Search results for: armored vehicle noise

Authors: Yena Lee, Vassilis M. Charitopoulos, Karthik Thyagarajan, Ian Morris, Jose M. Pinto, Lazaros G. Papageorgiou

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With globalisation, the need to have better coordination of production and distribution decisions has become increasingly important for industrial gas companies in order to remain competitive in the marketplace. In this work, we investigate a problem that integrates production, inventory, and routing decisions in a liquid oxygen supply chain. The oxygen supply chain consists of production facilities, external third-party suppliers, and multiple customers, including hospitals and industrial customers. The product produced by the plants or sourced from the competitors, i.e., third-party suppliers, is distributed by a fleet of heterogenous vehicles to satisfy customer demands. The objective is to minimise the total operating cost involving production, third-party, and transportation costs. The key decisions for production include production and inventory levels and product amount from third-party suppliers. In contrast, the distribution decisions involve customer allocation, delivery timing, delivery amount, and vehicle routing. The optimisation of the coordinated production, inventory, and routing decisions is a challenging problem, especially when dealing with large-size problems. Thus, we present a two-stage procedure to solve the integrated problem efficiently. First, the problem is formulated as a mixed-integer linear programming (MILP) model by simplifying the routing component. The solution from the first-stage MILP model yields the optimal customer allocation, production and inventory levels, and delivery timing and amount. Then, we fix the previous decisions and solve a detailed routing. In the second stage, we propose a column generation scheme to address the computational complexity of the resulting detailed routing problem. A case study considering a real-life oxygen supply chain in the UK is presented to illustrate the capability of the proposed models and solution method. Furthermore, a comparison of the solutions from the proposed approach with the corresponding solutions provided by existing metaheuristic techniques (e.g., guided local search and tabu search algorithms) is presented to evaluate the efficiency.

Keywords: production planning, inventory routing, column generation, mixed-integer linear programming

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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: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: Norazlan Mohmad Misnan, Maizatul Hasyima Omar, Mohd Isa Wasiman

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Papaya (Carica papaya L., Caricaceae) is a tree which mainly cultivated for its fruits in many tropical regions including Australia, Brazil, China, Hawaii, and Malaysia. Beside of fruits, its leaves, seeds, and latex have also been traditionally used for treating diseases, which also reported to possess anti-cancer and anti- malaria properties. Its leaves have been reported to consist of various chemical compounds such as alkaloids, flavonoids and phenolics. Clitorin and manghaslin are among major flavonoids presence. Thus, the aim of this study is to quantify the purity of these isolated compounds (clitorin and manghsalin) by using quantitative Nuclear Magnetic Resonance (qNMR) analysis. Only fresh C. papaya leaves were used for juice extraction procedure and subsequently was freeze-dried to obtain a dark green powdered form of the extract prior to Centrifugal Partition Chromatography (CPC) separation. The CPC experiments were performed using a two-phase solvent system comprising ethyl acetate/butanol/water (1:4:5, v/v/v/v) solvent. The upper organic phase was used as the stationary phase, and the lower aqueous phase was employed as the mobile phase. Ten fractions were obtained after an hour runtime analysis. Fraction 6 and fraction 8 has been identified as clitorin (m/z 739.21 [M-H]-) and manghaslin (m/z 755.21 [M-H]-), respectively, based on LCMS data and full analysis of NMR (1H NMR, 13C NMR, HMBC, and HSQC). The 1H-qNMR measurements were carried out using a 400 MHz NMR spectrometer (JEOL ECS 400MHz, Japan) and deuterated methanol was used as a solvent. Quantification was performed using the AQARI method (Accurate Quantitative NMR) with deuterated 1,4-Bis(trimethylsilyl)benzene (BTMSB) as an internal reference substances. This AQARI protocol includes not only NMR measurement but also sample preparation that provide highest precision and accuracy than other qNMR methods. The 90° pulse length and the T1 relaxation times for compounds and BTMSB were determined prior to the quantification to give the best signal-to-noise ratio. Regions containing the two downfield signals from aromatic part (6.00–6.89 ppm), and the singlet signal, (18H) arising from BTMSB (0.63-1.05ppm) were selected for integration. The purity of clitorin and manghaslin were calculated to be 52.22% and 43.36%, respectively. Further purification is needed in order to increase its purity. This finding has demonstrated the use of qNMR for quality control and standardization of various plant extracts and which can be applied for NMR fingerprinting of other plant-based products with good reproducibility and in the case where commercial standards is not readily available.

Keywords: Carica papaya, clitorin, manghaslin, quantitative Nuclear Magnetic Resonance, Centrifugal Partition Chromatography

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: H. Y. Al-Matubsi, G. A. Oriquat, M. Abu-Samak, O. A. Al Hanbali, M. Salim

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Background: Uncontrolled diabetes mellitus (DM) is an etiological factor for recurrent pregnancy loss and major congenital malformations in the offspring. Antioxidant therapy has been advocated to overcome the oxidant-antioxidant disequilibrium inherent in diabetes. The aims of this study were to evaluate the protective effect of lipoic acid (LA) on fetal outcome and to elucidate changes that may be involved in the mechanism(s) implicit diabetic fetopathy. Methods: Female rats were rendered hyperglycemic using streptozocin and then mated with normal male rat. Pregnant non-diabetic (group1; n=9; and group2; n=7) or pregnant diabetic (group 3; n=10; and group 4; n=8) rats were treated daily with either lipoic acid (LA) (30 mg/kg body weight; groups 2 and 4) or vehicle (groups 1 and 3) between gestational days 0 and 15. On day 15 of gestation, the rats were sacrificed, and the fetuses, placentas and membranes dissected out of the uterine horns. Following morphological examination, the fetuses, placentas and membranes were homogenized, and used to measure cyclooxygenases (COX) activities and metabolisms of prostaglandin (PG) E2 (PGEM) and PGF2 (PGFM) levels. Maternal liver and plasma total glutathione levels were also determined. Results: Supplementation of diabetic rats with LA was found to significantly (P<0.05) reduce resorption rates in diabetic rats and increased mean fetal weight compared to diabetic group. Treatment of diabetic rats with LA leads to a significant (P<0.05) increase in liver and plasma total glutathione, in comparison with diabetic rats. Decreased levels of PGEM and elevated levels of PGFM in the fetuses, placentas and membranes were characteristic of experimental diabetic gestation associated with malformation. LA treatment to diabetic mothers failed to normalize levels of PGEM to the non-diabetic control rats. However, the levels of PGEM in malformed fetuses from LA-treated diabetic mothers was significantly (P < 0.05) higher than those in malformed fetuses from diabetic rats. Conclusions: We conclude that LA can reduce congenital malformations in the offspring of diabetic rats at day 15 of gestation. However, LA treatment did not completely prevent the occurrence of malformations, other factors, such as arachidonic acid deficiency and altered prostaglandin metabolismmay be involved in the pathogenesis of diabetes-induced congenital malformations.

Keywords: diabetes, lipoic acid, pregnancy, prostaglandins

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Authors: Haiqiao Du, Qian Wang, Shuwei Wang, Jianan Li

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Purpose: The aim is to evaluate the effect of cochlear implantation (CI) in patients with unilateral hearing loss, with a view to providing data support for the selection of therapeutic interventions for patients with single-sided deafness (SSD)/asymmetric hearing loss (AHL) and the broadening of the indications for CI. Methods: The study subjects were patients with unilateral hearing loss who underwent cochlear implantation surgery in our hospital in August 2022 and were willing to cooperate with the test and were divided into 2 groups: SSD group and AHL group. The enrolled patients were followed up for hearing level, tinnitus changes, speech recognition ability, sound source localization ability, and quality of life at five-time points: preoperatively, and 1, 3, 6, and 12 months after postoperative start-up. Results: As of June 30, 2024, a total of nine patients completed follow-up, including four in the SSD group and five in the AHL group. The mean postoperative hearing aid thresholds on the CI side were 31.56 dB HL and 34.75 dB HL in the two groups, respectively. Of the four patients with preoperative tinnitus symptoms (three patients in the SSD group and one patient in the AHL group), all showed a degree of reduction in Tinnitus Handicap Inventory (THI) scores, except for one patient who showed no change. In both the SSD and AHL groups, the sound source localization results (expressed as RMS error values, with smaller values indicating better ability) were 66.87° and 77.41° preoperatively and 29.34° and 54.60° 12 months after postoperative start-up, respectively, which showed that the ability to localize the sound source improved significantly with longer implantation time. The level of speech recognition was assessed by 3 test methods: speech recognition rate of monosyllabic words in a quiet environment and speech recognition rate of different sound source directions at 0° and 90° (implantation side) in a noisy environment. The results of the 3 tests were 99.0%, 72.0%, and 36.0% in the preoperative SSD group and 96.0%, 83.6%, and 73.8% in the AHL group, respectively, whereas they fluctuated in the postoperative period 3 months after start-up, and stabilized at 12 months after start-up to 99.0%, 100.0%, and 100.0% in the SSD group and 99.5%, 96.0%, and 99.0%. Quality of life was subjectively evaluated by three tests: the Speech Spatial Quality of Sound Auditory Scale (SSQ-12), the Quality-of-Life Bilateral Listening Questionnaire (QLBHE), and the Nijmegen Cochlear Implantation Inventory (NCIQ). The results of the SSQ-12 (with a 10-point score out of 10) showed that the scores of preoperative and postoperative 12 months after start-up were 6.35 and 6.46 in the SSD group, while they were 5.61 and 9.83 in the AHL group. The QLBHE scores (100 points out of 100) were 61.0 and 76.0 in the SSD group and 53.4 and 63.7 in the AHL group for the preoperative versus the postoperative 12 months after start-up. Conclusion: Patients with unilateral hearing loss can benefit from cochlear implantation: CI implantation is effective in compensating for the hearing on the affected side and reduces the accompanying tinnitus symptoms; there is a significant improvement in sound source localization and speech recognition in the presence of noise; and the quality of life is improved.

Keywords: single-sided deafness, asymmetric hearing loss, cochlear implant, unilateral hearing loss

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Authors: Okpala Charles Chikwendu, Ezeanyim Okechukwu Chiedu, Onukwuli Somto Kenneth

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The demand for lightweight and fuel-efficient automobiles has led to the use of fiber-reinforced polymer composites in place of traditional metal parts. Coir, a natural fiber, offers qualities such as low cost, good tensile strength, and biodegradability, making it a potential filler material for automotive components. However, poor interfacial adhesion between coir and polymeric matrices has been a challenge. To address poor interfacial adhesion with polymeric matrices due to their moisture content and method of preparation, the extracted coir was chemically treated using NaOH. To develop a side view mirror encasement by investigating the mechanical effect of fiber percentage composition, fiber length and percentage composition of Epoxy in a coir fiber reinforced composite, polyester was adopted as the resin for the mold, while that of the product is Epoxy. Coir served as the filler material for the product. Specimens with varied compositions of fiber loading (15, 30 and 45) %, length (10, 15, 20, 30 and 45) mm, and (55, 70, 85) % weight of epoxy resin were fabricated using hand lay-up technique, while those specimens were later subjected to mechanical tests (Tensile, Flexural and Impact test). The results of the mechanical test showed that the optimal solution for the input factors is coir at 45%, epoxy at 54.543%, and 45mm coir length, which was used for the development of a vehicle’s side view mirror encasement. The optimal solutions for the response parameters are 49.333 Mpa for tensile strength, flexural for 57.118 Mpa, impact strength for 34.787 KJ/M2, young modulus for 4.788 GPa, stress for 4.534 KN, and 20.483 mm for strain. The models that were developed using Design Expert software revealed that the input factors can achieve the response parameters in the system with 94% desirability. The study showed that coir is quite durable for filler material in an epoxy composite for automobile applications and that fiber loading and length have a significant effect on the mechanical behavior of coir fiber-reinforced epoxy composites. The coir's low density, considerable tensile strength, and bio-degradability contribute to its eco-friendliness and potential for reducing the environmental hazards of synthetic automotive components.

Keywords: coir, composite, coir fiber, coconut husk, polymer, automobile, mechanical test

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Authors: Soo-Yong Cho, Chong-Hyun Cho, Chae-Whan Rim, Sang-Kyu Choi, Jin-Gyun Kim, Ju-Seok Nam

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Recently, vertical axis wind turbines (VAWT) have been widely used to produce electricity even in urban. They have several merits such as low sound noise, easy installation of the generator and simple structure without yaw-control mechanism and so on. However, their blades are operated under the influence of the trailing vortices generated by the preceding blades. This phenomenon deteriorates its output power and makes difficulty predicting correctly its performance. In order to improve the performance of VAWT, wind power towers can be applied. Usually, the wind power tower can be constructed as a multi-story building to increase the frontal area of the wind stream. Hence, multiple sets of the VAWT can be installed within the wind power tower, and they can be operated at high elevation. Many different types of wind power tower can be used in the field. In this study, a wind power tower with circular column shape was applied, and the VAWT was installed at the center of the wind power tower. Seven guide walls were used as a strut between the floors of the wind power tower. These guide walls were utilized not only to increase the wind velocity within the wind power tower but also to adjust the wind direction for making a better working condition on the VAWT. Hence, some important design variables, such as the distance between the wind turbine and the guide wall, the outer diameter of the wind power tower, the direction of the guide wall against the wind direction, should be considered to enhance the output power on the VAWT. A numerical analysis was conducted to find the optimum dimension on design variables by using the computational fluid dynamics (CFD) among many prediction methods. The CFD could be an accurate prediction method compared with the stream-tube methods. In order to obtain the accurate results in the CFD, it needs the transient analysis and the full three-dimensional (3-D) computation. However, this full 3-D CFD could be hard to be a practical tool because it requires huge computation time. Therefore, the reduced computational domain is applied as a practical method. In this study, the computations were conducted in the reduced computational domain and they were compared with the experimental results in the literature. It was examined the mechanism of the difference between the experimental results and the computational results. The computed results showed this computational method could be an effective method in the design methodology using the optimization algorithm. After validation of the numerical method, the CFD on the wind power tower was conducted with the important design variables affecting the performance of VAWT. The results showed that the output power of the VAWT obtained using the wind power tower was increased compared to them obtained without the wind power tower. In addition, they showed that the increased output power on the wind turbine depended greatly on the dimension of the guide wall.

Keywords: CFD, performance, VAWT, wind power tower

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Authors: Matthew Conner, Leah Plocharczyk

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This study examines the role of academic libraries in support of the intellectually disabled (ID) in post-secondary education. With the growing public awareness of the ID, there has been recognition of their need for post-secondary educational opportunities. This was an unforeseen result for a population that has been associated with elementary levels of education, yet the reasons are compelling. After aging out of the school system, the ID need and deserve educational and social support as much as anyone. Moreover, the commitment to diversity in higher education rings hollow if this group is excluded. Yet, challenges remain to integrating the ID into a college curriculum. This presentation focuses on the role of academic libraries. Neglecting this vital resource for the support of the ID is not to be thought of, yet the library’s contribution is not clear. Library collections presume reading ability and libraries already struggle to meet their traditional goals with the resources available. This presentation examines how academic libraries can support post-secondary ID. For context, the presentation first examines the state of post-secondary education for the ID with an analysis of data on the United States compiled by the ThinkCollege! Project. Geographic Information Systems (GIS) and statistical analysis will show regional and methodological trends in post-secondary support of the ID which currently lack any significant involvement by college libraries. Then, the presentation analyzes a case study of a book club at the Florida Atlantic University (FAU) libraries which has run for several years. Issues such as the selection of books, effective pedagogies, and evaluation procedures will be examined. The study has found that the instruction pedagogies used by libraries can be extended through concepts of Universal Learning Design (ULD) to effectively engage the ID. In particular, student-centered, participatory methodologies that accommodate different learning styles have proven to be especially useful. The choice of text is complex and determined not only by reading ability but familiarity of subject and features of the ID’s developmental trajectory. The selection of text is not only a necessity but also promises to give insight into the ID. Assessment remains a complex and unresolved subject, but the voluntary, sustained, and enthusiastic attendance of the ID is an undeniable indicator. The study finds that, through the traditional library vehicle of the book club, academic libraries can support ID students through training in both reading and socialization, two major goals of their post-secondary education.

Keywords: academic libraries, intellectual disability, literacy, post-secondary education

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Authors: Gileade P. Freitas, Helena B. Lopes, Alann T. P. Souza, Paula G. F. P. Oliveira, Adriana L. G. Almeida, Paulo G. Coelho, Marcio M. Beloti, Adalberto L. Rosa

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Bone tissue presents great capacity to regenerate when injured by trauma, infectious processes, or neoplasia. However, the extent of injury may exceed the inherent tissue regeneration capability demanding some kind of additional intervention. In this scenario, cell therapy has emerged as a promising alternative to treat challenging bone defects. This study aimed at evaluating the effect of local injection of bone marrow-derived mesenchymal stem cells (BM-MSCs) and adipose tissue-derived mesenchymal stem cells (AT-MSCs) on bone regeneration of rat calvaria defects. BM-MSCs and AT-MSCs were isolated and characterized by expression of surface markers; cell viability was evaluated after injection through a 21G needle. Defects of 5 mm in diameter were created in calvaria and after two weeks a single injection of BM-MSCs, AT-MSCs or vehicle-PBS without cells (Control) was carried out. Cells were tracked by bioluminescence and at 4 weeks post-injection bone formation was evaluated by micro-computed tomography (μCT) and histology, nanoindentation, and through gene expression of bone remodeling markers. The data were evaluated by one-way analysis of variance (p≤0.05). BM-MSCs and AT-MSCs presented characteristics of mesenchymal stem cells, kept viability after passing through a 21G needle and remained in the defects until day 14. In general, injection of both BM-MSCs and AT-MSCs resulted in higher bone formation compared to Control. Additionally, this bone tissue displayed elastic modulus and hardness similar to the pristine calvaria bone. The expression of all evaluated genes involved in bone formation was upregulated in bone tissue formed by BM-MSCs compared to AT-MSCs while genes involved in bone resorption were upregulated in AT-MSCs-formed bone. We show that cell therapy based on the local injection of BM-MSCs or AT-MSCs is effective in delivering viable cells that displayed local engraftment and induced a significant improvement in bone healing. Despite differences in the molecular cues observed between BM-MSCs and AT-MSCs, both cells were capable of forming bone tissue at comparable amounts and properties. These findings may drive cell therapy approaches toward the complete bone regeneration of challenging sites.

Keywords: cell therapy, mesenchymal stem cells, bone repair, cell culture

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Authors: Alejandra Torres-Landa López

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Introduction: Can architecture students be creative in spaces conformed by an educational infrastructure build with paradigms of the past?, this question and others related are answered in this paper as it presents the PhD research: An anthropic conflict in Mexican Higher Education Institutes, problems and challenges of the educational infrastructure in teaching and learning History of Architecture. This research was finished in 2013 and is one of the first studies conducted nationwide in Mexico that analysis the educational infrastructure impact in learning architecture; its objective was to identify which elements of the educational infrastructure of Mexican Higher Education Institutes where architects are formed, hinder or contribute to the teaching and learning of History of Architecture; how and why it happens. The methodology: A mixed methodology was used combining quantitative and qualitative analysis. Different resources and strategies for data collection were used, such as questionnaires for students and teachers, interviews to architecture research experts, direct observations in Architecture classes, among others; the data collected was analyses using SPSS and MAXQDA. The veracity of the quantitative data was supported by the Cronbach’s Alpha Coefficient, obtaining a 0.86, figure that gives the data enough support. All the above enabled to certify the anthropic conflict in which Mexican Universities are. Major findings of the study: Although some of findings were probably not unknown, they haven’t been systematized and analyzed with the depth to which it’s done in this research. So, it can be said, that the educational infrastructure of most of the Higher Education Institutes studied, is a barrier to the educational process, some of the reasons are: the little morphological variation of space, the inadequate control of lighting, noise, temperature, equipment and furniture, the poor or none accessibility for disable people; as well as the absence, obsolescence and / or insufficiency of information technologies are some of the issues that generate an anthropic conflict understanding it as the trouble that teachers and students have to relate between them, in order to achieve significant learning). It is clear that most of the educational infrastructure of Mexican Higher Education Institutes is anchored to paradigms of the past; it seems that they respond to the previous era of industrialization. The results confirm that the educational infrastructure of Mexican Higher Education Institutes where architects are formed, is perceived as a "closed container" of people and data; infrastructure that becomes a barrier to teaching and learning process. Conclusion: The research results show it's time to change the paradigm in which we conceive the educational infrastructure, it’s time to stop seen it just only as classrooms, workshops, laboratories and libraries, as it must be seen from a constructive, urban, architectural and human point of view, taking into account their different dimensions: physical, technological, documental, social, among others; so the educational infrastructure can become a set of elements that organize and create spaces where ideas and thoughts can be shared; to be a social catalyst where people can interact between each other and with the space itself.

Keywords: educational infrastructure, impact of space in learning architecture outcomes, learning environments, teaching architecture, learning architecture

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Authors: Murray David Schane

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Though years of clinical encounters with patients with autism spectrum disorders and those with a schizoid personality the many defining diagnostic features shared between these conditions have been explored and current neurobiological differences have been reviewed; and, critical and different treatment strategies for each have been devised. The paper compares and contrasts the apparent similarities between autism spectrum disorders and the schizoid personality are found in these DSM descriptive categories: restricted range of social-emotional reciprocity; poor non-verbal communicative behavior in social interactions; difficulty developing and maintaining relationships; detachment from social relationships; lack of the desire for or enjoyment of close relationships; and preference for solitary activities. In this paper autism, fundamentally a communicative disorder, is revealed to present clinically as a pervasive aversive response to efforts to engage with or be engaged by others. Autists with the Asperger presentation typically have language but have difficulty understanding humor, irony, sarcasm, metaphoric speech, and even narratives about social relationships. They also tend to seek sameness, possibly to avoid problems of social interpretation. Repetitive behaviors engage many autists as a screen against ambient noise, social activity, and challenging interactions. Also in this paper, the schizoid personality is revealed as a pattern of social avoidance, self-sufficiency and apparent indifference to others as a complex psychological defense against a deep, long-abiding fear of appropriation and perverse manipulation. Neither genetic nor MRI studies have yet located the explanatory data that identifies the cause or the neurobiology of autism. Similarly, studies of the schizoid have yet to group that condition with those found in schizophrenia. Through presentations of clinical examples, the treatment of autists of the Asperger type is revealed to address the autist’s extreme social aversion which also precludes the experience of empathy. Autists will be revealed as forming social attachments but without the capacity to interact with mutual concern. Empathy will be shown be teachable and, as social avoidance relents, understanding of the meaning and signs of empathic needs that autists can recognize and acknowledge. Treatment of schizoids will be shown to revolve around joining empathically with the schizoid’s apprehensions about interpersonal, interactive proximity. Models of both autism and schizoid personality traits have yet to be replicated in animals, thereby eliminating the role of translational research in providing the kind of clues to behavioral patterns that can be related to genetic, epigenetic and neurobiological measures. But as these clinical examples will attest, treatment strategies have significant impact.

Keywords: autism spectrum, schizoid personality traits, neurobiological implications, critical diagnostic distinctions

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Authors: Champika Amarasinghe

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Introduction: Covid 19 pandemic was badly hit to the Sri Lankan economy during the year 2021. More than 65% of the Sri Lankan work force is engaged with small and medium scale businesses which no doubt that they had to struggle for their survival and business continuity during the pandemic. Objective: To assess the association of adherence to the new norms during the Covid 19 pandemic and maintenance of healthy working environmental conditions for business continuity. A cross sectional study was carried out to assess the OSH status and adequacy of Covid 19 preventive strategies among the 200 SME’S in selected two districts in Sri Lanka. These two districts were selected considering the highest availability of SME’s. Sample size was calculated, and probability propionate to size was used to select the SME’s which were registered with the small and medium scale development authority. An interviewer administrated questionnaire was used to collect the data, and OSH risk assessment was carried out by a team of experts to assess the OSH status in these industries. Results: According to the findings, more than 90% of the employees in these industries had a moderate awareness related to COVID 19 disease and preventive strategies such as the importance of Mask use, hand sainting practices, and distance maintenance, but the only forty percent of them were adhered to implementation of these practices. Furthermore, only thirty five percent of the employees and employers in these SME’s new the reasons behind the new norms, which may be the reason for reluctance to implement these strategies and reluctance to adhering to the new norms in this sector. The OSH risk assessment findings revealed that the working environmental organization while maintaining the distance between two employees was poor due to the inadequacy of space in these entities. More than fifty five percent of the SME’s had proper ventilation and lighting facilities. More than eighty five percent of these SME’s had poor electrical safety measures. Furthermore, eighty two percent of them had not maintained fire safety measures. Eighty five percent of them were exposed to heigh noise levels and chemicals where they were not using any personal protectives nor any other engineering controls were not imposed. Floor conditions were poor, and they were not maintaining the occupational accident nor occupational disease diseases. Conclusions: Based on the findings, proper awareness sessions were carried out by NIOSH. Six physical training sessions and continues online trainings were carried out to overcome these issues, which made a drastic change in their working environments and ended up with hundred percent implementation of the Covid 19 preventive strategies, which intern improved the worker participation in the businesses. Reduced absentees and improved business opportunities, and continued their businesses without any interruption during the third episode of Covid 19 in Sri Lanka.

Keywords: working environment, Covid 19, occupational diseases, occupational accidents

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Authors: Akshay B. Pawar, Rohit Y. Parasnis

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Heart Rate Variability (HRV) is a widely used indicator of the regulation between the autonomic nervous system (ANS) and the cardiovascular system. Besides being non-invasive, it also has the potential to predict mortality in cases involving critical injuries. The gold standard method for determining HRV is based on the analysis of RR interval time series extracted from ECG signals. However, because it is much more convenient to obtain photoplethysmogramic (PPG) signals as compared to ECG signals (which require the attachment of several electrodes to the body), many researchers have used pulse cycle intervals instead of RR intervals to estimate HRV. They have also compared this method with the gold standard technique. Though most of their observations indicate a strong correlation between the two methods, recent studies show that in healthy subjects, except for a few parameters, the pulse-based method cannot be a surrogate for the standard RR interval- based method. Moreover, the former tends to overestimate short-term variability in heart rate. This calls for improvements in or alternatives to the pulse-cycle interval method. In this study, besides the systolic peak-peak interval method (PP method) that has been studied several times, four recent PPG-based techniques, namely the first derivative peak-peak interval method (P1D method), the second derivative peak-peak interval method (P2D method), the valley-valley interval method (VV method) and the tangent-intersection interval method (TI method) were compared with the gold standard technique. ECG and PPG signals were obtained from 10 young and healthy adults (consisting of both males and females) seated in the armchair position. In order to de-noise these signals and eliminate baseline drift, they were passed through certain digital filters. After filtering, the following HRV parameters were computed from PPG using each of the five methods and also from ECG using the gold standard method: time domain parameters (SDNN, pNN50 and RMSSD), frequency domain parameters (Very low-frequency power (VLF), Low-frequency power (LF), High-frequency power (HF) and Total power or “TP”). Besides, Poincaré plots were also plotted and their SD1/SD2 ratios determined. The resulting sets of parameters were compared with those yielded by the standard method using measures of statistical correlation (correlation coefficient) as well as statistical agreement (Bland-Altman plots). From the viewpoint of correlation, our results show that the best PPG-based methods for the determination of most parameters and Poincaré plots are the P2D method (shows more than 93% correlation with the standard method) and the PP method (mean correlation: 88%) whereas the TI, VV and P1D methods perform poorly (<70% correlation in most cases). However, our evaluation of statistical agreement using Bland-Altman plots shows that none of the five techniques agrees satisfactorily well with the gold standard method as far as time-domain parameters are concerned. In conclusion, excellent statistical correlation implies that certain PPG-based methods provide a good amount of information on the pattern of heart rate variation, whereas poor statistical agreement implies that PPG cannot completely replace ECG in the determination of HRV.

Keywords: photoplethysmography, heart rate variability, correlation coefficient, Bland-Altman plot

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Hyeuk Ju Ko, Eui Ju Lee

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Many electronic devices are powered by various rechargeable batteries such as lithium-ion today, but occasionally the batteries undergo thermal runaway and cause fire, explosion, and other hazards. If a battery fire should occur in an electronic device of vehicle and aircraft cabin, it is important to quickly extinguish the fire and cool the batteries to minimize safety risks. Attempts to minimize these risks have been carried out by many researchers but the number of study on the successful extinguishment is limited. Because most rechargeable batteries are operated on the ion state with electron during charge and discharge of electricity, and the reaction of this electrolyte has a big difference with normal combustion. Here, we focused on the effect of ions on reaction stability and pollutant emissions during combustion process. The other importance for understanding ionized fuel combustion could be found in high efficient and environment-friendly combustion technologies, which are used to be operated an extreme condition and hence results in unintended flame instability such as extinction and oscillation. The use of electromagnetic energy and non-equilibrium plasma is one of the way to solve the problems, but the application has been still limited because of lack of excited ion effects in the combustion process. Therefore, the understanding of ion role during combustion might be promised to the energy safety society including the battery safety. In this study, the effects of an ionized fuel on the flame stability and pollutant emissions were experimentally investigated in the hydrocarbon jet diffusion flames. The burner used in this experiment consisted of 7.5 mm diameter tube for fuel and the gaseous fuels were ionized with the ionizer (SUNJE, SPN-11). Methane (99.9% purity) and propane (commercial grade) were used as a fuel and open ambient air was used as an oxidizer. As the performance of ionizer used in the experiment was evaluated at first, ion densities of both propane and methane increased linearly with volume flow rate but the ion density of propane is slightly higher than that of methane. The results show that the overall flame stability and shape such as flame length has no significant difference even in the higher ion concentration. However, the fuel ionization affects to the pollutant emissions such as NOx and soot. NOx and CO emissions measured in post flame region decreased with increasing fuel ionization, especially at high fuel velocity, i.e. high ion density. TGA analysis and morphology of soot by TEM indicates that the fuel ionization makes soot to be matured.

Keywords: battery fires, ionization, jet flames, stability, NOx and soot

Procedia PDF Downloads 184

Authors: Nidhi Choudhary, Silke A. Peeters, Ciaran T. Lennon, Dmytro Besprozvannyy, Harm C. M. Knoops, Robert H. Hadfield

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Superconducting Nanowire Single Photon Detectors (SNSPDs) have become leading devices in quantum optics and photonics, known for their exceptional efficiency in detecting single photons from ultraviolet to mid-infrared wavelengths with minimal dark counts, low noise, and reduced timing jitter. Recent advancements in materials science focus attention on refractory metal thin films such as NbN and NbTiN to enhance the optical properties and superconducting performance of SNSPDs, opening the way for next-generation detectors. These films have been deposited by several different techniques, such as atomic layer deposition (ALD), plasma pro-advanced plasma processing (ASP) and magnetron sputtering. The fabrication flexibility of these films enables precise control over morphology, crystallinity, stoichiometry and optical properties, which is crucial for optimising the SNSPD performance. Hence, it is imperative to study the optical and superconducting properties of these materials across a wide range of wavelengths. This study provides a comprehensive analysis of the optical and superconducting properties of some important materials in this category (NbN, NbTiN) by different deposition methods. Using Variable angle ellipsometry spectroscopy (VASE), we measured the refractive index, extinction, and absorption coefficient across a wide wavelength range (200-1700 nm) to enhance light confinement for optical communication devices. The critical temperature and sheet resistance were measured using a four-probe method in a custom-built, cryogen-free cooling system with a Sumitomo RDK-101D cold head and CNA-11C compressor. Our results indicate that ALD-deposited NbN shows a higher refractive index and extinction coefficient in the near-infrared region (~1500 nm) than sputtered NbN of the same thickness. Further, the analysis of the optical properties of plasma pro-ASP deposited NbTiN was performed at different substrate bias voltages and different thicknesses. The analysis of substrate bias voltage indicates that the maximum value of the refractive index and extinction coefficient observed for the substrate biasing of 50-80 V across a substrate bias range of (0 V - 150 V). The optical properties of sputtered NbN films are also investigated in terms of the different substrate temperatures during deposition (100 °C-500 °C). We find the higher the substrate temperature during deposition, the higher the value of the refractive index and extinction coefficient has been observed. In all our superconducting thin films ALD-deposited NbN films possess the highest critical temperature (~12 K) compared to sputtered (~8 K) and plasma pro-ASP (~5 K).

Keywords: optical communication, thin films, superconductivity, atomic layer deposition (ALD), niobium nitride (NbN), niobium titanium nitride (NbTiN), SNSPD, superconducting detector, photon-counting.

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Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

Procedia PDF Downloads 312

Authors: Laura Helena Caicedo Lopez, Luis Miguel Contreras Medina, Ramon Gerardo Guevara Gonzales, Juan E. Andrade

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In this study, we evaluated the effect of three different hydric stress conditions: Low (LHS), medium (MHS), and high (HHS) on capsaicinoid content and enzyme regulation of C. annuum plants. Five main peaks were detected using a 2 Hz resolution vibrometer laser (Polytec-B&K). These peaks or “characteristic frequencies” were used as acoustic emissions (AEs) treatment, transforming these signals into audible sound with the frequency (Hz) content of each hydric stress. Capsaicinoids (CAPs) are the main, secondary metabolites of chili pepper plants and are known to increase during hydric stress conditions or short drought-periods. The AEs treatments were applied in two plant stages: the first one was in the pre-anthesis stage to evaluate the genes that encode the transcription of enzymes responsible for diverse metabolic activities of C. annuum plants. For example, the antioxidant responses such as peroxidase (POD), superoxide dismutase (Mn-SOD). Also, phenyl-alanine ammonia-lyase (PAL) involved in the biosynthesis of the phenylpropanoid compounds. The chalcone synthase (CHS) related to the natural defense mechanisms and species-specific aquaporin (CAPIP-1) that regulate the flow of water into and out of cells. The second stage was at 40 days after flowering (DAF) to evaluate the biochemical effect of AEs related to hydric stress on capsaicinoids production. These two experiments were conducted to identify the molecular responses of C. annuum plants to AE. Moreover, to define AEs could elicit any increase in the capsaicinoids content after a one-week exposition to AEs treatments. The results show that all AEs treatment signals (LHS, MHS, and HHS) were significantly different compared to the non-acoustic emission control (NAE). Also, the AEs induced the up-regulation of POD (~2.8, 2.9, and 3.6, respectively). The gene expression of another antioxidant response was particularly treatment-dependent. The HHS induced and overexpression of Mn-SOD (~0.23) and PAL (~0.33). As well, the MHS only induced an up-regulation of the CHs gene (~0.63). On the other hand, CAPIP-1 gene gas down-regulated by all AEs treatments LHS, MHS, and HHS ~ (-2.4, -0.43 and -6.4, respectively). Likewise, the down-regulation showed particularities depending on the treatment. LHS and MHS induced downregulation of the SOD gene ~ (-1.26 and -1.20 respectively) and PAL (-4.36 and 2.05, respectively). Correspondingly, the LHS and HHS showed the same tendency in the CHs gene, respectively ~ (-1.12 and -1.02, respectively). Regarding the elicitation effect of AE on the capsaicinoids content, additional treatment controls were included. A white noise treatment (WN) to prove the frequency-selectiveness of signals and a hydric stressed group (HS) to compare the CAPs content. Our findings suggest that WN and NAE did not present differences statically. Conversely, HS and all AEs treatments induced a significant increase of capsaicin (Cap) and dihydrocapsaicin (Dcap) after one-week of a treatment. Specifically, the HS plants showed an increase of 8.33 times compared to the NAE and WN treatments and 1.4 times higher than the MHS, which was the AEs treatment with a larger induction of Capsaicinoids among treatments (5.88) and compared to the controls.

Keywords: acoustic emission, capsaicinoids, elicitors, hydric stress, plant signaling

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Authors: Sunday Moses Ojelabi

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Safety is the protection of the crew, passenger and equipment itself, as well as those living and working near bodies of water, from hazardous situations. To assure safety, watch keeping is paramount because neglecting your watchkeeping can lead to hazardous situations. Navigation is the assignment of a sailor to a specific route on a vessel to operate. Navigation is the process of planning, managing, and directing a vessel safely to the desired destination with the aid of intense and efficient watch keeping. Safety, i,e, all measures done to preserve the welfare of marine life, maritime infrastructure, facilities, ships, offshore installations, crew, and passengers, as well as the preservation of navigation and the ease of maritime trade, are referred to as safety measures;. When it comes to health, the absence of a proper first aid kit will affect injured sailors and passengers. Not using goggles while shipping, ear muffs, etc., in the course of maintenance can be hazardous. Watchkeeping: i.e the specific dutiies assigned to a personnel in a vessel to see to its continous smooth functionality. Your lookout or watch officer [officer on navigational duty] must be active at all times in the course of duty. Navigation refers to the technique of precisely determining a craft or vehicle's position and directing its motion along a particular course. The seafarers are not being put through regular seminars, training, and orientations. In parts of West Africa, sailors go to school without being able to secure jobs until their papers expire. For that, they won’t go for another Standard Trainning Certification and Watch keeping for Seafarers to upgrade their certificate. In light of this, they are not familiar with the new vessels in the country, and for this, they can`t meet the safety, watch keeping, and navigation standards. Also, shipping companies and ship owners are being selfish by not putting the proper things needed onboard regarding safety, watchkeeping, and navigational equipment. The questions raised in these presentations are the breakdown of the safety activities, watch keeping effectiveness, and navigational accuracy. All safety and watch keeping regulations should be applied efficiently. The problem identified includes a lack of safety instruments onboard vessels in African waters. Also, inadequate proper watchkeeping due to the excess workload on the seafarers can lead to an improper lookout, which gives room to collision, hijacking, and piracy. The impact of this research is to inform African seafarers, shipping companies, and ship owners of the necessary information concerning the safety of their lives and that of their passengers, cargo, and equipment.

Keywords: standard of training, certification, watch keeping for seafarers, navigation, safety, watchkeeping

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Authors: Dahia Chibouti, Benoit Trouette, Eric Chenier

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With the development of micro-electro-mechanical systems (MEMS), understanding fluid flow and heat transfer at the micrometer scale is crucial. In the case where the flow characteristic length scale is narrowed to around ten times the mean free path of gas molecules, the classical fluid mechanics and energy equations are still valid in the bulk flow, but particular attention must be paid to the gas/solid interface boundary conditions. Indeed, in the vicinity of the wall, on a thickness of about the mean free path of the molecules, called the Knudsen layer, the gas molecules are no longer in local thermodynamic equilibrium. Therefore, macroscopic models based on the continuity of velocity, temperature and heat flux jump conditions must be applied at the fluid/solid interface to take this non-equilibrium into account. Although these macroscopic models are widely used, the assumptions on which they depend are not necessarily verified in realistic cases. In order to get rid of these assumptions, simulations at the molecular scale are carried out to study how molecule interaction with walls can change the fluid flow and heat transfers at the vicinity of the walls. The developed approach is based on a kind of heterogeneous multi-scale method: micro-domains overlap the continuous domain, and coupling is carried out through exchanges of information between both the molecular and the continuum approaches. In practice, molecular dynamics describes the fluid flow and heat transfers in micro-domains while the Navier-Stokes and energy equations are used at larger scales. In this framework, two kinds of micro-simulation are performed: i) in bulk, to obtain the thermo-physical properties (viscosity, conductivity, ...) as well as the equation of state of the fluid, ii) close to the walls to identify the relationships between the slip velocity and the shear stress or between the temperature jump and the normal temperature gradient. The coupling strategy relies on an implicit formulation of the quantities extracted from micro-domains. Indeed, using the results of the molecular simulations, a Bayesian regression is performed in order to build continuous laws giving both the behavior of the physical properties, the equation of state and the slip relationships, as well as their uncertainties. These latter allow to set up a learning strategy to optimize the number of micro simulations. In the present contribution, the first results regarding this coupling associated with the learning strategy are illustrated through parametric studies of convergence criteria, choice of basis functions and noise of input data. Anisothermic flows of a Lennard Jones fluid in micro-channels are finally presented.

Keywords: multi-scale, microfluidics, micro-channel, hybrid approach, coupling

Procedia PDF Downloads 164

Authors: Prince Vivek, Vijay Kumar Bharti, Deepak Kumar, Rohit Kumar, Kapil Nehra, Dhananjay Singh, Om Prakash Chaurasia, Bhuvnesh Kumar

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High altitude native people still rely heavily on animal transport for logistic support at eastern and northern Himalayas regions. The prevalent mountainous terrains and rugged region are not suitable for the motorized vehicle to use in logistic transport. Therefore, people required high endurance pack animals for load carrying and riding. So far to the best of our knowledge, no studies have been taken to evaluate the effect of loads on the physiology of ponies in high altitude region. So, in this view, we evaluated variation in physiological, hematological, biochemical, and cytokines indices of Zanskar ponies during load carrying at high altitude. Total twelve (12) of Zanskar ponies, mare, age 4-6 years selected for this study, Feed was offered at 2% of body weight, and water ad libitum. Ponies were divided into three groups; group-A (without load), group-B (60 kg), and group-C (80 kg) of backpack loads. The track was very narrow and slippery with gravel, uneven with a rocky surface and has a steep gradient of 4 km uphill at altitude 3291 to 3500m. When we evaluate these parameters, it is understood that the heart rate, pulse rate, and respiration rate was significantly increased in 80 kg group among the three groups. The hematology parameters viz. hemoglobin significantly increased in 80 kg group on 1st day after load carrying among the three groups which was followed by control and 60 kg whereas, PCV, lymphocytes, monocytes percentage significantly increased however, ESR and eosinophil % significantly decreased in 80 kg group after load carrying on 7th day after load carrying among the three groups which were followed by control and 60 kg group. In biochemical parameters viz. LA, LDH, TP, hexokinase (HK), cortisol (CORT), T3, GPx, FRAP and IL-6 significantly increased in 80 kg group on the 7th day after load carrying among the three groups which were followed by control and 60 kg group. The ALT, ALB, GLB, UR, and UA significantly increased in 80 kg group on the 7th day before and after load carrying among the three groups which were followed by control and 60 kg group. The CRT, AST, and CK-MB were significantly increased in 80 kg group on the 1st and 7th day after load carrying among the three groups which were followed by control and 60 kg group. It has been concluded that, heart rate, respiration rate, hematological indices like PCV, lymphocytes, monocytes, Hb and ESR, biochemical indices like lactic acid, LDH, TP, HK, CORT, T3, ALT, AST and CRT, ALB, GLB, UR, UA, GPx, FRAP and IL-6 are important biomarkers to assess effect of load on animal physiology and endurance. Further, this result has revealed the strong correlation of change in biomarkers level with performance in ponies during load carry. Hence, these parameters might be used for the performance of endurance of Zanskar ponies in the high mountain region.

Keywords: biochemical, endurance, high altitude, load, ponies

Procedia PDF Downloads 280

Authors: Subrat Kumar Bhattamisra, Vivian Lee Yean Yan, Chin Koh Lee, Chew Hui Kuean, Yun Khoon Liew, Mayuren Candasamy

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Geraniol, an acyclic monoterpenoid is the main active constituent in the essential oils of rose and palmorosa. Antioxidant, antibacterial, anticancer and antiulcer activity of geraniol was reported by many researchers. The present investigation was designed to study in vivo antiulcer and anti-Helicobacter pylori activity of geraniol. Antiulcer and anti-H. pylori activity of geraniol was evaluated on acetic acid plus H. pylori induced ulcer in rats. Acetic acid (0.03 mL) was injected to the sub-serosal layer of the stomach through laparotomy under anaesthesia. Orogastric inoculation of H. pylori (ATCC 43504) was done twice daily for 7 days. Geraniol (15 and 30 mg/kg), vehicle and standard drugs (Amoxicillin, 50 mg/kg; clarithromycin, 25 mg/kg & omeprazole, 20 mg/kg) was administered twice daily for 14 days. Antiulcer activity of geraniol was examined by the determination of gastric ulcer index, measuring the volume of gastric juice, pH and total acidity, myeloperoxidase activity and histopathological examination. Histopathological investigation for the presence of inflammation, white blood cell infiltration, edema, the mucosal damage was studied. The presence of H. pylori was detected by placing a biopsy sample from antral part of the stomach into rapid urease test. Ulcer index in H. pylori inoculated control group was 4.13 ± 0.85 and was significantly (P < 0.05) lowered in geraniol (30 mg/kg) and reference drug treated group. Geraniol increase the pH of the gastric juice (2.18 ± 0.13 in control vs. 4.14 ± 0.57 in geraniol 30mg/kg) and lower total acidity significantly (P < 0.01) in geraniol (15 & 30 mg/kg). Myeloperoxidase (MPO) activity was measured in stomach homogenate of all the groups. H. pylori control group has significant (P < 0.05) increase in MPO activity compared to normal control group. Geraniol (30 mg/kg) was showed significant (P < 0.05) and most effective among all the groups. Histopathological examination of rat stomach was scored and the total score for H. pylori control group was 8. After geraniol (30 mg/kg) and reference drug treatment, the histopathological score was significantly decreased and it was observed to be 3.5 and 2.0 respectively. Percentage inhibition of H. pylori infection in geraniol (30 mg/kg) and reference drug were found to be 40% and 50% respectively whereas, 100% infection in H. pylori control group was observed. Geraniol exhibited significant antiulcer and anti- H. pylori activity in the rats. Thus, geraniol has the potential for the further development as an effective medication in treating H. pylori associated ulcer.

Keywords: geraniol, helicobacter pylori atcc 43504, myeloperoxidase, ulcer

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Priya Jaswal, Vivek, S. K. Sinha

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One of the most important and complicated factors influencing the functional performance of unpaved roads is traffic loading. The complexity of traffic loading is caused by the variable magnitude and frequency of load, which causes unpaved roads to fail prematurely. Unpaved roads are low-volume roads, and as peri-urbanization increases, unpaved roads act as a means to boost the rural economy. This has also increased traffic on unpaved roads, intensifying the issue of settlement, rutting, and fatigue failure. This is a major concern for unpaved roads built on poor subgrade soil, as excessive rutting caused by heavy loads can cause driver discomfort, vehicle damage, and an increase in maintenance costs. Some researchers discovered that when a consistent static load is exerted as opposed to a rapidly changing load, the rate of deformation of unpaved roads increases. Previously, some of the most common methods for overcoming the problem of rutting and fatigue failure included chemical stabilisation, fibre reinforcement, and so on. However, due to their high cost, engineers' attention has shifted to geotextiles which are used as reinforcement in unpaved roads. Geotextiles perform the function of filtration, lateral confinement of base material, vertical restraint of subgrade soil, and the tension membrane effect. The use of geotextiles in unpaved roads increases the strength of unpaved roads and is an economically viable method because it reduces the required aggregate thickness, which would need less earthwork, and is thus recommended for unpaved road applications. The majority of geotextiles used previously were polymeric, but with a growing awareness of sustainable development to preserve the environment, researchers' focus has shifted to natural fibres. Coir is one such natural fibre that possesses the advantage of having a higher tensile strength than other bast fibres, being eco-friendly, low in cost, and biodegradable. However, various researchers have discovered that the surface of coir fibre is covered with various impurities, voids, and cracks, which act as a plane of weakness and limit the potential application of coir geotextiles. To overcome this limitation, chemical surface modification of coir geotextiles is widely accepted by researchers because it improves the mechanical properties of coir geotextiles. The current paper reviews the effect of using treated coir geotextiles as reinforcement on the load-deformation behaviour of a two-layered unpaved road model.

Keywords: coir, geotextile, treated, unpaved

Procedia PDF Downloads 91

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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 258

Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

Abstract:

In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

Procedia PDF Downloads 140