Search results for: temporal convolutional net

Authors: Muhammad A. Ashraf, Scott Steinmetz, Matthew J. Dunn, Assaad R. Masri

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This study focuses on the evolution of soot and soot precursors in three different piloted diffusion turbulent flames. The fuel composition is as follow flame A (ethylene/nitrogen, 2:3 by volume), flame B (ethylene/air, 2:3 by volume), and flame C (pure methane). These flames are stabilized using a 4mm diameter jet surrounded by a pilot annulus with an outer diameter of 15 mm. The pilot issues combustion products from stoichiometric premixed flames of hydrogen, acetylene, and air. In all cases, the jet Reynolds number is 10,000, and air flows in the coflow stream at a velocity of 5 m/s. Time-resolved laser-induced fluorescence (LIF) is collected at two wavelength bands in the visible (445 nm) and UV regions (266 nm) along with laser-induced incandescence (LII). The combined results are employed to study concentration, size, and growth of soot and precursors. A set of four fast photo-multiplier tubes are used to record emission data in temporal domain. A 266nm laser pulse preferentially excites smaller nanoparticles which emit a fluorescence spectrum which is analysed to track the presence, evolution, and destruction of nanoparticles. A 1064nm laser pulse excites sufficiently large soot particles, and the resulting incandescence is collected at 1064nm. At downstream and outer radial locations, intermittency becomes a relevant factor. Therefore, data collected in turbulent flames is conditioned to account for intermittency so that the resulting mean profiles for scattering, fluorescence, and incandescence are shown for the events that contain traces of soot. It is found that in the upstream regions of the ethylene-air and ethylene-nitrogen flames, the presence of soot precursors is rather similar. However, further downstream, soot concentration grows larger in the ethylene-air flames.

Keywords: laser induced incandescence, laser induced fluorescence, soot, nanoparticles

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Authors: Naim Izet Kajtazi

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Context: Although rare, glomus tumor (i.e., nonchromaffin chemodectomas and paragan¬gliomas) is the most common middle ear tumor, with female predominance. Pre-operative embolization is often required to devascularize the hypervascular tumor for better surgical outcomes. Process: A 35-year-old female presented with episodes of frequent dizziness, ear fullness, and right ear tinnitus for 12 months. Head imaging revealed a right glomus tympanicum tumor. She underwent pre-operative endovascular embolization of the glomus tympanicum tumor with surgical, cyanoacrylate-based glue. Immediately after the procedure, she developed drowsiness and severe pain in the right temporal region. Further investigations revealed a right cerebellar stroke in the posterior inferior cerebellar artery territory. She was treated with intravenous heparin, followed by one year of oral anticoagulation. With rehabilitation, she significantly recovered from her post embolization stroke. However, the tumor was resected at another institution. Ten years later, follow-up imaging indicated a gradual increase in the size of the glomus jugulare tumor, compressing the nearby critical vascular structures. She subsequently received radiation therapy to treat the residual tumor. Outcome: Currently, she has no neurological deficit, but her mild dizziness, right ear tinnitus, and hearing impairment persist. Relevance: This case highlights the complex nature of these tumors, which often bring challenges to the patients as well as treatment teams. The multi-disciplinary team approach is necessary to tailor the management plan for individual tumors. Although embolization is a safe procedure, careful attention and thoughtful anatomic knowledge regarding dangerous anastomosis are essential to avoid devastating complications. Complications occur due to encountered vessel anomalies and new anastomoses formed during the gluing and changes in hemodynamics.

Keywords: stroke, embolization, MRI brain, cerebral angiogram

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Authors: Racha El Kadiri, Mohamed Sultan, Henrique Momm, Zachary Blair, Rachel Schultz, Tamer Al-Bayoumi

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The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region.

Keywords: rainfall, neural networks, climatic indices, Mediterranean

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Authors: Katie Kilgour, Brendan Turner, Carly Catella, Michael Daniele, Stefano Menegatti

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In vivo, the extracellular matrix (ECM) provides biochemical and mechanical properties that are instructional to resident cells to form complex tissues with characteristics to develop and support vascular networks. In vitro, the development of vascular networks can be guided by biochemical patterning of substrates via spatial distribution and display of peptides and growth factors to prompt cell adhesion, differentiation, and proliferation. We have developed a technique utilizing peptide ligands that specifically bind vascular endothelial growth factor (VEGF), erythropoietin (EPO), or angiopoietin-1 (ANG1) to spatiotemporally distribute growth factors to cells. This allows for the controlled release of each growth factor, ultimately enhancing the formation of a vascular network. Our engineered tissue constructs (ETCs) are fabricated out of gelatin methacryloyl (GelMA), which is an ideal substrate for tailored stiffness and bio-functionality, and covalently patterned with growth factor specific peptides. These peptides mimic growth factor receptors, facilitating the non-covalent binding of the growth factors to the ETC, allowing for facile uptake by the cells. We have demonstrated in the absence of cells the binding affinity of VEGF, EPO, and ANG1 to their respective peptides and the ability for each to be patterned onto a GelMA substrate. The ability to organize growth factors on an ETC provides different functionality to develop organized vascular networks. Our results demonstrated a method to incorporate biochemical cues into ETCs that enable spatial and temporal control of growth factors. Future efforts will investigate the cellular response by evaluating gene expression, quantifying angiogenic activity, and measuring the speed of growth factor consumption.

Keywords: growth factor, hydrogel, peptide, angiogenesis, vascular, patterning

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Atitallah Sofien, Bouyahia Olfa, Krifi Farah, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Cutis marmorata telangiectatica congenita (CMTC) is a rare cutaneous vascular malformation. It most often appears at birth or during the first days of life. Its origin is still unknown. It associates a livedo with telangiectasias of diffuse or segmental topography. In rare cases, it can be associated with neurological disorders such as macrocephaly and, less frequently, with epilepsy. Methodology: We report a case of an infant with Macrocephaly- Cutis marmorata telangiectatica congenita syndrome associated with epilepsy. Results: This is the case of a one month and 15 days old female infant from a non-consanguineous marriage, admitted for a status epilepticus in the context of apyrexia. Infectious and metabolic causes had been eliminated. Physical examination had shown non-infiltrated and reticular livedoid erythematous patches affecting the left upper limb and atrophic on the back of the left hand. Cerebral magnetic resonance imaging (MRI) showed thin layers of bifrontal, temporal, and left parietal hygromas associated with the widening of the bifrontal subarachnoid spaces. The electroencephalogram showed a well-organized sleep tracing with a single right occipital paroxysmal abnormality. Antiepileptic treatment has been administered with good clinical evolution and regression of the skin lesion and a control electroencephalogram without abnormality. Conclusion: This observation illustrates an association of CMTC with both macrocephaly and epilepsy. This pathology, which is relatively benign and has a good prognosis, generally does not require treatment. However, a detailed examination must be carried out, and a follow-up plan must be put in place for each patient presenting with CMTC, given the risk of association with other abnormalities, which can be potentially serious.

Keywords: cutis marmorata telangiectatica congenita, macrocephaly, epilepsy, children

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: G. C. Joshi, M. Paul, B. K. Kalita, V. Ranga, J. S. Rawat, P. S. Rawat

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Being a habitat of the global village, every place has established connection through the strength and power of social media piercing through the political boundaries. Social media is a digital platform, where people across the world can interact as it has advantages of being universal, anonymous, easily accessible, indirect interaction, gathering and sharing information. The power of social media lies in the intensity of sharing extreme opinions or feelings, in contrast to the personal interactions which can be easily mapped in the form of Sentiment Mapping. The easy access to social networking sites such as Facebook, Twitter and blogs made unprecedented opportunities for citizens to voice their opinions loaded with dynamics of emotions. These further influence human thoughts where social media plays a very active role. A recent incident of public importance was selected as a case study to map the sentiments of people through Twitter. Understanding those dynamics through the eye of an ordinary people can be challenging. With the help of R-programming language and by the aid of GIS techniques sentiment maps has been produced. The emotions flowing worldwide in the form of tweets were extracted and analyzed. The number of tweets had diminished by 91 % from 25/08/2017 to 31/08/2017. A boom of sentiments emerged near the origin of the case, i.e., Delhi, Haryana and Punjab and the capital showed maximum influence resulting in spillover effect near Delhi. The trend of sentiments was prevailing more as neutral (45.37%), negative (28.6%) and positive (21.6%) after calculating the sentiment scores of the tweets. The result can be used to know the spatial distribution of digital penetration in India, where highest concentration lies in Mumbai and lowest in North East India and Jammu and Kashmir.

Keywords: sentiment mapping, digital literacy, GIS, R statistical language, spatio-temporal

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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Authors: Dishari Rakshit, Mitchell Gallagher

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The global landscape is witnessing a disconcerting surge in democratic backsliding, engendering concerns over the rise of autocratisation. This research demonstrates the intricate relationship between a nation's domestic propensity for autocratic governance and its trade relations with China. Giving prominence to Belt and Road Initiative (BRI) investments, this study adopts a rigorous neorealist framework to discern the complexities of nations' economic interests amidst an anarchic milieu and how these interests may transcend steadfast adherence to democratic principles. The burgeoning bipolarity in the international political setting serves as a backdrop to our inquiry. To operationalise our hypothesis, we conduct a large-scale 'N' study, encompassing a comprehensive global dataset comprising countries' democracy indicators, total trade volume with China, and cumulative Chinese BRI investments over a substantial temporal expanse. By meticulously examining BRI signatories’, we aim to ascertain the potential accentuation of democratic backsliding among these nations. To test our empirical underpinning, we will validate our findings through cogent case studies. Our analysis adds to the scholarship on multifaceted interactions between trade dynamics and democratic governance within the fabric of the international political landscape. In its culmination, the paper addresses the question- has the erstwhile grandeur of bipolarity resurfaced in the contemporary global panorama? Concurrently, we explore the nexus between the ascendant wave of autocratisation as a by-product of the Beijing Consensus? Pertinent to policymakers, our discoveries stand poised to furnish a comprehensive grasp of the manifold implications arising from the deepening entanglements with China under the auspices of the BRI.

Keywords: democracy, autocracy, china, belt road initiative, international political economy

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Authors: Muhd. Barzani Gasim, Mohd. Ekhwan Toriman, Mohd. Khairul Amri Kamarudin, Azman Azid, Siti Humaira Haron, Muhammad Hafiz Md. Saad

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Malaysia is a country in Southeast Asia that constantly exposed to flooding and landslide. The disaster has caused some troubles such loss of property, loss of life and discomfort of people involved. This problem occurs as a result of climate change leading to increased stream flow rate as a result of disruption to regional hydrological cycles. The aim of the study is to determine hydrologic processes in the east coasts of Peninsular Malaysia, especially in Kelantan Basin. Parameterized to account for the spatial and temporal variability of basin characteristics and their responses to climate variability. For hydrological modeling of the basin, the Soil and Water Assessment Tool (SWAT) model such as relief, soil type, and its use, and historical daily time series of climate and river flow rates are studied. The interpretation of Landsat map/land uses will be applied in this study. The combined of SWAT and climate models, the system will be predicted an increase in future scenario climate precipitation, increase in surface runoff, increase in recharge and increase in the total water yield. As a result, this model has successfully developed the basin analysis by demonstrating analyzing hydrographs visually, good estimates of minimum and maximum flows and severe floods observed during calibration and validation periods.

Keywords: east coasts of Peninsular Malaysia, Kelantan river basin, minimum and maximum flows, severe floods, SWAT model

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Authors: John Ahluwalia

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As an affluent first-world nation, Canada took swift and comprehensive action during the outbreak of the SARS-CoV-2 (COVID-19) pandemic compared to other countries in the same socio-economic cohort. The United States has stumbled to overcome obstacles most developed nations have faced, which has led to significantly more per capita cases and deaths. The initial outbreaks of COVID-19 occurred in the US and Canada within days of each other and posed similar potentially catastrophic threats to public health, the economy, and governmental stability. On a macro level, events that take place in the US have a direct impact on Canada. For example, both countries tend to enter and exit economic recessions at approximately the same time, they are each other’s largest trading partners, and their currencies are inexorably linked. Variables intrinsic to Canada’s national infrastructure have been instrumental in the country’s efforts to flatten the curve of COVID-19 cases and deaths. Canada’s coordinated multi-level governmental effort has allowed it to create and enforce policies related to COVID-19 at both the national and provincial levels. Canada’s policy of universal health care is another variable. Health care and public health measures are enforced on a provincial level, and it is within each province’s jurisdiction to dictate standards for public safety based on scientific evidence. Rather than introducing confusion and the possibility of competition for resources such as PPE and vaccines, Canada’s multi-level chain of government authority has provided consistent policies supporting national public health and local delivery of medical care. This paper will demonstrate that the coordinated efforts on provincial and federal levels have been the linchpin in Canada’s relative success in containing the deadly spread of the COVID-19 virus.

Keywords: COVID-19, canada, GIS, geospatial analysis

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Authors: P. M. Kundu, L. R. Singo, J. O. Odiyo

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Luvuvhu River catchment in South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Inter-tropical Convergence Zone (ITCZ). The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyze the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency analysis was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges was obtained by direct measurements in the field and from the Department of Water. A digital elevation model was generated from contour maps available at http://www.ngi.gov.za. The results showed that land cover changes had impacted negatively to the hydrology of the catchment. Peak discharges in the whole catchment were noted to have increased by at least 17% over the period while flood volumes were noted to have increased by at least 11% over the same period. The flood time to peak indicated a decreasing trend, in the range of 0.5 to 1 hour within the years. The synergism between remotely sensed digital data and GIS for land surface analysis and modeling was realized, and it was therefore concluded that hydrologic modeling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.

Keywords: catchment, digital elevation model, hydrological model, routing, runoff

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Authors: Francisco Miroslav Ulloa-Stanojlovic, Gina Polo, Ricardo Augusto Dias

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In Brazil, there is a high incidence of rabies in herbivores of economic interest (HEI) transmitted by the common vampire bat Desmodus rotundus, the presence of human rabies cases and the huge economic losses in the world's largest cattle industry, it is important to assist the National Program for Control of Rabies in herbivores in Brazil, that aims to reduce the incidence of rabies in HEI populations, mainly through epidemiological surveillance, vaccination of herbivores and control of vampire-bat roosts. Material and Methods: A spatiotemporal retrospective Kulldorff's spatial scan statistic based on a Poisson model and Monte Carlo simulation and an Anselin's Local Moran's I statistic were used to uncover spatial clustering of HEI rabies from 2000 – 2014. Results: Were identify three important clusters with significant year-to-year variation (Figure 1). In 2000, was identified one area of clustering in the North region, specifically in the State of Tocantins. Between the year 2000 and 2004, a cluster centered in the Midwest and Southeast region including the States of Goiás, Minas Gerais, Rio de Janeiro, Espirito Santo and São Paulo was prominent. And finally between 2000 and 2005 was found an important cluster in the North, Midwest and South region. Conclusions: The HEI rabies is endemic in the country, in addition, appears to be significant differences among the States according to their surveillance services, that may be difficulting the control of the disease, also other factors could be influencing in the maintenance of this problem like the lack of information of vampire-bat roosts identification, and limited human resources for realization of field monitoring. A review of the program control by the authorities it’s necessary.

Keywords: Brazil, Desmodus rotundus, herbivores, rabies

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Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Aayush Anant, Roshni Thendiyath

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Aridity impacts on agriculture, as well as ecological, human health, and economic activities. In the present study, the effect of climate change on aridity index has been analysed in South Bihar for the past 30 year period by five types of aridity indices as Lang AI, De-Martonne AI, Erinc AI, Pinna combinative AI and UNEP AI. For the study of aridity index, the analysis of rainfall and temperature is significant. Rainfall was analysed for 30 year period from data of 23 gridded stations in for the period 1991-2020. The results show that rainfall pattern was decreasing with respect to previous decades for majority of stations. Trend of maximum, minimum and mean annual temperature has been observed, which shows increasing trend. Structural breakpoint was observed for mean annual temperature data series in year 2004. In period 1991-2004 mean annual temperature was 25.25 ºC, and in period 2005-2020, mean annual temperature was 25.7 ºC. Average aridity index has been calculated by all the above mentioned methods for whole 30 period. Lang AI shows that eastern part of study area is Humid type, and rest all is semi arid. De-Martonne AI also reveals that east part is humid, but rest of the study area is moist sub humid. According to Erinc AI and Pinna, combinative AI shows that whole south Bihar is dry sub humid and semi dry, respectively. UNEP AI shows most of the part as sub humid, and very small part in west is semi arid, while small part of east is humid. Temporal distribution of all the aridity indices shows a decreasing trend. This indicates a decrease in the humid areas in south Bihar for the selected time period.

Keywords: drought, aridity index, climate change, rainfall, temperature

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Authors: Abdul Ghani Khan

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This paper focuses on the Buddhist rock carvings in the Diamer-Basha reservoir area, Gilgit-Baltistan, which is perhaps the largest rock art province of the world. The study region has thousands of rock carvings, particularly of the stupa carvings, engraved by artists, devotees or pilgrims, merchants have left their marks in the landscape or for the propagation of Buddhism. The Pak-German Archaeological Mission prepared, documented, and published the extensive catalogues of these carvings. Though, to date, very little systematic or statistically driven analysis was undertaken for in-depth understandings of the Buddhist rock carving tradition of the study region. This paper had made an attempt to examine stupa carvings and their constituent parts from the five selected sites, namely Oshibat, Shing Nala, Gichi Nala, Dadam Das, and Chilas Bridge. The statistical analyses and classification of the stupa carvings and their chronological contexts were carried out with the help of modern scientific tools such as STATA, FileMaker Pro, and MapSource softwares. The study had found that the tradition of stupa carvings on the surfaces of the rocks at the five selected sites continued for around 900 years, from the 1st century BCE to 8th century CE. There is a variation within the chronological settings of each of selected sites, possibly impacted by their utilization within particular landscapes, such as political (for example, change in political administrations or warfare) landscapes and geographical (for example, shifting of routes). The longer existence of the stupa carvings' tradition at these specific locations also indicates their central position on the trade and communication routes, and these were possibly also linked with religious ideologies within their particular times. The analyses of the different architectural elements of stupa carvings in the study area show that this tradition had structural similarities and differences in temporal and spatial contexts.

Keywords: rock carvings, stupa, stupa carvings, Buddhism, Pak-German archaeological mission

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Authors: Luksanaporn Krungkraipetch

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Pterygium is a frequent ocular surface lesion that begins in the limbal conjunctiva within the palpebral fissure and spreads to the cornea. The lesion is more common in the nasal limbus than in the temporal, and it has a wing-like aspect. Indications for surgery, in decreasing order of significance, are growth over the corneal center, decreased vision due to corneal deformation, documented growth, sensations of discomfort, and esthetic concerns. The aim of this study is twofold: first, to determine the frequency of pterygium recurrence after surgery at the mentioned hospital, and second, to identify the factors that influence the recurrence of pterygium. The research design is a retrospective examination of 164 patient samples in an eastern Thai university hospital (Code 13766). Data analysis is descriptive statistics analysis, i.e., basic data details about pterygium surgery and the risk of recurrent pterygium, and for factor analysis, the inferential statistics chi-square and ANOVA are utilized. Twenty-four of the 164 patients who underwent surgery exhibited recurrent pterygium. Consequently, the incidence of recurrent pterygium after surgery was 14.6%. There were an equal number of men and women present. The participants' ages ranged from 41 to 60 years (62, 8 percent). According to the findings, the majority of patients were female (60.4%), over the age of 60 (51.2%), did not live near the beach (83.5%), did not have an underlying disease (92.1%), and 95.7% did not have any other eye problems. Gender (X² = 1.26, p = .289), age (X² = 5.86, p = .119), an address near the sea (X² = 3.30, p = .081)), underlying disease (X² = 0.54, p = .694), and eye disease (X² = 0.00, p = 1.00) had no effect on pterygium recurrence. Recurrences occurred in 79.1% of all surgical procedures and 11.6% of all patients using the bare sclera technique. The recurrence rate for conjunctival autografts was 20.9% for all procedures and 3.0% for all participants. Mitomycin-C and amniotic membrane transplant techniques had no recurrence following surgery. Comparing the surgeries done on people with recurrent pterygium did not show anything important (F = 1.13, p = 0.339). In conclusion, the prevalence of pterygium recurrence following pterygium, 14.6%, does not differ from earlier research. Underlying disease, other eye conditions, and surgical procedures such as pterygium recurrence are unaffected by pterygium surgery.

Keywords: pterygium, recurrence pterygium, pterygium surgery, excision pterygium

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Authors: Zongyao Sha

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Green vegetation plays a vital role in energy flows and matter cycles in terrestrial ecosystems, and vegetation phenology may not only be influenced by but also impose active feedback on climate changes. The phenological events of vegetation, such as the start of the season (SOS), end of the season (EOS), and length of the season (LOS), can respond to climate changes and affect gross primary productivity (GPP). Here we coupled satellite remote sensing imagery with FLUXNET observations to systematically map the shift of SOS, EOS, and LOS in global vegetated areas and explored their response to climate fluctuations and feedback on GPP during the last two decades. Results indicated that SOS advanced significantly, at an average rate of 0.19 days/year at a global scale, particularly in the northern hemisphere above the middle latitude (≥30°N) and that EOS was slightly delayed during the past two decades, resulting in prolonged LOS in 72.5% of the vegetated area. The climate factors, including seasonal temperature and precipitation, are attributed to the shifts in vegetation phenology but with a high spatial and temporal difference. The study revealed interactions between vegetation phenology and climate changes. Both temperature and precipitation affect vegetation phenology. Higher temperature as a direct consequence of global warming advanced vegetation green-up date. On the other hand, 75.9% and 20.2% of the vegetated area showed a positive correlation and significant positive correlation between annual GPP and length of vegetation growing season (LOS), likely indicating an enhancing effect on vegetation productivity and thus increased carbon uptake from the shifted vegetation phenology. Our study highlights a comprehensive view of the vegetation phenology changes of the global terrestrial ecosystems during the last two decades. The interactions between the shifted vegetation phenology and climate changes may provide useful information for better understanding the future trajectory of global climate changes. The feedback on GPP from the shifted vegetation phenology may serve as an adaptation mechanism for terrestrial ecosystems to mitigate global warming through improved carbon uptake from the atmosphere.

Keywords: vegetation phenology, growing season, NPP, correlation analysis

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Authors: Yang Shen, Yongpan Cheng, Jinliang Xu

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The effective blade cooling is of great significance for improving the performance of turbine. The mist cooling emerges as the promising way compared with the transitional single-phase cooling. In the mist cooling, the injected droplet will evaporate rapidly, and cool down the blade surface due to the absorbed latent heat, hence the lifetime for evaporating droplet becomes critical for design of cooling passages for the blade. So far there have been extensive studies on the droplet evaporation, but usually the isothermal model is applied for most of the studies. Actually the surface cooling effect can affect the droplet evaporation greatly, it can prolong the droplet evaporation lifetime significantly. In our study, a new theoretical model for sessile droplet evaporation with surface cooling effect is built up in toroidal coordinate. Three evaporation modes are analyzed during the evaporation lifetime, include “Constant Contact Radius”(CCR) mode、“Constant Contact Angle”(CCA) mode and “stick-slip”(SS) mode. The dimensionless number E0 is introduced to indicate the strength of the evaporative cooling, it is defined based on the thermal properties of the liquid and the atmosphere. Our model can predict accurately the lifetime of evaporation by validating with available experimental data. Then the temporal variation of droplet volume, contact angle and contact radius are presented under CCR, CCA and SS mode, the following conclusions are obtained. 1) The larger the dimensionless number E0, the longer the lifetime of three evaporation cases is; 2) The droplet volume over time still follows “2/3 power law” in the CCA mode, as in the isothermal model without the cooling effect; 3) In the “SS” mode, the large transition contact angle can reduce the evaporation time in CCR mode, and increase the time in CCA mode, the overall lifetime will be increased; 4) The correction factor for predicting instantaneous volume of the droplet is derived to predict the droplet life time accurately. These findings may be of great significance to explore the dynamics and heat transfer of sessile droplet evaporation.

Keywords: blade cooling, droplet evaporation, lifetime, theoretical analysis

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Authors: Pius Borona, Cheikh Mbow, Issa Ouedraogo

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In the Sahel, climate variability has been associated with a complex web of direct and indirect impacts. This natural phenomenon has been an impediment to agro-pastoral communities who experience uncertainty while involving in farming activities which is also their key source of livelihood. In this scenario, the role of climate variability in influencing the performance, quantity and quality of staple cereals yields, vital for food and nutrition security has been a topic of importance. This response of crops and subsequent yield variability is also a subject of immense debate due to the complexity of crop development at different stages. This complexity is further compounded by influence of slowly changing non-climatic factors. With these challenges in mind, the present paper initially explores the occurrence of climate variability at an inter annual and inter decadal level in South Burkina Faso. This is evidenced by variation of the total annual rainfall and the number of rainy days among other climatic descriptors. Further, it is shown how district-scale cereal yields in the study area including maize, sorghum and millet casually associate variably to the inter-annual variation of selected climate variables. Statistical models show that the three cereals widely depict sensitivity to the length of the growing period and total dry days in the growing season. Maize yields on the other hand relate strongly to the rainfall amount variation (R2=51.8%) showing high moisture dependence during critical growth stages. Our conclusions emphasize on adoption of efficient water utilization platforms especially those that have evidently increased yields and strengthening of forecasts dissemination.

Keywords: climate variability, cereal yields, seasonality, rain fed farming, Burkina Faso, rainfall

Procedia PDF Downloads 179

Authors: Leilani Forby, Farid Pazhoohi, Alan Kingstone

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There is abundant research on the nature and content of mind wandering (MW) in neurotypical (NT) adults, however, there is little to no research in these areas on autistic individuals. The objective of the current study was to uncover any differences between low and high autistic trait individuals in their MW. In particular, we examined their attitudes toward, and the themes and temporal dimensions (past, present, future) of, their MW episodes. For our online study, we recruited 518 students (394 women and 124 men), between the ages of 18 and 51 years (M = 20.93, SD = 3.40) from the undergraduate Human Subject Pool at the University of British Columbia. Participants completed the Short Imaginal Processes Inventory (SIPI), which includes the three subscales Positive-Constructive Daydreaming (SIPI-PC), Guilt and Fear of Failure Daydreaming (SIPI-GFF), and Poor Attentional Control (SIPI-PAC). Participants also completed the Past (IPI-past) and Present (IPI-present) subscales of the Imaginal Processes Inventory (IPI), the Deliberate (MW-D) and Spontaneous (MW-S) Mind Wandering scales, the Short Form Perceived Stress Scale (PSS-4), and the 10-item Autism Quotient (AQ-10). Results showed that overall, participant AQ-10 scores were significantly correlated with MW-S, SIPI-GFF, and PSS-4 scores, such that as the number of autistic traits endorsed by participants increased, so did their reports of spontaneous mind wandering, guilt and fear of failure themed day dreaming, and stress levels. This same pattern held for female participants, however, AQ-10 scores were positively correlated with only PSS-4 scores for males. These results suggest that compared to males with autistic traits, MW in females with autistic traits is more similar to individuals with low autistic traits in terms of content and intentionality. Results are discussed in terms of clinical implications, their limitations, and suggested directions for future research.

Keywords: autism, deliberate, mind wandering, spontaneous, perceived stress

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Authors: Sneha Kumari, Ravi Krishnan Elangovan

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This abstract describes the development of a high-speed tracking method by modification in motor components for nanoparticle attachment. Myosin motors are nano-sized protein machines powering movement that defines life. These miniature molecular devices serve as engines utilizing chemical energy stored in ATP to produce useful mechanical energy in the form of a few nanometre displacement events leading to force generation that is required for cargo transport, cell division, cell locomotion, translated to macroscopic movements like running etc. With the advent of in vitro motility assay (IVMA), detailed functional studies of the actomyosin system could be performed. The major challenge with the currently available IVMA for tracking actin filaments is a resolution limitation of ± 50nm. To overcome this, we are trying to develop Single Molecule IVMA in which nanoparticle (GNP/QD) will be attached along or on the barbed end of actin filaments using CapZ protein and visualization by a compact TIRF module called ‘cTIRF’. The waveguide-based illumination by cTIRF offers a unique separation of excitation and collection optics, enabling imaging by scattering without emission filters. So, this technology is well equipped to perform tracking with high precision in temporal resolution of 2ms with significantly improved SNR by 100-fold as compared to conventional TIRF. Also, the nanoparticles (QD/GNP) attached to actin filament act as a point source of light coffering ease in filament tracking compared to conventional manual tracking. Moreover, the attachment of cargo (QD/GNP) to the thin filament paves the way for various nano-technological applications through their transportation to different predetermined locations on the chip

Keywords: actin, cargo, IVMA, myosin motors and single-molecule system

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Authors: Mahfoudha Sid'Elemine

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The refugee resettlement process profoundly shapes the trajectories of individuals in their new host countries, exerting lasting effects on their long-term integration. Prevailing literature underscores the pivotal role of trust in facilitating successful refugee resettlement. However, this research challenges the notion of trust as universally paramount, contending that its significance is contingent upon variables such as the nature of resettlement programs and the diverse backgrounds and perspectives of refugees. Rather than advocating for a blanket approach to trust-building, this research contends that for certain resettlement programs, trust may prove counterproductive amidst resource constraints and tight service timelines. Moreover, trust may not uniformly emerge as a primary requisite for all refugees, presenting formidable challenges in its establishment. Focusing specifically on resettlement in the United States, this study illustrates how the temporal constraints of resettlement services, coupled with refugees' varied cultural experiences, can impede the cultivation of trust between aid workers and refugees. As an alternative paradigm, this research proposes an approach centered on fostering opportunities for reciprocal engagement, positioning refugees as active contributors within their newfound communities. Embracing reciprocity as the cornerstone of burgeoning relationships promises to fortify refugees' ties with the broader community, bolster their autonomy, and facilitate sustained integration over time. The research draws upon qualitative analyses of in-depth interviews conducted with a subset of resettled refugees, as well as aid workers and volunteers involved in refugee resettlement endeavors within Hampton Roads, Virginia, over the past decade. Through this nuanced examination, the study offers insights into the complexities of trust dynamics in refugee resettlement contexts and advocates for a paradigm shift towards reciprocal integration strategies.

Keywords: Resettlement programs, Trust dynamics, Reciprocity, Long-term integration

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Authors: Ana Claudia Muniz Rennó, Karina Nogueira

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This study aimed to investigate the in vivo tissue response of the introduction of the bioactive mesh (BM) scaffolds using a model of tibial bone defect implants in rats. Although a previous in vivo study demonstrated a highly positive response of particulate bioactive materials in the morphological and biomechanical properties of the bone callus, the effects of material with superior bioactivity, present in form of meshes have not been studied yet. Eighty male Wistar rats with 3 mm tibial defects were used. Animals were divided into four groups: intact group (IG) – tibia without any injury; bone defect day zero (0dD) – bone defects, sacrificed immediately after injury; bone defect control group (CG) – bone defects without any filler and bone defect filled with BM scaffold. The animals of BM and CG groups were sacrificed 15, 30 and 45 days post-injury to compare the temporal-special effects of the scaffolds on bone healing. The histological analysis revealed an organized newly formed bone at 30 and 45 days post-surgery in the BM. Also, this group presented an increased COX-2 expression on days 15 and 30 post-surgery. Furthermore, the immunohistochemistry analysis revealed that, BM presented a positive immunoexpression of RUNX-2 during all periods evaluated. The biomechanical analysis revealed that at 15 day after surgery, no significant statistically difference was observed between BM and CG and both groups had significantly higher values of maximal load compared to 0dG and significantly lower values than IG. On days 30 and 45 post-surgery, BM presented statistically lower values of maximal load compared to the CG. Nevertheless, at the same periods, BM did not show statistically significant difference compared to the IG maximal load values (p > 0, 05). Our results revealed that the implantation of the BM scaffolds was effective in stimulating newly bone formation.

Keywords: bone, biomaterials, scaffolds, cartilage

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Authors: David Whitehouse

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Some of the strengths of online teaching include flexibility, creativity, and comprehensiveness. A challenge can be motivation. How can an instructor repeating the same lessons over and over, day in and day out, year after year, maintain motivation? Enthusiasm? Does motivating the student and creating enthusiasm in class build the same things inside the instructor? The answers lie in the adoption of what I label EUQ—The Empathy and Understanding Quotient. In the online environment, students who are adults have many demands on their time: civilian careers, families (spouse, children, older parents), and sometimes even military service. Empathetic responses on the part of the instructor will lead to open and honest communication on the part of the student, which will lead to understanding on the part of the instructor and a rise in motivation in both parties. Understanding the demands can inform an instructor’s relationship with the student throughout the temporal parameters of classwork. In practicing EUQ, instructors can build motivation in their students and find internal motivation in an enhanced classroom dynamic. The presentation will look at what motivates a student to accomplish more than the minimum required and how that can lead to excellent results for an instructor’s own motivation. Through direct experience of having students give high marks on post-class surveys and via direct messaging, the presentation will focus on how applying EUQ in granting extra time, searching for intent while grading, communicating with students via Quick Notes, responses in Forums, comments in Assignments, and comments in grading areas - - - how applying these things infuses enthusiasm and energy in the instructor which drive creativity in teaching. Three primary ways of communicating with students will be given as examples. The positive response and negative response each for a Forum, an Assignment, and a Message will be explored. If there is time, participants will be invited to craft their own EUQ responses in a role playing exercise involving two common classroom scenarios—late work and plagiarism.

Keywords: education, instruction, motivation, online, teaching

Procedia PDF Downloads 153

Authors: Norbert Simon, Rodeano Roslee, Abdul Ghani Rafek, Goh Thian Lai, Azimah Hussein, Lee Khai Ern

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The 54 km stretch of Ranau-Tambunan (RTM) road in Sabah is subjected to slope failures almost every year. This study is focusing on identifying section of roads that are susceptible to failure based on temporal landslide density and lineament density analyses. In addition to the analyses, the rock slopes in several sections of the road were assessed using the geological strength index (GSI) technique. The analysis involved 148 landslides that were obtained in 1978, 1994, 2009 and 2011. The landslides were digitized as points and the point density was calculated based on every 1km2 of the road. The lineaments of the area was interpreted from Landsat 7 15m panchromatic band. The lineament density was later calculated based on every 1km2 of the area using similar technique with the slope failure density calculation. The landslide and lineament densities were classified into three different classes that indicate the level of susceptibility (low, moderate, high). Subsequently, the two density maps were overlap to produce the final susceptibility map. The combination of both high susceptibility classes from these maps signifies the high potential of slope failure in those locations in the future. The final susceptibility map indicates that there are 22 sections of the road that are highly susceptible. Seven rock slopes were assessed along the RTM road using the GSI technique. It was found from the assessment that rock slopes along this road are highly fractured, weathered and can be classified into fair to poor categories. The poor condition of the rock slope can be attributed to the high lineament density that presence in the study area. Six of the rock slopes are located in the high susceptibility zones. A detailed investigation on the 22 high susceptibility sections of the RTM road should be conducted due to their higher susceptibility to failure, in order to prevent untoward incident to road users in the future.

Keywords: GSI, landslide, landslide density, landslide susceptibility, lineament density

Procedia PDF Downloads 373

Authors: Sumaira Zafar, Arjumand Zaidi, Muhammad Arslan Hafeez

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Indus Basin Irrigation System (IBIS) is the largest contiguous irrigation system of the world comprising Indus River and its tributaries, canals, distributaries, and watercourses. A big challenge faced by IBIS is transmission losses through seepage and leaks that account to 41 percent of the total water derived from the river and about 40 percent of that is through watercourses. Irrigation system rehabilitation programs in Pakistan are focused on improvement of canal system at the watercourse level (tertiary channels). Under these irrigation system management programs more than 22,800 watercourses have been improved or lined out of 43,000 (12,900 Kilometers) watercourses. The evaluation of the improvement work is required at this stage to testify the success of the programs. In this paper, emerging technologies of GIS and satellite remote sensing are used for impact assessment of watercourse rehabilitation work in Sindh. To evaluate the efficiency of the improved watercourses, few parameters are selected like soil moisture along watercourses, availability of water at tail end and changes in cultivable command areas. Improved watercourses details and maps are acquired from National Program for Improvement of Watercourses (NPIW) and Space and Upper Atmospheric Research Commission (SUPARCO). High resolution satellite images of Google Earth for the year of 2004 to 2013 are used for digitizing command areas. Temporal maps of cultivable command areas show a noticeable increase in the cultivable land served by improved watercourses. Field visits are conducted to validate the results. Interviews with farmers and landowners also reveal their overall satisfaction in terms of availability of water at the tail end and increased crop production.

Keywords: geospatial, impact assessment, watercourses, GIS, remote sensing, seepage, canal lining

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Authors: Avinash Nayak, Debopam Das

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The current work implements the variational principle to find the optimum initial perturbation that provides maximum growth in an impulsively blocked channel flow. The conventional method for studying temporal stability has always been through modal analysis. In most of the transient flows, this modal analysis is still followed with the quasi-steady assumption, i.e. change in base flow is much slower compared to perturbation growth rate. There are other studies where transient analysis on time dependent flows is done by formulating the growth of perturbation as an initial value problem. But the perturbation growth is sensitive to the initial condition. This study intends to find the initial perturbation that provides the maximum growth at a later time. Here, the expression of base flow for blocked channel is derived and the formulation is based on the two dimensional perturbation with stream function representing the perturbation quantity. Hence, the governing equation becomes the Orr-Sommerfeld equation. In the current context, the cost functional is defined as the ratio of disturbance energy at a terminal time 'T' to the initial energy, i.e. G(T) = ||q(T)||2/||q(0)||2 where q is the perturbation and ||.|| defines the norm chosen. The above cost functional needs to be maximized against the initial perturbation distribution. It is achieved with the constraint that perturbation follows the basic governing equation, i.e. Orr-Sommerfeld equation. The corresponding adjoint equation is derived and is solved along with the basic governing equation in an iterative manner to provide the initial spatial shape of the perturbation that provides the maximum growth G (T). The growth rate is plotted against time showing the development of perturbation which achieves an asymptotic shape. The effects of various parameters, e.g. Reynolds number, are studied in the process. Thus, the study emphasizes on the usage of optimal perturbation and its growth to understand the stability characteristics of time dependent flows. The assumption of quasi-steady analysis can be verified against these results for the transient flows like impulsive blocked channel flow.

Keywords: blocked channel flow, calculus of variation, hydrodynamic stability, optimal perturbation

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