Search results for: forensic case

Authors: Elena Listo Ubeda, Miguel Marchamalo Sacristan

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The demand for water doubles every twenty years, at a rate which is twice as fast as the world´s population growth. Despite it´s great importance, water is one of the most degraded natural resources in the world, mainly because of the reduction of natural vegetation coverage, population growth, contamination and changes in the soil use which reduces its capacity to collect water. This situation is especially serious in Central America, as reflected in the Human Development reports. The objective of this project is to assist in the improvement of water production and quality in Central America. In order to do these two watersheds in Costa Rica were selected as experiments: that of the Virilla-Durazno River, located in the extreme north east of the central valley which has an Atlantic influence; and that of the Jabillo River, which flows directly into the Pacific. The Virilla river watershed is located over andisols, and that of the Jabillo River is over alfisols, and both are of great importance for water supply to the Greater Metropolitan Area and the future tourist resorts respectively, as well as for the production of agriculture, livestock and hydroelectricity. The hydrological reaction in different soil-cover complexes, varying from the secondary forest to natural vegetation and degraded pasture, was analyzed according to the evaluation of the properties of the soil, infiltration, soil compaction, as well as the effects of the soil cover complex on erosion, calculated by the C factor of the Revised Universal Soil Loss Equation (RUSLE). A water balance was defined for each watershed, in which the volume of water that enters and leaves were estimated, as well as the evapotranspiration, runoff, and infiltration. Two future scenarios, representing the implementation of reforestation and deforestation plans, were proposed, and were analyzed for the effects of the soil cover complex on the water balance in each case. The results obtained show an increase of the ground water recharge in the humid forest areas, and an extension of the study of the dry areas is proposed since the ground water recharge here is diminishing. These results are of great significance for the planning, design of Payment Schemes for Environmental Services and the improvement of the existing water supply systems. In Central America spatial planning is a priority, as are the watersheds, in order to assess the water resource socially and economically, and securing its availability for the future.

Keywords: Costa Rica, infiltration, soil, water

Procedia PDF Downloads 383

Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Nina Ponikvar, Katja Zajc Kejžar

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While the positive impacts of heritage on a broad societal spectrum have long been recognized and measured, the economic effects of the heritage sector are often less visible and frequently underestimated. At macro level, economic effects are usually studied based on one of the two mainstream approach, i.e. either the multiplier approach or the value chain approach. Consequently, there is limited comparability of the empirical results due to the use of different methodological approach in the literature. Furthermore, it is also not clear on which criteria the used approach was selected. Our aim is to bring the attention to the difference in the scope of effects that are encompassed by the two most frequent methodological approaches to valuation of economic effects of cultural heritage on macroeconomic level, i.e. the multiplier approach and the value chain approach. We show that while the multiplier approach provides a systematic, theory-based view of economic impacts but requires more data and analysis, the value chain approach has less solid theoretical foundations and depends on the availability of appropriate data to identify the contribution of cultural heritage to other sectors. We conclude that the multiplier approach underestimates the economic impact of cultural heritage, mainly due to the narrow definition of cultural heritage in the statistical classification and the inability to identify part of the contribution of cultural heritage that is hidden in other sectors. Yet it is not possible to clearly determine whether the value chain method overestimates or underestimates the actual economic impact of cultural heritage since there is a risk that the direct effects are overestimated and double counted, but not all indirect and induced effects are considered. Accordingly, these two approaches are not substitutes but rather complementary. Consequently, a direct comparison of the estimated impacts is not possible and should not be done due to the different scope. To illustrate the difference of the impact assessment of the cultural heritage, we apply both approaches to the case of Slovenia in the 2015-2022 period and measure the economic impact of cultural heritage sector in terms of turnover, gross value added and employment. The empirical results clearly show that the estimation of the economic impact of a sector using the multiplier approach is more conservative, while the estimates based on value added capture a much broader range of impacts. According to the multiplier approach, each euro in cultural heritage sector generates an additional 0.14 euros in indirect effects and an additional 0.44 euros in induced effects. Based on the value-added approach, the indirect economic effect of the “narrow” heritage sectors is amplified by the impact of cultural heritage activities on other sectors. Accordingly, every euro of sales and every euro of gross value added in the cultural heritage sector generates approximately 6 euros of sales and 4 to 5 euros of value added in other sectors. In addition, each employee in the cultural heritage sector is linked to 4 to 5 jobs in other sectors.

Keywords: economic value of cultural heritage, multiplier approach, value chain approach, indirect effects, slovenia

Procedia PDF Downloads 74

Authors: Mary Rosa Espinosa-Ochoa

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The study of overgeneralization in inflectional morphology provides evidence for understanding how a child's mind works when applying linguistic patterns in a novel way. High-frequency inflectional forms in the input cause inappropriate use in contexts related to lower-frequency forms. Children learn verbs as lexical items and new forms develop only gradually, around their second year: most of the utterances that children produce are closely related to what they have previously produced. Spanish has a complex verbal system that inflects for person, mood, and tense. Approximately 200 verbs are irregular, and bare roots always require an inflected form, which represents a challenge for the memory. The aim of this research is to investigate i) what kinds of overgeneralization errors children make in verb production, ii) to what extent these errors are related to verb forms previously produced, and iii) whether the overgeneralized verb components are also frequent in children’s linguistic inventory. It consists of a high-density longitudinal study of a middle-class girl (1;11,24-2;02,24) from Mexico City, whose utterances were recorded almost daily for three months to compile a unique corpus in the Spanish language. Of the 358 types of inflected verbs produced by the child, 9.11% are overgeneralizations. Not only are inflected forms (verbal and pronominal clitics) overgeneralized, but also verbal roots. Each of the forms can be traced to previous utterances, and they show that the child is detecting morphological patterns. Neither verbal roots nor inflected forms are associated with high frequency patterns in her own speech. For example, the child alternates the bare roots of an irregular verb, cáye-te* and cáiga-te* (“fall down”), to express the imperative of the verb cá-e-te (fall down.IMPERATIVE-PRONOMINAL.CLITIC), although cay-ó (PAST.PERF.3SG) is the most frequent form of her previous complete inventory, and the combined frequency of caer (INF), cae (PRES.INDICATIVE.3SG), and caes (PRES.INDICATIVE.2SG) is the same as that of as caiga (PRES.SUBJ.1SG and 3SG). These results provide evidence that a) two forms of the same verb compete in the child’s memory, and b) although the child uses her own inventory to create new forms, these forms are not necessarily frequent in her memory storage, which means that her mind is more sensitive to external stimuli. Language acquisition is a developing process, given the sensitivity of the human mind to linguistic interaction with the outside world.

Keywords: inflection, morphology, child language acquisition, Spanish

Procedia PDF Downloads 100

Authors: Xin Jiao, Xin Zhang, Jian Fan, Zhenwei Cai, Yiming Xu

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Tower cranes play a crucial role in the construction industry, facilitating the vertical and horizontal movement of materials and aiding in building construction, especially for high-rise structures. However, tower crane accidents can lead to severe consequences, highlighting the importance of effective safety management and inspection. This paper presents an innovative approach to tower crane inspection utilizing Unmanned Aerial Vehicles (UAVs) and an Intelligent Inspection APP System. The system leverages UAVs equipped with high-definition cameras to conduct efficient and comprehensive inspections, reducing manual labor, inspection time, and risk. By integrating advanced technologies such as Real-Time Kinematic (RTK) positioning and digital image processing, the system enables precise route planning and collection of safety hazards images. A case study conducted on a construction site demonstrates the practicality and effectiveness of the proposed method, showcasing its potential to enhance tower crane safety. On-site testing of UAV intelligent inspections reveals key findings: efficient tower crane hazard inspection within 30 minutes, with a full-identification capability coverage rates of 76.3%, 64.8%, and 76.2% for major, significant, and general hazards respectively and a preliminary-identification capability coverage rates of 18.5%, 27.2%, and 19%, respectively. Notably, UAVs effectively identify various tower crane hazards, except for those requiring auditory detection. The limitations of this study primarily involve two aspects: Firstly, during the initial inspection, manual drone piloting is required for marking tower crane points, followed by automated flight inspections and reuse based on the marked route. Secondly, images captured by the drone necessitate manual identification and review, which can be time-consuming for equipment management personnel, particularly when dealing with a large volume of images. Subsequent research efforts will focus on AI training and recognition of safety hazard images, as well as the automatic generation of inspection reports and corrective management based on recognition results. The ongoing development in this area is currently in progress, and outcomes will be released at an appropriate time.

Keywords: tower crane, inspection, unmanned aerial vehicle (UAV), intelligent inspection app system, safety management

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Aarti Agarwal, Ajmal Khan

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Background and Objective: Breathing difficulty is most distressing symptom for the patient and their caregivers providing palliative care to individuals with advanced malignancy. It needs to be tackled effectively and sometimes preemptively to provide relief from respiratory obstruction. Interventional procedures like tracheal stenting are becoming increasingly popular as a part of palliation for respiratory symptoms. We present a case of esophageal tumor earlier stented by Gastroenterologist to maintain esophageal patency, but the tumor outgrew to produce tracheal infiltration and thereby causing airway obstruction. Method and Result: 62-year-old man presented with unresectable Carcinoma oesophagus with inability to swallow. A metallic stent was placed by the gastroenterologist, to maintain esophageal patency and enable patient to swallow. Two months later, the patient returned to hospital in emergency with respiratory distress. CT neck and thorax revealed tumor infiltration through posterior tracheal wall. Lower extent of the tumor was till 1 cm above the carina. Airway stenting with Tracheo bronchial stent with Y configuration was planned under general anaesthesia with airway blocks. Superior Laryngeal Nerve Block, Glossopharyngeal block and Trans tracheal infiltration of local anaesthetics were performed. The patient was sedated with Fentanyl, Midazolam and propofol infusion but was breathing spontaneously. Once the rigid bronchoscope was placed inside trachea, breathing was supported with oxygen and sevoflurane. Initially, the trachea was cleared of tumor by coring. After creating space, tracheal stent was positioned and deployed. After stent placement patient was awakened, suctioned and nebulized. His respiratory stridor relieved instantaneously and was shifted to recovery. Conclusion: Airway blocks help in decreasing the incidence and severity of coughing during airway instrumentation thereby help in proper stent placement. They also reduce the requirement of general anaesthetics and hasten the post stenting recovery. Airway stent provided immediate relief to patient from symptoms of respiratory difficulty. Decision for early tracheal stenting may be taken for a select group of patients with high propensity for local spread, thereby avoiding respiratory complications and providing better quality of life in patients with inoperable malignancy.

Keywords: tracheal stent, respiratory difficulty, esophageal tumor, anaesthetic management

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Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

Procedia PDF Downloads 150

Authors: Karolina Mazur, Stanislaw Kuciel

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Polylactides (PLA) and polyhydroxyalkanoates (PHA) are the two groups of biodegradable and biocompatible thermoplastic polymers most commonly utilised in medicine and rehabilitation. The aim of this work is to determine the changes in the strength properties and the microstructures taking place in biodegradable polymer composites during their long-term storage in a highly cooled environment (i.e. a freezer at -24ºC) and to initially assess the durability of such biocomposites when used as single-use elements of rehabilitation or medical equipment. It is difficult to find any information relating to the feasibility of long-term storage of technical products made of PLA or PHA, but nonetheless, when using these materials to make products such as casings of hair dryers, laptops or mobile phones, it is safe to assume that without storing in optimal conditions their degradation time might last even several years. SEM images and the assessment of the strength properties (tensile, bending and impact testing) were carried out and the density and water sorption of two polymers, PLA and PHA (NaturePlast PLE 001 and PHE 001), filled with cellulose fibres (corncob grain – Rehofix MK100, Rettenmaier&Sohne) up to 10 and 20% mass were determined. The biocomposites had been stored at a temperature of -24ºC for 4 years. In order to find out the changes in the strength properties and the microstructure taking place after such a long time of storage, the results of the assessment have been compared with the results of the same research carried out 4 years before. Results shows a significant change in the manner of fractures – from ductile with developed surface for the PHA composite with corncob grain when the tensile testing was performed directly after the injection into a more brittle state after 4 years of storage, which is confirmed by the strength tests, where a decrease of deformation is observed at point of fracture. The research showed that there is a way of storing medical devices made out of PLA or PHA for a reasonably long time, as long as the required temperature of storage is met. The decrease of mechanical properties found during tensile testing and bending for PLA was less than 10% of the tensile strength, while the modulus of elasticity and deformation at fracturing slightly rose, which may implicate the beginning of degradation processes. The strength properties of PHA are even higher after 4 years of storage, although in that case the decrease of deformation at fracturing is significant, reaching even 40%, which suggests its degradation rate is higher than that of PLA. The addition of natural particles in both cases only slightly increases the biodegradation.

Keywords: biocomposites, PLA, PHA, storage

Procedia PDF Downloads 264

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Tammy Wee, Detlev Remy, Arif Perdana

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In the recent years, data analytics has become the buzzword in the hospitality industry. The hospitality industry is another example of a data-rich industry that has yet fully benefited from the insights of data analytics. Effective use of data analytics can change how hotels operate, market and position themselves competitively in the hospitality industry. However, at the moment, the data obtained by individual hotels remain under-utilized. This research is a preliminary research on data analytics in the hospitality industry, using an in-depth face-to-face interview on one hotel as a start to a multi-level research. The main case study of this research, hotel A, is a chain brand of international hotel that has been systematically gathering and collecting data on its own customer for the past five years. The data collection points begin from the moment a guest book a room until the guest leave the hotel premises, which includes room reservation, spa booking, and catering. Although hotel A has been gathering data intelligence on its customer for some time, they have yet utilized the data to its fullest potential, and they are aware of their limitation as well as the potential of data analytics. Currently, the utilization of data analytics in hotel A is limited in the area of customer service improvement, namely to enhance the personalization of service for each individual customer. Hotel A is able to utilize the data to improve and enhance their service which in turn, encourage repeated customers. According to hotel A, 50% of their guests returned to their hotel, and 70% extended nights because of the personalized service. Apart from using the data analytics for enhancing customer service, hotel A also uses the data in marketing. Hotel A uses the data analytics to predict or forecast the change in consumer behavior and demand, by tracking their guest’s booking preference, payment preference and demand shift between properties. However, hotel A admitted that the data they have been collecting was not fully utilized due to two challenges. The first challenge of using data analytics in hotel A is the data is not clean. At the moment, the data collection of one guest profile is meaningful only for one department in the hotel but meaningless for another department. Cleaning up the data and getting standards correctly for usage by different departments are some of the main concerns of hotel A. The second challenge of using data analytics in hotel A is the non-integral internal system. At the moment, the internal system used by hotel A do not integrate with each other well, limiting the ability to collect data systematically. Hotel A is considering another system to replace the current one for more comprehensive data collection. Hotel proprietors recognized the potential of data analytics as reported in this research, however, the current challenges of implementing a system to collect data come with a cost. This research has identified the current utilization of data analytics and the challenges faced when it comes to implementing data analytics.

Keywords: data analytics, hospitality industry, customer relationship management, hotel marketing

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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: Yi-Chun Huang, Kuan-Yun Chen, Chuang-Hung Lin

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Urban Green Belt and Blue is a part of the city landscape, it is an important constituent element of the urban environment and appearance. The Hsinchu East Gate Moat is situated in the center of the city, which not only has a wealth of historical and cultural resources, but also combines the Green Belt and the Blue Belt qualities at the same time. The Moat runs more than a thousand meters through the vital Green Belt and the Blue Belt in downtown, and each section is presented in different qualities of moat from south to north. The water area and the green belt of surroundings are presented linear and banded spread. The water body and the rich diverse river banks form an urban green belt of rich layers. The watercourse with green belt design lets users have connections with blue belts in different ways; therefore, the integration of Hsinchu East Gate and moat have become one of the unique urban landscapes in Taiwan. The study is based on the fact-finding case of Hsinchu East Gate Moat where situated in northern Taiwan, to research the impact between the SVF variation of the city and spatial sequence of Urban Green Belt and Blue landscape and visual analysis by constituent cross-section, and then comparing the influence of different leaf area index – the variable ecological factors to the degree of enclosure. We proceed to survey the landscape design of open space, to measure existing structural features of the plant canopy which contain the height of plants and branches, the crown diameter, breast-height diameter through access to diagram of Geographic Information Systems (GIS) and on-the-spot actual measurement. The north and south districts of blue green belt areas are divided 20 meters into a unit from East Gate Roundabout as the epicenter, and to set up a survey points to measure the SVF above the survey points; then we proceed to quantitative analysis from the data to calculate open landscape degree of enclosure. The results can be reference for the composition of future river landscape and the practical operation for dynamic space planning of blue and green belt landscape.

Keywords: sky view factor, degree of enclosure, spatial sequence, leaf area indices

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Authors: Judith Margaret Tymon

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As cities struggle to incorporate informal settlements into the fabric of urban areas, the focus has often been on the provision of housing. This study explores the underlying structure of street networks, with the goal of understanding the morphogenesis of informal settlements through the lens of the access network. As the stages of development progress from infill to consolidation and eventually, to a planned in-situ settlement, the access networks retain the form of the core segments; however, a majority of street patterns are adapted to a grid design to support infrastructure in the final upgraded phase. A case study is presented to examine the street network in the informal settlement of Gobabis Namibia as it progresses from its initial stages to a planned, in-situ, and permanently upgraded development. The Informal Development Stages framework of foundation, infill, and consolidation, as developed by Dr. Jota Samper, is utilized to examine the evolution of street networks. Data is gathered from historical Google Earth satellite images for the time period between 2003 and 2022. The results demonstrate that during the foundation through infill stages, incremental changes follow similar patterns, with pathways extended, lengthened, and densified as housing is created and the settlement grows. In the final stage of consolidation, the resulting street layout is transformed to support the installation of infrastructure; however, some elements of the original street patterns remain. The core pathways remain intact to accommodate the installation of infrastructure and the creation of housing plots, defining the shape of the settlement and providing the basis of the urban form. The adaptations, growth, and consolidation of the street network are critical to the eventual formation of the spatial layout of the settlement. This study will include a comparative analysis of findings with those of recent research performed by Kamalipour, Dovey, and others regarding incremental urbanism within informal settlements. Further comparisons will also include studies of street networks of well-established urban centers that have shown links between the morphogenesis of access networks and the eventual spatial layout of the city. The findings of the study can be used to guide and inform strategies for in-situ upgrading and can contribute to the sustainable development of informal settlements.

Keywords: Gobabis Namibia, incremental urbanism, informal development stages, informal settlements, street networks

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Authors: Ajved Ahmed

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This research paper explores the intricate relationship between sports activities and disability, aiming to shed light on the multifaceted impacts of sports participation on individuals with disabilities. As the world grapples with the challenges posed by the growing population of people with disabilities, understanding the role of sports in their lives becomes increasingly important. The paper begins by providing a comprehensive overview of the diverse forms of disabilities, emphasizing the wide spectrum of physical, sensory, and cognitive impairments. It then delves into the benefits of sports activities for individuals with disabilities, highlighting the profound physical, psychological, and social advantages that engagement in sports can offer. These benefits encompass improved physical fitness, enhanced self-esteem and mental well-being, increased social integration, and a sense of empowerment and independence. Furthermore, the paper examines the barriers and challenges that individuals with disabilities often encounter when attempting to participate in sports activities, ranging from inaccessible facilities to societal prejudices and stereotypes. It underscores the critical role of inclusive sports programs, adaptive equipment, and policy initiatives in overcoming these barriers and fostering an environment where everyone can enjoy the benefits of sports. Through a comprehensive review of existing research and case studies, the paper also explores specific sports and their suitability for various types of disabilities. It discusses adapted sports like wheelchair basketball, blind soccer, and para-swimming, showcasing how these tailored activities not only accommodate disabilities but also promote excellence and competition at the highest levels. Additionally, the research paper delves into the economic and societal implications of increased sports participation among individuals with disabilities. It explores the potential for greater inclusion in the workforce, reduced healthcare costs, and the fostering of a more inclusive and accepting society. This research paper underscores the profound impact of sports activities on individuals with disabilities, highlighting their potential to improve physical health, mental well-being, and social integration. It calls for continued efforts to break down barriers and promote inclusive sports programs to ensure that everyone, regardless of their abilities, can access the transformative power of sports. Ultimately, this study contributes to a broader understanding of disability and sports, emphasizing the importance of inclusivity and accessibility in creating a more equitable and healthier society.

Keywords: sports and health, sports and disability, curing disability through sports, health benefits of sports

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Authors: Huseyin Guler, Cigdem Kosar

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The aim of this study is to propose Bridge estimator for seasonal unit root tests. Seasonality is an important factor for many economic time series. Some variables may contain seasonal patterns and forecasts that ignore important seasonal patterns have a high variance. Therefore, it is very important to eliminate seasonality for seasonal macroeconomic data. There are some methods to eliminate the impacts of seasonality in time series. One of them is filtering the data. However, this method leads to undesired consequences in unit root tests, especially if the data is generated by a stochastic seasonal process. Another method to eliminate seasonality is using seasonal dummy variables. Some seasonal patterns may result from stationary seasonal processes, which are modelled using seasonal dummies but if there is a varying and changing seasonal pattern over time, so the seasonal process is non-stationary, deterministic seasonal dummies are inadequate to capture the seasonal process. It is not suitable to use seasonal dummies for modeling such seasonally nonstationary series. Instead of that, it is necessary to take seasonal difference if there are seasonal unit roots in the series. Different alternative methods are proposed in the literature to test seasonal unit roots, such as Dickey, Hazsa, Fuller (DHF) and Hylleberg, Engle, Granger, Yoo (HEGY) tests. HEGY test can be also used to test the seasonal unit root in different frequencies (monthly, quarterly, and semiannual). Another issue in unit root tests is the lag selection. Lagged dependent variables are added to the model in seasonal unit root tests as in the unit root tests to overcome the autocorrelation problem. In this case, it is necessary to choose the lag length and determine any deterministic components (i.e., a constant and trend) first, and then use the proper model to test for seasonal unit roots. However, this two-step procedure might lead size distortions and lack of power in seasonal unit root tests. Recent studies show that Bridge estimators are good in selecting optimal lag length while differentiating nonstationary versus stationary models for nonseasonal data. The advantage of this estimator is the elimination of the two-step nature of conventional unit root tests and this leads a gain in size and power. In this paper, the Bridge estimator is proposed to test seasonal unit roots in a HEGY model. A Monte-Carlo experiment is done to determine the efficiency of this approach and compare the size and power of this method with HEGY test. Since Bridge estimator performs well in model selection, our approach may lead to some gain in terms of size and power over HEGY test.

Keywords: bridge estimators, HEGY test, model selection, seasonal unit root

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Authors: Danielle G. Saique

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Introduction: Promoting Gender Equality, Equity and Empowerment of Women (GEE&EW) can be attained by practicing thereby exercising Sexual and Reproductive Health and Rights (SRHR). Gender Inequality is manifested thru Violence Against Women (VAW). Objectives: This study presents causes, prevalence, effects of Gender Inequality for not practicing and violating SRHR. This proposes Action Plan by promoting, integrating SRHR in the “holistic approach” of Social Work education, practice and service-delivery in any work-set-ups. Limitations: VAW cases showed victim and violator are known, related and living together. Cases transpired at home, reported, investigated in the police and filed in the legal court of law for the year 2013. Methods: Data from blotters, reports, filed cases, case studies gathered by the Social Worker (SWr). Qualitative analysis identified cause, prevalence of VAW related in violating SRHR. SWr serves innovative interventions in any work settings by applying SRHR background, skills in educating, counseling client-victims. Results: 65 VAW cases on non-negotiation or refusal of practicing SRHR. Non-acceptance of Family Planning yielded unwanted, unplanned pregnancies, abandoned children, battered women. Neglected pre-post natal maternal care caused complications or death. Rape, incest led trauma or death. Unsafe, unprotected sex transmitted STDs. Conclusions: Non-availing SRHR from health facilities, from Medical Health SWr concluded to non-practicing or violating rights to life, health care, protection, rights to information, education, rights to plan family, rights from torture, ill-treatment. VAW brings undesirable effects to the well-being, wellness and humaneness of the victim. Recommendations: The innovative intervention services on SRHR of a SWr and the findings, results in violating SRHR are recommendations in Action Planning by adding “The SRHR Concepts” in Social Work thereby preventing VAW; empowering women’s rights to development, gender equality, equity liberty, security, freedom; resilience and involvement in promoting, practicing, exercising SRHR at home. Recommended therefore to duplicate this innovative practice and experience on SRHR as implemented by the SWr in any work setting.

Keywords: women development, promoting gender equality, equity, empowerment of women

Procedia PDF Downloads 475

Authors: Alexandra Emmanuelle Membangbi, Jacky Njiki Bikoï, Esther Del-florence Moni Ndedi, Marie Joseph Nkodo Mindimi, Donatien Serge Mbaga, Elsa Nguiffo Makue, André Chris Mikangue Mbongue, Martha Mesembe, George Ikomey Mondinde, Eric Walter Perfura-yone, Sara Honorine Riwom Essama

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Background: Tuberculosis (TB) is one of the top lethal infectious diseases worldwide. In recent years, interferon-γ (INF-γ) release assays (IGRAs) have been established as routine tests for diagnosing TB infection. However, produced INF-γ assessment failed to distinguish active TB (ATB) from latent TB infection (LTBI), especially in TB epidemic areas. In addition to IFN-γ, interleukin-2 (IL-2), another cytokine secreted by activated T cells, is also involved in immune response against Mycobacterium tuberculosis. The aim of the study was to assess the capacity of IFN-γ and IL2 to evaluate the therapeutic response of patients on anti-tuberculosis treatment. Material and Methods: We conducted a cross-sectional study in the Pneumonology Departments of the Jamot Hospital in Yaoundé between May and August 2021. After signed the informed consent, the sociodemographic data, as well as 5 mL of blood, were collected in the crook of the elbow of each participant. Sixty-one subjects were selected (n= 61) and divided into 4 groups as followed: group 1: resistant tuberculosis (n=13), group 2: active tuberculosis (n=19), group 3 cured tuberculosis (n=16), and group 4: presumed healthy persons (n=13). The cytokines of interest were determined using an indirect Enzyme-linked Immuno-Sorbent Assay (ELISA) according to the manufacturer's recommendations. P-values < 0.05 were interpreted as statistically significant. All statistical calculations were performed using SPSS version 22.0 Results: The results showed that men were more 14/61 infected (31,8%) with a high presence in active and resistant TB groups. The mean age was 41.3±13.1 years with a 95% CI = [38.2-44.7], the age group with the highest infection rate was ranged between 31 and 40 years. The IL-2 and INF-γ means were respectively 327.6±160.6 pg/mL and 26.6±13.0 pg/mL in active tuberculosis patients, 251.1±30.9 pg/mL and 21.4±9.2 pg/mL in patients with resistant tuberculosis, while it was 149.3±93.3 pg/mL and 17.9±9.4 pg/mL in cured patients, 15.1±8.4 pg/mL and 5.3±2.6 pg/mL in participants presumed healthy (p <0.0001). Significant differences in IFN-γ and IL-2 rates were observed between the different groups. Conclusion: Monitoring the serum levels of INF-γ and IL-2 would be useful to evaluate the therapeutic response of anti-tuberculosis patients, particularly in the both cytokines association case, that could improve the accuracy of routine examinations.

Keywords: antibiotic therapy, interferon gamma, interleukin 2, tuberculosis

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Authors: M. Azharul Islam, M. Russel Sarker, M. Shahadat Hossen

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Air pollution is one of the major environmental problems that have gained importance in all over the world. Air pollution is a problem for all of us. The present study was conducted to explore the people’s perception level and awareness of air pollution in selected areas of Mymensingh in Bangladesh. Health impacts of air pollution also studied through personal interview and structured questionnaire. The relationship of independent variables (age, educational qualification, family size, residence and communication exposure) with the respondent’s perception level and awareness of air pollution (dependent variable) was studied to achieve the objectives of the study. About 600 respondents were selected randomly from six sites for collecting data during the period of July 2016 to June 2017. Pearson’s product-moment correlation coefficients were computed to examine the relationship between the concerned variables. The results revealed that about half (46.67%) of the respondents had a medium level of perception and awareness about air pollution in their areas where 31.67 percent had low, and 21.67 percent had a high level. In rural areas of the study sites, 43.33 percent respondents had low, 50 percent had medium, and only 6.67 percent had high perception and awareness on air pollution. In case of urban areas, 20 percent respondents had low, 43.33 percent had medium, and 36.67 percent had a high level of awareness and perception on air pollution. The majority of the respondents (93.33 percent) were lacking of proper awareness about air pollution in rural areas while 63.33 percent in urban areas. Out of five independent variables, three variables such as- educational qualification, residence status and communication exposure had positive and significant relationship. Age of respondents had negative and significant relationship with their awareness of air pollution where family size of the respondents had no significant relationship with their perception and awareness of air pollution. Thousands of people live in urban areas where urban smog, particle pollution, and toxic pollutants pose serious health concerns. But most of the respondents of the urban sites are not familiarize about the real causes of air pollution. Respondents exposed higher level of experience for air pollutants, such as- irritation of the eyes, coughing, tightness of chest and many health difficulties. But respondents of both rural and urban area hugely suffered such health problems and the tendency of certain difficulties increased day by day. In this study, most of the respondents had lack of knowledge on the causes of such health difficulties due to their lower perception level. Proper attempts should be taken to raise literacy level, communication exposure to increase the perception and awareness of air pollution among the respondents of the study areas. Extra care with above concerned fields should be taken to increase perception and awareness of air pollution in rural areas.

Keywords: air pollution, awareness, health impacts, perception of people

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Authors: Mark A. S. Laidlaw, Howard W. Mielke

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In California between the late 1920’s and 1986 the lead concentrations in urban soils and dust climbed rapidly following the deposition of greater than 387,000 tonnes of lead emitted from gasoline. Previous research indicates that when children are lead exposed around 90% of the lead is retained in their bones and teeth due to the substitution of lead for calcium. Lead in children’s bones has been shown to accumulate over time and is highest in inner-city urban areas, lower in suburban areas and lowest in rural areas. It is also known that women’s bones demineralize during pregnancy due to the foetus's high demand for calcium. Lead accumulates in women’s bones during childhood and the accumulated lead is subsequently released during pregnancy – a lagged response. This results in calcium plus lead to enter the blood stream and cross the placenta to expose the foetus with lead. In 1970 in the United States, the average age of a first‐time mother was about 21. In 2008, the average age was 25.1. In this study, it is demonstrated that in California there is a forward lagged relationship between the accumulated emissions of lead from vehicle fuel additives and later autism prevalence trends between the 1990’s and current time period. Regression analysis between a 24 year forward lag of accumulated lead emissions and autism prevalence trends in California are associated strongly (R2=0.95, p=0.00000000127). It is hypothesized that autism in genetically susceptible children may stem from vehicle fuel lead emission exposures of their mothers during childhood and that the release of stored lead during subsequent pregnancy resulted in lead exposure of foetuses during a critical developmental period. It is furthermore hypothesized that the 24 years forward lag between lead exposures has occurred because that is time period is the average length for women to enter childbearing age. To test the hypothesis that lead in mothers bones is associated with autism, it is hypothesized that retrospective case-control studies would show an association between the lead in mother’s bones and autism. Furthermore, it is hypothesized that the forward lagged relationship between accumulated historical vehicle fuel lead emissions (or air lead concentrations) and autism prevalence trends will be similar in cities at the national and international scale. If further epidemiological studies indicate a strong relationship between accumulated vehicle fuel lead emissions (or accumulated air lead concentrations) and lead in mother’s bones and autism rates, then urban areas may require extensive soil intervention to prevent the development of autism in children.

Keywords: autism, bones, lead, gasoline, petrol, prevalence

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Authors: Richa Raje, Anumol Antony

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Playing is the foremost stepping stone for childhood development. Play is an essential aspect of a child’s development and learning because it creates meaningful enduring environmental connections and increases children’s performance. The children’s proficiencies are ever varying in their course of growth. There is innovation in the activities, as it kindles the senses, surges the love for exploration, overcomes linguistic barriers and physiological development, which in turn allows them to find their own caliber, spontaneity, curiosity, cognitive skills, and creativity while learning during play. This paper aims to comprehend the learning in play which is the most essential underpinning aspect of the outdoor play area. It also assesses the trend of playgrounds design that is merely hammered with equipment's. It attempts to derive a relation between the natural environment and children’s activities and the emotions/senses that can be evoked in the process. One of the major concerns with our outdoor play is that it is limited to an area with a similar kind of equipment, thus making the play highly regimented and monotonous. This problem is often lead by the strict timetables of our education system that hardly accommodates play. Due to these reasons, the play areas remain neglected both in terms of design that allows learning and wellbeing. Poorly designed spaces fail to inspire the physical, emotional, social and psychological development of the young ones. Currently, the play space has been condensed to an enclosed playground, driveway or backyard which confines the children’s capability to leap the boundaries set for him. The paper emphasizes on study related to kids ranging from 5 to 11 years where the behaviors during their interactions in a playground are mapped and analyzed. The theory of affordance is applied to various outdoor play areas, in order to study and understand the children’s environment and how variedly they perceive and use them. A higher degree of affordance shall form the basis for designing the activities suitable in play spaces. It was observed during their play that, they choose certain spaces of interest majority being natural over other artificial equipment. The activities like rolling on the ground, jumping from a height, molding earth, hiding behind tree, etc. suggest that despite equipment they have an affinity towards nature. Therefore, we as designers need to take a cue from their behavior and practices to be able to design meaningful spaces for them, so the child gets the freedom to test their precincts.

Keywords: children, landscape design, learning environment, nature and play, outdoor play

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Authors: Joana PaScoa Pinheiro, David Goncalves Ferreira, Filipe Ramos, Joaquim Soares Do Brito, Samuel Martins, Marco Sarmento

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Introduction: The SARS-CoV-2 (COVID-19) pandemic was identified in January 2020 in China, in the city of Wuhan. The increase in the number of cases over the following months was responsible for the restructuring of hospitals and departments in order to accommodate admissions related to COVID-19. Essential services, such as trauma, had to readapt to maintain their functionality and thus guarantee quick and safe access in case of an emergency. Objectives: This study describes the impact of COVID-19 on a Level III Trauma Center and particularly on the clinical management of hospitalized patients with spine injuries. Study Design & Methods: This is a retrospective cohort study whose results were obtained through the medical records of patients with spine injuries who underwent surgical intervention in the years 2019 and 2020 (period from March 1st to December 31st). A comparison between the two groups was made. In the study patients with injuries in the context of trauma were included who underwent surgery in the periods previously described. Patients hospitalized with a spine injury in a non-traumatic context and/or were not surgically treated were excluded. Results: In total, 137 patients underwent trauma spine surgery of which 71 in 2019 (51.8%) were without significant differences in intergroup comparisons. The most frequent injury mechanism in 2019 was motor vehicle crash (47.9%) compared to 2020 which was of a person falling from a height between 2-4 meters (37.9%). Cervical trauma was reported to be the most frequent spine injury in both years. There was a significant decrease in the need for intensive care in 2020, 51.4% vs 30.3%, p = .015 and the number of complications was also lower in 2020 (1.35% vs 0.98%), including the number of deaths, being the difference marginally significant. There were no significant differences regarding time for presentation to surgery or in the total days of hospitalization. Conclusions: The restructuring made in the trauma unit at a Level III Trauma Center in the context of the current COVID-19 pandemic was effective, with no significant differences between the years of 2019 vs 2020 when compared with the time for presentation to surgery or the number of days of hospitalization. It was also found that lockdown rules in 2020 were probably responsible for the decrease in the number of road traffic accidents, which justifies a significant decrease in the need for intensive care as well as in the number of complications in patients hospitalized in the context of spine trauma.

Keywords: trauma, spine, impact, covid-19

Procedia PDF Downloads 252

Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Hsiu-Tsu Cho

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Collective efficacy refers to a group’s sense of its capacity to complete a task successfully or to reach objectives. Little effort has been expended on investigating the relationship between the emotion expression of a leader and collective efficacy. In this study, we examined the impact of the different emotions and emotion expression of a group leader on collective efficacy and explored whether the emotion–expressive effects differed under conditions of negative and positive emotions. A total of 240 undergraduate and graduate students recruited using Facebook and posters at a university participated in this research. The participants were separated randomly into 80 groups of four persons consisting of three participants and a confederate. They were randomly assigned to one of five conditions in a 2 (pride vs. guilt) × 2 (emotion expression of group leader vs. no emotion expression of group leader) factorial design and a control condition. Each four-person group was instructed to get the reward in a group competition of solving the five-disk Tower of Hanoi puzzle and making decisions on an investment case. We surveyed the participants by employing the emotional measure revised from previous researchers and collective efficacy questionnaire on a 5-point scale. To induce an emotion of pride (or guilt), the experimenter announced whether the group performance was good enough to have a chance of getting the reward (ranking the top or bottom 20% among all groups) after group task. The leader (confederate) could either express or not express a feeling of pride (or guilt) following the instruction according to the assigned condition. To check manipulation of emotion, we added a control condition under which the experimenter revealed no results regarding group performance in maintaining a neutral emotion. One-way ANOVAs and post hoc pairwise comparisons among the three emotion conditions (pride, guilt, and control condition) involved assigning pride and guilt scores (pride: F(1,75) = 32.41, p < .001; guilt: F(1,75) = 6.75, p < .05). The results indicated that manipulations of emotion were successful. A two-way between-measures ANOVA was conducted to examine the predictions of the main effects of emotion types and emotion expression as well as the interaction effect of these two variables on collective efficacy. The experimental findings suggest that pride did not affect collective efficacy (F(1,60) = 1.90, ns.) more than guilt did and that the group leader did not motivate collective efficacy regardless of whether he or she expressed emotion (F(1,60) = .89, ns.). However, the interaction effect of emotion types and emotion expression was statistically significant (F(1,60) = 4.27, p < .05, ω2 = .066); the effects accounted for 6.6% of the variance. Additional results revealed that, under the pride condition, the leader enhanced group efficacy when expressing emotion, whereas, under the guilt condition, an expression of emotion could reduce collective efficacy. Overall, these findings challenge the assumption that the effect of expression emotion are the same on all emotions and suggest that a leader should be cautious when expressing negative emotions toward a group to avoid reducing group effectiveness.

Keywords: collective efficacy, group leader, emotion expression, pride, guilty

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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: Nicolaas Unland, John Webb

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The acidification and mobilisation of metals during the oxidation of acid sulfate soils exposed during lake bed drying is an increasingly common phenomenon under climate scenarios with reduced rainfall. In order to assess the risk of generating high concentrations of acidity and dissolved metals, chromium suite analysis are fundamental, but sometimes limited in characterising the potential risks they pose. This study combines such fundamental test work, along with incubation tests and 1D modelling to investigate the risks associated with the drying of Third Reedy Lake in South East Australia. Core samples were collected from a variable depth of 0.5 m below the lake bed, at 19 locations across the lake’s footprint, using a boat platform. Samples were subjected to a chromium suite of analysis, including titratable actual acidity, chromium reducible sulfur and acid neutralising capacity. Concentrations of reduced sulfur up to 0.08 %S and net acidities up to 0.15 %S indicate that acid sulfate soils have formed on the lake bed during permanent inundation over the last century. A further sub-set of samples were prepared in 7 columns and subject to accelerated heating, drying and wetting over a period of 64 days in laboratory. Results from the incubation trial indicate that while pyrite oxidation proceeded, minimal change to soil pH or the acidity of leachate occurred, suggesting that the internal buffering capacity of lake bed sediments was sufficient to neutralise a large proportion of the acidity produced. A 1D mass balance model was developed to assess potential changes in lake water quality during drying based on the results of chromium suite and incubation tests. Results from the above test work and modelling suggest that acid sulfate soils pose a moderate to low risk to the Third Reedy Lake system. Further, the risks can be effectively managed during the initial stages of lake drying via flushing with available mildly alkaline water. The study finds that while test work such as chromium suite analysis are fundamental in characterizing acid sulfate soil environments, they can the overestimate risks associated with the soils. Subsequent incubation test work may more accurately characterise such soils and lead to better-informed management strategies.

Keywords: acid sulfate soil, incubation, management, model, risk

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

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Authors: Jaspreet Kaur, Parminder Nain, Vipin Saini, Sumitra Dahiya

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Elaeocarpus sphaericus has been traditionally used in the Indian traditional medicine system for the treatment of stress, anxiety, depression, palpitation, epilepsy, migraine and lack of concentration. The study was investigated to evaluate the neurological potential such as anxiolytic, muscle relaxant and sedative activity of methanolic extract of Elaeocarpus sphaericus stem bark (MEESSB) in mice. Preliminary phytochemical screening and acute oral toxicity of MEESSB was carried out by using standard methods. The anxiety was induced by employing Elevated Plus-Maze (EPM), Light and Dark Test (LDT), Open Field Test (OFT) and Social Interaction test (SIT). The motor coordination and sedative effect was also observed by using actophotometer, rota-rod apparatus and ketamine-induced sleeping time, respectively. Animals were treated with different doses of MEESSB (i.e.100, 200, 400 and 800 mg/kg orally) and diazepam (2 mg/kg i.p) for 21 days. Brain neurotransmitters like dopamine, serotonin and nor-epinephrine level were estimated by validated methods. Preliminary phytochemical analysis of the extract revealed the presence of tannins, phytosterols, steroids and alkaloids. In the acute toxicity studies, MEESSB was found to be non-toxic and with no mortality. In anxiolytic studies, the different doses of MEESSB showed a significant (p<0.05) effect on EPM and LDT. In OFT and SIT, a significant (p<0.05) increase in ambulation, rearing and social interaction time was observed. In the case of motor coordination activity, the MEESSB does not cause any significant effect on the latency to fall off from the rotarod bar as compared to the control group. Moreover, no significant effects on ketamine-induced sleep latency and total sleeping time induced by ketamine were observed. Results of neurotransmitter estimation revealed the increased concentration of dopamine, whereas the level of serotonin and nor-epinephrine was found to be decreased in the mice brain, with MEESSB at dose 800 mg/kg only. The study has validated the folkloric use of the plant as an anxiolytic in Indian traditional medicine while also suggesting potential usefulness in the treatment of stress and anxiety without causing sedation.

Keywords: anxiolytic, behavior experiments, brain neurotransmitters, elaeocarpus sphaericus

Procedia PDF Downloads 173

Authors: Hamed Ahari, Behrouz Akbari Adreghani, Vadood Razavilar, Amirali Anvar, Sima Moradi, Hourieh Shalchi

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Considering the ever increasing population and industrialization of the developmental trend of humankind's life, we are no longer able to detect the toxins produced in food products using the traditional techniques. This is due to the fact that the isolation time for food products is not cost-effective and even in most of the cases, the precision in the practical techniques like the bacterial cultivation and other techniques suffer from operator errors or the errors of the mixtures used. Hence with the advent of nanotechnology, the design of selective and smart sensors is one of the greatest industrial revelations of the quality control of food products that in few minutes time, and with a very high precision can identify the volume and toxicity of the bacteria. Methods and Materials: In this technique, based on the bacterial antibody connection to nanoparticle, a sensor was used. In this part of the research, as the basis for absorption for the recognition of bacterial toxin, medium sized silica nanoparticles of 10 nanometer in form of solid powder were utilized with Notrino brand. Then the suspension produced from agent-linked nanosilica which was connected to bacterial antibody was positioned near the samples of distilled water, which were contaminated with Staphylococcus aureus bacterial toxin with the density of 10-3, so that in case any toxin exists in the sample, a connection between toxin antigen and antibody would be formed. Finally, the light absorption related to the connection of antigen to the particle attached antibody was measured using spectrophotometry. The gene of 23S rRNA that is conserved in all Staphylococcus spp., also used as control. The accuracy of the test was monitored by using serial dilution (l0-6) of overnight cell culture of Staphylococcus spp., bacteria (OD600: 0.02 = 107 cell). It showed that the sensitivity of PCR is 10 bacteria per ml of cells within few hours. Result: The results indicate that the sensor detects up to 10-4 density. Additionally, the sensitivity of the sensors was examined after 60 days, the sensor by the 56 days had confirmatory results and started to decrease after those time periods. Conclusions: Comparing practical nano biosensory to conventional methods like that culture and biotechnology methods(such as polymerase chain reaction) is accuracy, sensitiveness and being unique. In the other way, they reduce the time from the hours to the 30 minutes.

Keywords: exotoxin, nanobiosensor, recognition, Staphylococcus aureus

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Authors: Gruffydd E. Jones

Abstract:

The world’s largest collection of historical, cultural, and heritage material is unarchived and undocumented in the hands of the public. Not only does this material represent the missing collections in heritage sector archives today, but it is also the key to providing a diverse range of communities with the means to express their history in their own words and to celebrate their unique, personal heritage. The People’s Collection Wales (PCW) acts as a platform on which the heritage of Wales and her people can be collated and shared, at the heart of which is a thriving community engagement programme across a network of museums, archives, and libraries. By providing communities with the archival skillset commonly employed throughout the heritage sector, PCW enables local projects, societies, and individuals to express their understanding of local heritage with their own voices, empowering communities to embrace their diverse and complex identities around Wales. Drawing on key examples from the project’s history, this paper will demonstrate the successful way in which museums have been developed as hubs for community engagement where the public was at the heart of collection and documentation activities, informing collection and curatorial policies to benefit both the institute and its local community. This paper will also highlight how collections from marginalised, under-represented, and minority communities have been published and celebrated extensively around Wales, including adoption by the education system in classrooms today. Any activity within the heritage sector, whether of collection, preservation, digitisation, or accessibility, should be considerate of community engagement opportunities not only to remain relevant but in order to develop as community hubs, pivots around which local heritage is supported and preserved. Attention will be drawn to our digitisation workflow, which, through training and support from museums and libraries, has allowed the public not only to become involved but to actively lead the contemporary evolution of documentation strategies in Wales. This paper will demonstrate how the PCW online access archive is promoting museum collections, encouraging user interaction, and providing an invaluable platform on which a broader community can inform, preserve and celebrate their cultural heritage through their own archival material too. The continuing evolution of heritage engagement depends wholly on placing communities at the heart of the sector, recognising their wealth of cultural knowledge, and developing the archival skillset necessary for them to become archival practitioners of their own.

Keywords: social history, cultural heritage, community heritage, museums, archives, libraries, community engagement, oral history, community archives

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