of the reactor part inside the wet scrubber is highly important since removal performance of the polluted gas in the reactor plays an important role in overall performance and stability. In the present study, a CFD (Computational Fluid Dynamics) analysis was performed to figure out the thermal and flow characteristics inside unit a reactor of wet scrubber. In order to verify the numerical result, temperature distribution of the numerical result at various monitoring points was compared to the experimental result. The average error rates (12~15%) between them was shown and the numerical result of temperature distribution was in good agreement with the experimental data. By using validated numerical method, the effect of the reactor geometry on heat transfer rate was also taken into consideration. Uniformity of temperature distribution was improved about 15%. Overall, the result of present study could be useful information to identify the fluid behavior and thermal performance for various scrubber systems. This project is supported by the ‘R&D Center for the reduction of Non-CO₂ Greenhouse gases (RE201706054)’ funded by the Korea Ministry of Environment (MOE) as the Global Top Environment R&D Program.

Keywords: semiconductor, polluted gas, CFD (Computational Fluid Dynamics), wet scrubber, reactor

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Serin Darwish, Hakim Saibi, Amir Gabr

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The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

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Authors: Jaballah Jamil

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KLD (Peter Kinder, Steve Lydenberg and Amy Domini) research & analytics is an independent intermediary of social performance information that adopts an investor-pay model. KLD rating agency does not have an explicit monitoring on the rated firm which suggests that KLD ratings may not include private informations. Moreover, the incapacity of KLD to predict accurately the extra-financial rating of Enron casts doubt on the reliability of KLD ratings. Therefore, we first investigate whether KLD ratings affect investors' perception by studying the effect of KLD rating changes on firms' financial performances. Second, we study the impact of the Enron scandal on investors' perception of KLD rating changes by comparing the effect of KLD rating changes on firms' financial performances before and after the failure of Enron. We propose an empirical study that relates a number of equally-weighted portfolios returns, excess stock returns and book-to-market ratio to different dimensions of KLD social responsibility ratings. We first find that over the last two decades KLD rating changes influence significantly and negatively stock returns and book-to-market ratio of rated firms. This finding suggests that a raise in corporate social responsibility rating lowers the firm's risk. Second, to assess the Enron scandal's effect on the perception of KLD ratings, we compare the effect of KLD rating changes before and after the Enron scandal. We find that after the Enron scandal this significant effect disappears. This finding supports the view that the Enron scandal annihilates the KLD's effect on Socially Responsible Investors. Therefore, our findings may question results of recent studies that use KLD ratings as a proxy for Corporate Social Responsibility behavior.

Keywords: KLD social rating agency, investors' perception, investment decision, financial performance

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Authors: R. Posia, J. Mistry, K. Kamani

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The health screening of laboratory rodents is essential for ensuring animal health and the validity of biomedical research data. Routine health monitoring is necessary to verify the effectiveness of biosecurity and the specific pathogen free (SPF) status of the colony. The present screening was performed in barrier maintained rat (Rattus norvegicus) colony. Rats were maintained under a controlled environment and strict biosecurity in the facility. The screening was performed on quarterly bases from randomly selected animals from breeding and or maintenance colonies. Selected animals were subject to blood collection under isoflurane anaesthesia. Serum was separated from the collected blood and stored samples at -60 ± 10 °C until further use. A total of 88 samples were collected quarterly bases from animals in a year. In the serological test, enzyme-linked immunosorbent assay (ELISA) was used for screening of serum samples against sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV). ELISA kits were procured from XpressBio, USA. Test serum samples were run along with positive control, negative control serum in 96 well ELISA plates as per the procedure recommended by the vendor. Test ELISA plate reading was taken in the microplate reader. This screening observed that none of the samples was observed positive for the sialodacryoadenitis virus (SDAV), Sendai virus (SV), and Kilham’s rat virus (KRV), indicating that effectiveness of biosecurity practices followed in the rodent colony. The result of serological screening helps us to declare that our rodent colony is specifically pathogen free for these pathogens.

Keywords: biosecurity, ELISA, specific pathogen free, serological screening, serum

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Authors: Habtamu Abdisa

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Spring water is particularly valuable due to its high mineral content, which is beneficial for human health. However, anthropogenic activities usually imbalance the natural levels of its composition, which can cause adverse health effects. Regular monitoring of a naturally given environmental resource is of great concern in the world today. The spectrophotometric application is one of the best methods for qualifying and quantifying the mineral contents of environmental water samples. This research was conducted to evaluate the quality of spring water concerning its heavy metal composition. A grab sampling technique was employed to collect representative samples, including duplicates. The samples were then treated with concentrated HNO3 to a pH level below 2 and stored at 4oC. The samples were digested and analyzed for cadmium (Cd), chromium (Cr), manganese (Mn), copper (Cu), iron (Fe), and zinc (Zn) following method validation. Atomic Absorption Spectrometry (AAS) was utilized for the sample analysis. Quality control measures, including blanks, duplicates, and certified reference materials (CRMs), were implemented to ensure the accuracy and precision of the analytical results. Of the metals analyzed in the water samples, Cd and Cr were found to be below the detection limit. However, the concentrations of Mn, Cu, Fe, and Zn ranged from mean values of 0.119-0.227 mg/L, 0.142-0.166 mg/L, 0.183-0.267 mg/L, and 0.074-0.181 mg/L, respectively. Sediment analysis revealed mean concentration ranges of 348.31-429.21 mg/kg, 0.23-0.28 mg/kg, 18.73-22.84 mg/kg, 2.76-3.15 mg/kg, 941.84-1128.56 mg/kg, and 42.39-66.53 mg/kg for Mn, Cd, Cu, Cr, Fe, and Zn, respectively. The study results established that the evaluated spring water and its associated sediment met the regulatory standards and guidelines for heavy metal concentrations. Furthermore, this research can enhance the quality assurance and control processes for environmental sample analysis, ensuring the generation of reliable data.

Keywords: method validation, heavy metal, spring water, sediment, method detection limit

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Authors: Ahmet Ozcan, Onder Alparslan, Anil Sezgin, Omer Cetin

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The use of unmanned systems for different purposes has become very popular over the past decade. Expectations from these systems have also shown an incredible increase in this parallel. But meeting the demands of the tasks are often not possible with the usage of a single unmanned vehicle in a mission, so it is necessary to use multiple autonomous vehicles with different abilities together in coordination. Therefore the usage of the same type of vehicles together as a swarm is helped especially to satisfy the time constraints of the missions effectively. In other words, it allows sharing the workload by the various numbers of homogenous platforms together. Besides, it is possible to say there are many kinds of problems that require the usage of the different capabilities of the heterogeneous platforms together cooperatively to achieve successful results. In this case, cooperative working brings additional problems beyond the homogeneous clusters. In the scenario presented as an example problem, it is expected that an autonomous ground vehicle, which is lack of its position information, manage to perform point-to-point navigation without losing its way in a previously unknown labyrinth. Furthermore, the ground vehicle is equipped with very limited sensors such as ultrasonic sensors that can detect obstacles. It is very hard to plan or complete the mission for the ground vehicle by self without lost its way in the unknown labyrinth. Thus, in order to assist the ground vehicle, the autonomous air drone is also used to solve the problem cooperatively. The autonomous drone also has limited sensors like downward looking camera and IMU, and it also lacks computing its global position. In this context, it is aimed to solve the problem effectively without taking additional support or input from the outside, just benefiting capabilities of two autonomous vehicles. To manage the point-to-point navigation in a previously unknown labyrinth, the platforms have to work together coordinated. In this paper, cooperative work of heterogeneous unmanned systems is handled in an applied sample scenario, and it is mentioned that how to work together with an autonomous ground vehicle and the autonomous flying platform together in a harmony to take advantage of different platform-specific capabilities. The difficulties of using heterogeneous multiple autonomous platforms in a mission are put forward, and the successful solutions are defined and implemented against the problems like spatially distributed tasks planning, simultaneous coordinated motion, effective communication, and sensor fusion.

Keywords: unmanned systems, heterogeneous autonomous vehicles, coordination, task planning

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Authors: Emmanouil Papavasileiou, Nikos Bozionelos, Liza Howe-Walsh, Sarah Turnbull

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Purpose: The research focuses on women academics’ insecure identity at work and examines its link with generational identity. The aim is to enrich understanding of identities at work as a crucial attribute of managing academics in the context of the proliferation of managerialist controls of audit, accountability, monitoring, and performativity. Methodology: Positivist quantitative methodology was utilized. Data were collected from the Scientific Women's Academic Network (SWAN) Charter. Responses from 155 women academics based in the British Higher Education system were analysed. Findings: Analysis showed high prevalence of strong imposter feelings among participants, suggesting high insecurity at work among women academics in the United Kingdom. Generational identity was related to imposter feelings. In particular, Millennials scored significantly higher than the other generational groups. Research implications: The study shows that imposter feelings are variously manifested among the prevalent generations of women academics, while generational identity is a significant antecedent of such feelings. Research limitations: Caution should be exercised in generalizing the findings to national cultural contexts beyond the United Kingdom. Practical and social implications: Contrary to popular depictions of Millennials as self-centered, narcissistic, materialistic and demanding, women academics who are members of this generational group appear significantly more insecure than the preceding generations. Value: The study provides insightful understandings into women academics’ identity at work as a function of generational identity, and provides a fruitful avenue for further research within and beyond this gender group and profession.

Keywords: academics, generational diversity, imposter feelings, United Kingdom, women, work identity

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Authors: Parisa Mansour

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Cystic fibrosis (CF) is one of the most common autosomal recessive diseases among whites. It mostly affects the lungs, causing infections and inflammation that account for 90% of deaths in CF patients. Because of this high variability in clinical presentation and organ involvement, investigating treatment responses and evaluating lung changes over time is critical to preventing CF progression. High-resolution computed tomography (HRCT) greatly facilitates the assessment of lung disease progression in CF patients. Recently, artificial intelligence was used to analyze chest CT scans of CF patients. In this paper, we propose a convolutional neural network (CNN) approach to classify CF lung patterns in HRCT images. The proposed network consists of two convolutional layers with 3 × 3 kernels and maximally connected in each layer, followed by two dense layers with 1024 and 10 neurons, respectively. The softmax layer prepares a predicted output probability distribution between classes. This layer has three exits corresponding to the categories of normal (healthy), bronchitis and inflammation. To train and evaluate the network, we constructed a patch-based dataset extracted from more than 1100 lung HRCT slices obtained from 45 CF patients. Comparative evaluation showed the effectiveness of the proposed CNN compared to its close peers. Classification accuracy, average sensitivity and specificity of 93.64%, 93.47% and 96.61% were achieved, indicating the potential of CNNs in analyzing lung CF patterns and monitoring lung health. In addition, the visual features extracted by our proposed method can be useful for automatic measurement and finally evaluation of the severity of CF patterns in lung HRCT images.

Keywords: HRCT, CF, cystic fibrosis, chest CT, artificial intelligence

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Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

Procedia PDF Downloads 987

Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Massimiliano Condotta, Paolo Ruggeri, Chiara Scanagatta, Giovanni Borga

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Architects and urban planners, when designing and renewing cities, have to face a complex set of problems, including the issues of noise and air pollution which are considered as hot topics (i.e., the Clean Air Act of London and the Soundscape definition). It is usually taken for granted that these problems go by together because the noise pollution present in cities is often linked to traffic and industries, and these produce air pollutants as well. Traffic congestion can create both noise pollution and air pollution, because NO₂ is mostly created from the oxidation of NO, and these two are notoriously produced by processes of combustion at high temperatures (i.e., car engines or thermal power stations). We can see the same process for industrial plants as well. What have to be investigated – and is the topic of this paper – is whether or not there really is a correlation between noise pollution and air pollution (taking into account NO₂) in urban areas. To evaluate if there is a correlation, some low-cost methodologies will be used. For noise measurements, the OpeNoise App will be installed on an Android phone. The smartphone will be positioned inside a waterproof box, to stay outdoor, with an external battery to allow it to collect data continuously. The box will have a small hole to install an external microphone, connected to the smartphone, which will be calibrated to collect the most accurate data. For air, pollution measurements will be used the AirMonitor device, an Arduino board to which the sensors, and all the other components, are plugged. After assembling the sensors, they will be coupled (one noise and one air sensor) and placed in different critical locations in the area of Mestre (Venice) to map the existing situation. The sensors will collect data for a fixed period of time to have an input for both week and weekend days, in this way it will be possible to see the changes of the situation during the week. The novelty is that data will be compared to check if there is a correlation between the two pollutants using graphs that should show the percentage of pollution instead of the values obtained with the sensors. To do so, the data will be converted to fit on a scale that goes up to 100% and will be shown thru a mapping of the measurement using GIS methods. Another relevant aspect is that this comparison can help to choose which are the right mitigation solutions to be applied in the area of the analysis because it will make it possible to solve both the noise and the air pollution problem making only one intervention. The mitigation solutions must consider not only the health aspect but also how to create a more livable space for citizens. The paper will describe in detail the methodology and the technical solution adopted for the realization of the sensors, the data collection, noise and pollution mapping and analysis.

Keywords: air quality, data analysis, data collection, NO₂, noise mapping, noise pollution, particulate matter

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Authors: Terentes Printzios Dimitrios, Loanna Gourgouli, Vlachopoulos Charalambos

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Aims: Atrial fibrillation (AF) remains one of the major causes of stroke, heart failure, sudden death and cardiovascular morbidity. Ablation techniques are becoming more appealing after the latest results of randomized trials showing the overall clinical benefit. On the other hand, imaging techniques and the frontier application of 3D printing are emerging as a valuable ally for cardiac procedures. However, no randomized trial has directly assessed the impact of preprocedural imaging and especially 3D printing guidance for AF ablation. The present study is designed to investigate for the first time the effect of 3D printing of the heart on the safety and effectiveness of the ablation procedure. Methods and design: The 3D-GALA trial is a randomized, open-label, controlled, multicentre clinical trial of 2 parallel groups designed to enroll a total of 100 patients undergoing ablation using cryo-balloon for paroxysmal and persistent AF. Patients will be randomized with a patient allocation ratio of 1: 1 to preprocedural MRI scan of the heart and 3D printing of left atrium and pulmonary veins and cryoablation versus standard cryoablation without imaging. Patients will be followed up to 6 months after the index procedure. The primary outcome measure is the reduction of radiation dose and contrast amount during pulmonary veins isolation. Secondary endpoints will include the percentage of atrial fibrillation relapse at 24h-Holter electrocardiogram monitoring at 6 months after initial treatment. Discussion: To our knowledge, the 3D-GALA trial will be the first study to provide evidence about the clinical impact of preprocedural imaging and 3D printing before cryoablation.

Keywords: atrial fibrillation, cardiac MRI, cryoablation, 3-d printing

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Authors: Mukisa Daphine Letisha

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Plea bargaining, a practice often associated with more developed legal systems, has emerged as a significant tool within Uganda's criminal justice system despite its absence in formal legal structures inherited from its colonial past. Initiated in 2013 with the aim of reducing case backlogs, expediting trials, and addressing prison congestion, plea bargaining reflects a pragmatic response to systemic challenges. While rooted in international statutes and domestic constitutional provisions, its implementation relies heavily on the Judicature (Plea Bargain) Rules of 2016, which outline procedural requirements and safeguards. Advocates argue that plea bargaining has yielded tangible benefits, including a reduction in case backlog and efficient allocation of resources, with notable support from judicial and prosecutorial authorities. Case examples demonstrate successful outcomes, with accused individuals benefitting from reduced sentences in exchange for guilty pleas. However, challenges persist, including procedural irregularities, inadequate statutory provisions, and concerns about coercion and imbalance of power between prosecutors and accused individuals. To enhance efficacy, recommendations focus on establishing monitoring mechanisms, stakeholder training, and public sensitization campaigns. In conclusion, while plea bargaining offers potential advantages in streamlining Uganda's criminal justice system, addressing its challenges requires careful consideration of procedural safeguards and stakeholder engagement to ensure fairness and integrity in the administration of justice.

Keywords: plea-bargaining, criminal-justice system, uganda, efficacy

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Authors: Nashed Atef Nashed Farag

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Introduction: Reporting adverse events following vaccination remains a challenge. WHO has mandated pharmacovigilance centers around the world to submit Adverse Events Following Immunization (AEFI) reports from different countries to a large electronic database of adverse drug event data called Vigibase. Despite sufficient information about AEFIs on Vigibase, they are not available to the general public. However, the WHO has an alternative website called VigiAccess, an open-access website that serves as an archive for reported adverse reactions and AEFIs. The aim of the study was to establish a reporting model for a number of commonly used vaccines in the VigiAccess system. Methods: On February 5, 2018, VigiAccess comprehensively searched for ESSI reports on the measles vaccine, oral polio vaccine (OPV), yellow fever vaccine, pneumococcal vaccine, rotavirus vaccine, meningococcal vaccine, tetanus vaccine, and tuberculosis vaccine (BCG). These are reports from all pharmacovigilance centers around the world since they joined the WHO Drug Monitoring Program. Results: After an extensive search, VigiAccess found 9,062 AEFIs from the measles vaccine, 185,829 AEFIs from the OPV vaccine, 24,577 AEFIs from the yellow fever vaccine, 317,208 AEFIs from the pneumococcal vaccine, 73,513 AEFIs from the rotavirus vaccine, and 145,447 AEFIs from meningococcal cal vaccine, 22,781 EI FI vaccines against tetanus and 35,556 BCG vaccines against AEFI. Conclusion: The study found that among the eight vaccines examined, pneumococcal vaccines were associated with the highest number of AEFIs, while measles vaccines were associated with the fewest AEFIs.

Keywords: surgical approach, anatomical approach, decompression, axillary nerve, quadrangular space adverse events following immunization, cameroon, COVID-19 vaccines, nOPV, ODK vaccines, adverse reactions, VigiAccess, adverse event reporting

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Authors: David Ryan, Martin Breugst, Turlough Downes, Peter A. Byrne, Gerard P. McGlacken

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An ambident nucleophile is a nucleophile that possesses two or more distinct nucleophilic sites that are linked through resonance and are effectively “in competition” for reaction with an electrophile. Examples include enolates, pyridone anions, and nitrite anions, among many others. Reactions of ambident nucleophiles and electrophiles are extremely prevalent at all levels of organic synthesis. The principle of hard and soft acids and bases (the “HSAB principle”) is most commonly cited in the explanation of selectivities in such reactions. Although this rationale is pervasive in any discussion on ambident reactivity, the HSAB principle has received considerable criticism. As a result, the principle’s supplantation has become an area of active interest in recent years. This project focuses on developing a model for rationalizing ambident reactivity. Presented here is an approach that incorporates computational calculations and experimental kinetic data to construct Gibbs energy profile diagrams. The preferred site of alkylation of nitrite anion with a range of ‘hard’ and ‘soft’ alkylating agents was established by ¹H NMR spectroscopy. Pseudo-first-order rate constants were measured directly by ¹H NMR reaction monitoring, and the corresponding second-order constants and Gibbs energies of activation were derived. These, in combination with computationally derived standard Gibbs energies of reaction, were sufficient to construct Gibbs energy wells. By representing the ambident system as a series of overlapping Gibbs energy wells, a more intuitive picture of ambident reactivity emerges. Here, previously unexplained switches in reactivity in reactions involving closely related electrophiles are elucidated.

Keywords: ambident, Gibbs, nucleophile, rates

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Authors: Abdullah Al-Alaian, Ahmad Al-Enzi, Hasan Al-Herz, Ahmad Bakri, Shant Tatorian, Amr Nounou

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Kuwait is a country that has an imbalanced economy since most of its national outcome comes from the oil trade. It is so risky for a country to be dependent on a single source for income, and this increases the need to diversify its economy. In addition, according to the Public Authority for Industry, the contribution of the industrial sector to the current Gross Domestic Product (GDP) of Kuwait is low which is about 4.33%. Therefore, the development of the industrial sector can be one of the means to diversify the economy and increase the industry's contribution to the national outcome. This is in accordance with Kuwait’s vision of 2035 which aims at increasing the contribution of the industrial sector to the GDP to 12%. In order to do so, this study aims at proposing a strategic plan that will accomplish certain objectives when implemented. It is based on analyzing the industrial sectors in Kuwait taking into consideration studying the strengths, weaknesses, opportunities, and threats facing them. At the same time, it tends to gain from the experience of leading models and neighboring countries regarding the development of the industrial sector. In this study, the SWOT analysis technique will be conducted on all industrial sectors based on evaluation criteria in which it is determined whether any of them has a potential for improvement or not. In other words, it is determined whether the sectors are able to compete locally, regionally, or globally. Based on the results of the SWOT analysis, certain sectors will be chosen, assessed based on an assessment scheme, and their potentials for improvement will be aligned with the overall objectives. To ensure the achievement of the study’s objectives, an action plan will be proposed regarding recommendations for the related authorities, and for entrepreneurs. In addition, monitoring tools are going to be provided for the purpose of periodically checking the progress made in the implementation of the plan.

Keywords: industrial sector, SWOT analysis, productivity, competitiveness, GDP, Kuwait, economy

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Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

Procedia PDF Downloads 101

Authors: Deepanjali Gurav, Kun Qian

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In-vitro metabolic diagnosis relies on designed materials-based analytical platforms for detection of selected metabolites in biological samples, which has a key role in disease detection and therapeutic evaluation in clinics. However, the basic challenge deals with developing a simple approach for metabolic analysis in bio-samples with high sample complexity and low molecular abundance. In this work, we report a designer plasmonic nanoshells based platform for direct detection of small metabolites in clinical samples for in-vitro metabolic diagnostics. We first synthesized a series of plasmonic core-shell particles with tunable nanoshell structures. The optimized plasmonic nanoshells as new matrices allowed fast, multiplex, sensitive, and selective LDI MS (Laser desorption/ionization mass spectrometry) detection of small metabolites in 0.5 μL of bio-fluids without enrichment or purification. Furthermore, coupling with isotopic quantification of selected metabolites, we demonstrated the use of these plasmonic nanoshells for disease detection and therapeutic evaluation in clinics. For disease detection, we identified patients with postoperative brain infection through glucose quantitation and daily monitoring by cerebrospinal fluid (CSF) analysis. For therapeutic evaluation, we investigated drug distribution in blood and CSF systems and validated the function and permeability of blood-brain/CSF-barriers, during therapeutic treatment of patients with cerebral edema for pharmacokinetic study. Our work sheds light on the design of materials for high-performance metabolic analysis and precision diagnostics in real cases.

Keywords: plasmonic nanoparticles, metabolites, fingerprinting, mass spectrometry, in-vitro diagnostics

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Authors: May Fadheel Estephan, Richard Perks

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Context: Cancer is a serious health concern that affects millions of people worldwide. Early detection and treatment are essential for improving patient outcomes. However, current methods for cancer detection have limitations, such as low sensitivity and specificity. Research Aim: The aim of this study was to develop an optical sensor for cancer detection using elastic light scattering spectroscopy (ELSS). ELSS is a noninvasive optical technique that can be used to characterize the size and concentration of particles in a solution. Methodology: An optical probe was fabricated with a 100-μm-diameter core and a 132-μm centre-to-centre separation. The probe was used to measure the ELSS spectra of polystyrene spheres with diameters of 2, 0.8, and 0.413 μm. The spectra were then analysed to determine the size and concentration of the spheres. Findings: The results showed that the optical probe was able to differentiate between the three different sizes of polystyrene spheres. The probe was also able to detect the presence of polystyrene spheres in suspension concentrations as low as 0.01%. Theoretical Importance: The results of this study demonstrate the potential of ELSS for cancer detection. ELSS is a noninvasive technique that can be used to characterize the size and concentration of cells in a tissue sample. This information can be used to identify cancer cells and assess the stage of the disease. Data Collection: The data for this study were collected by measuring the ELSS spectra of polystyrene spheres with different diameters. The spectra were collected using a spectrometer and a computer. Analysis Procedures: The ELSS spectra were analysed using a software program to determine the size and concentration of the spheres. The software program used a mathematical algorithm to fit the spectra to a theoretical model. Question Addressed: The question addressed by this study was whether ELSS could be used to detect cancer cells. The results of the study showed that ELSS could be used to differentiate between different sizes of cells, suggesting that it could be used to detect cancer cells. Conclusion: The findings of this research show the utility of ELSS in the early identification of cancer. ELSS is a noninvasive method for characterizing the number and size of cells in a tissue sample. To determine cancer cells and determine the disease's stage, this information can be employed. Further research is needed to evaluate the clinical performance of ELSS for cancer detection.

Keywords: elastic light scattering spectroscopy, polystyrene spheres in suspension, optical probe, fibre optics

Procedia PDF Downloads 82

Authors: Rajiv Ratan Singh, Sachin Kumar Tripathi, Pradeep Kumar Yadav

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The timely evaluation, diagnosis, and treatment of people who have been exposed to toxic chemicals is a crucial component of emergency poison management in the medical field. The various substances that can poison include chemicals, medications, and naturally occurring poisons. The toxicology of the particular drug involved, as well as the symptoms and indicators of poisoning, must be thoroughly understood to handle poisoning emergencies effectively. One of the most important aspects of emergency poison management in medicine is the prompt examination, diagnosis, and treatment of persons who have been exposed to dangerous substances. To properly manage poisoning crises, one must have a good understanding of the toxicology of the particular medication concerned, as well as the signs and indicators of poisoning. Emergency management of poisoning includes not only prompt medical attention but also patient education, follow-up care, and monitoring for any long-term consequences. To achieve the greatest results for patients, the management of poisoning is a complicated and dynamic process that calls for collaboration between medical professionals, first responders, and toxicologists. All poisoned patients who present to the emergency room are assessed and diagnosed based on a collection of symptoms and a biochemical diagnosis, and they are then provided targeted, specialized treatment for the toxin identified. This article focuses on the loxodromic strategy as the primary method of treatment for poisoned patients. The authors of this article conclude that mortality and morbidity can be reduced if patients visit the emergency room promptly and receive targeted treatment.

Keywords: antidotes, blood poisoning, emergency medicine, gastric lavage, medico-legal aspects, patient care

Procedia PDF Downloads 102

Authors: A. ElZawam, D. McLean, A. Tibary

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In alpaca, age at puberty is variable and the factors regulating the pattern of puberty and sexual maturation are a subject of controversy. Plasma testosterone level is often used as an indicator of sexual maturity. Our hypothesis is that hCG treatment will cause an increase in testosterone level that is correlated with animal age. The specific aim was to investigate the testicular tissue response to a single hCG injection by monitoring the serum testosterone concentration. Eighty four (n=84) males ranging in age from 6 to 60 months were used. Alpacas were grouped based on their ages into 15 groups. Each group had three to five male animals. Blood samples were collected from the jugular vein before treatment with hCG and 2 hours after intravenous administration of 3000 IU of hCG (Chorulon®). The serum was harvested and stored at -20ºC until the analysis. The effect of age on basal testosterone level and response to hCG treatment was evaluated by Analysis of Variance. As a result, basal serum testosterone concentrations were very low (<0.1ng/ml) until 9 months of age. Although basal serum testosterone concentrations increased steadily with age there was a significant variation amongst males within the same age group. Administration of 3000 IU of hCG, resulted in an average increase of 50% (P<0.05) in serum testosterone concentration after 2 hours. The percentage increase in serum testosterone in response to hCG stimulation varied from 51 to 81%. There was no correlation between the degree of response and age. However, the response to hCG injection presented two modes of increase depending on the age of animals. The first mode occurred at ages 9 to 14 months and the second mode was observed between 22 and 36 months. In conclusion, our results suggest that testicular growth and sensitivity to LH stimulation may be bimodal in the male alpaca with a rapid increase in growth and sensitivity between 9 and 14 months of age and a second phase of increased responsiveness after 21 months of ages.

Keywords: alpaca, testosterone, hCG, animal science

Procedia PDF Downloads 571

Authors: Tri Nopiyanto, Rahardhyani Dwiannisa, Arief Ismaryanto

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One main issue for a certain region in order to achieve development is if the government that consists of the executive, legislative and judicial board are able to work together. However, there are certain conditions that these boards are the sources of conflict, especially between the executive and legislative board. One of the example of the conflict is between the Local Government and Legislative Board (DPRD) in the Province of Jakarta in 2015. The cause of this conflict is because of the occurrence of pokir (pokok pikiran or ideas of budgeting). Pokir is driven by a budgeting plan that is arranged by DPRD that is supposed to be sourced from the aspiration of the people and delivered 5 months before the legalization of Local Government Budget (APBD), but the current condition in Jakarta is that pokir is a project by DPRD members itself and delivered just 3 days before the legalization in order to facilitate the interests of the members of the legislative. This paper discusses how pokir happens and what factors caused it. This paper uses political budgeting theory by Andy Norton and Diane Elson to analyze the issue. The method used in this paper is qualitative to collect the data and solve the problem of this research. The methods involved are in depth interview, experimental questionnaire, and literature studies. Results of this research are that Pokir occurs because of the distribution of power among DPRD members, between parties, executive, and legislative board. Beside that, Pokir also occurs because of the lack of the people’s participation in budgeting process and monitoring. Other than that, this paper also found that pokir also happens because of the budgeting system that is not able to provide a clean budgeting process, so it enables the creation of certain slots to add pokir into the budgets. Pokir also affects the development of Jakarta that goes through stagnation. This research recommends the implementation of e-budgeting to prevent the occurrence of pokir itself in the Province of Jakarta.

Keywords: legislative and executive board, Jakarta, political budgeting, Pokir

Procedia PDF Downloads 272

Authors: Daofan Guo, Dong Yang

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For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

Procedia PDF Downloads 147

Authors: Yoshifumi Hino

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An infinitely repeated prisoner’s dilemma is a typical model that represents teamwork situation. If both players choose costly actions and contribute to the team, then both players are better off. However, each player has an incentive to choose a selfish action. We analyze the game under costly observation. Each player can observe the action of the opponent only when he pays an observation cost in that period. In reality, teamwork situations are often costly observation. Members of some teams sometimes work in distinct rooms, areas, or countries. In those cases, they have to spend their time and money to see other team members if they want to observe it. The costly observation assumption makes the cooperation difficult substantially because the equilibrium must satisfy the incentives not only on the action but also on the observational decision. Especially, it is the most difficult to cooperate each other when the stage-game is prisoner's dilemma because players have to communicate through only two actions. We examine whether or not players can cooperate each other in prisoner’s dilemma under costly observation. Specifically, we check whether symmetric Pareto efficient payoff vectors in repeated prisoner’s dilemma can be approximated by sequential equilibria or not (efficiency result). We show the efficiency result without any randomization device under certain circumstances. It means that players can cooperate with each other without any randomization device even if the observation is costly. Next, we assume that public randomization device is available, and then we show that any feasible and individual rational payoffs in prisoner’s dilemma can be approximated by sequential equilibria under a specific situation (folk theorem). It implies that players can achieve asymmetric teamwork like leadership situation when public randomization device is available.

Keywords: cost observation, efficiency, folk theorem, prisoner's dilemma, private monitoring, repeated games.

Procedia PDF Downloads 241

Authors: Sarah M. Asar, Nabeel M. Elhady

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Egypt’s current per capita water share indicates that the country suffers and has been suffering from water poverty. The abundant utilization of turfgrass in Egypt’s new urban settlements, the reliance on freshwater for irrigation, and the inadequate plant selection increase the water demand in such settlements. Decreasing the surface area of turfgrass by using alternative landscape features such as mulching, using ornamental low-maintenance plants, increasing pathways, etc., could significantly decrease the water demand of urban landscapes. The use of Ammochloa palaestina, Cenchrus crientalis (Oriental Fountain Grass), and Cistus parviflorus (with water demands of approximately 0.005m³/m²/day) as alternatives for Cynodon dactylon (0.01m³/m²/day), which is the most commonly used grass species in Egypt’s landscape, could decrease an area’s water demand by approximately 40-50%. Moreover, creating hydro-zones of similar water demanding plants would enable irrigation facilitation rather than the commonly used uniformed irrigation. Such a practice could further reduce water consumption by 15-20%. These results are based on a case-study analysis of one of Egypt’s relatively new urban settlements, Al-Rehab. Such results emphasize the importance of utilizing native, drought-tolerant vegetation in the urban landscapes of Egypt to reduce irrigation demands. Furthermore, proper implementation, monitoring, and maintenance of automated irrigation systems could be an important factor in a space’s efficient water use. As most new urban settlements in Egypt adopt sprinkler and drip irrigation systems, the lack of maintenance leads to the manual operation of such systems, and, thereby, excessive irrigation occurs.

Keywords: alternative landscape, native plants, efficient irrigation, low water demand

Procedia PDF Downloads 78

Authors: Ahmed Elaksher, Islam Omar

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For many years, Mars surface has been a mystery for scientists. Lately with the help of geospatial data and photogrammetric procedures researchers were able to capture some insights about this planet. Two of the most imperative data sources to explore Mars are the The High Resolution Imaging Science Experiment (HiRISE) and the Mars Orbiter Laser Altimeter (MOLA). HiRISE is one of six science instruments carried by the Mars Reconnaissance Orbiter, launched August 12, 2005, and managed by NASA. The MOLA sensor is a laser altimeter carried by the Mars Global Surveyor (MGS) and launched on November 7, 1996. In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images for generating a more accurate and trustful surface of Mars. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. In this project, we employed three different 3D to 2D transformation models. These are the parallel projection (3D affine) transformation model; the extended parallel projection transformation model; the Direct Linear Transformation (DLT) model. A set of tie-points was digitized from both datasets. These points were split into two sets: Ground Control Points (GCPs), used to evaluate the transformation parameters using least squares adjustment techniques, and check points (ChkPs) to evaluate the computed transformation parameters. Results were evaluated using the RMSEs between the precise horizontal coordinates of the digitized check points and those estimated through the transformation models using the computed transformation parameters. For each set of GCPs, three different configurations of GCPs and check points were tested, and average RMSEs are reported. It was found that for the 2D transformation models, average RMSEs were in the range of five meters. Increasing the number of GCPs from six to ten points improve the accuracy of the results with about two and half meters. Further increasing the number of GCPs didn’t improve the results significantly. Using the 3D to 2D transformation parameters provided three to two meters accuracy. Best results were reported using the DLT transformation model. However, increasing the number of GCPS didn’t have substantial effect. The results support the use of the DLT model as it provides the required accuracy for ASPRS large scale mapping standards. However, well distributed sets of GCPs is a key to provide such accuracy. The model is simple to apply and doesn’t need substantial computations.

Keywords: mars, photogrammetry, MOLA, HiRISE

Procedia PDF Downloads 59

Authors: John Okanda Okwaro

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Carbon (IV) oxide (CO₂) is emitted majorly from fossil fuel combustion and industrial production. The sources of interest of carbon (IV) oxide in the study area are mining activities, transport systems, and industrial processes. This study is aimed at building models that will help in monitoring the emissions within the study area. Three scenarios were discussed, namely: pessimistic scenario, business-as-usual scenario, and optimistic scenario. The result showed that there was a reduction in carbon dioxide concentration by approximately 50.5 ppm between March 2020 and January 2021 inclusive. This is majorly due to reduced human activities that led to decreased consumption of energy. Also, the CO₂ concentration trend follows the business-as-usual scenario (BAU) path. From the models, the pessimistic, business-as-usual, and optimistic scenarios give CO₂ concentration of about 545.9 ppm, 408.1 ppm, and 360.1 ppm, respectively, on December 31st, 2021. This research helps paint the picture to the policymakers of the relationship between energy sources and CO₂ emissions. Since the reduction in CO₂ emission was due to decreased use of fossil fuel as there was a decrease in economic activities, then if Kenya relies more on green energy than fossil fuel in the post-COVID-19 period, there will be more CO₂ emission reduction. That is, the CO₂ concentration trend is likely to follow the optimistic scenario path, hence a reduction in CO₂ concentration of about 48 ppm by the end of the year 2021. This research recommends investment in solar energy by energy-intensive companies, mine machinery and equipment maintenance, investment in electric vehicles, and doubling tree planting efforts to achieve the 10% cover.

Keywords: forecasting, greenhouse gas, green energy, hierarchical data format

Procedia PDF Downloads 168