Search results for: plant detection

Authors: Pradeep Kumar, Shalinee Shukla

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Pavement plays a vital role in the socio-economic development of a country. Bituminous roads construction with conventional paving grade bitumen obtained from hot mix plant creates pollution and involves emission of greenhouse gases, also the construction of pavements at very high temperature is not feasible or desirable for high rainfall and snowfall areas. This problem of overheating can be eliminated by the construction of pavements with the usage of emulsified cold mixes which will eliminate emissions and help in the reduction of fuel requirement at mixing plant, which leads to energy conservation. Cold mix is a mixture of unheated aggregate and emulsion or cutback and filler. The primary objective of this research is to assess the volumetric mix design parameters of recycled aggregates with cold mixing technology and also to assess the impact of additives on volumetric mix characteristics. In this present study, bituminous pavement materials are reclaimed using cold mix technology, and Marshall specimens are prepared with the help of slow setting type 2 (SS-2) cationic bitumen emulsion as a binder for recycled aggregates. This technique of road construction is more environmentally friendly and can be done in adverse weather conditions.

Keywords: cold mixes, bitumen emulsion, recycled aggregates, volumetric properties

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Authors: Mansouri Ouarda, Abdennour Cherif, Saidi Malika

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Since the industrial revolution, many anthropogenic activities have caused environmental, considerable and overall changes. The lead represents a very dangerous disruptive for the functioning of the body. In this context the current study aims at evaluating a natural therapy by the use of the plant grass in wheat (Triticum durum) against the toxicity of lead in rat wistar male. The rats were divided into three groups: the control group, the group treated with 600 mg /kg food of lead only (Pb) is the group treated with the combination of 600 mg/kg of food and 9g/rat /day of the plant grass in wheat (Pb-bl). The duration of the treatment is 6 weeks. The results of the biometrics of the organs (thyroid, kidney, testis and epididymis) show no significant difference between the three groups. The dosage of a few parameters and hormonal biochemical shows a decrease in the concentration of the hormone T3 and TSH levels among the group pb alone compared to the control and Pb-Bl. These results have been confirmed by the study of histological slices. A morphological changes represented by a shrinking volume of vesicles with the group treated with Pb alone. A return to the normal state of the structure of the follicles was observed. The concentration in serum testosterone, urea and creatinine was significantly increased among the group treated by Pb only in relation to the control and Pb-Bl. whereas the rate of glucose did not show any significant difference. The histology study of the kidney, testis and epididymal weights show no modification at the group Pb-bl comparing to the control. The parenchyma of the kidney shows a dilation of tubes distal and proximal causing a tubular nephropathy for the batch processed by Pb only. The testicles have marked a destruction or absence of germ cells and the light of some seminiferous are almost empty. Conclusion: The supplementation of the plant Triticum durum has caused a considerable improvement which ensures the return of parameters investigated in the normal state.

Keywords: creatinine, glucose, histological sections, T3, TSH, testosterone

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Authors: Raoudha Abdellaoui, Faycal Boughalleb, Zohra Chebil

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In arid and semi-arid regions, salinity represents a major constraint towards plants’ growth. Stipa lagascae, a psammophile grass, is a promised species since its economic and ecological interests. Our study aims to explore the effects of different salt concentrations (0; 100; 200; 300 and 400 mM) on physiological, biochemical and anatomic parameters. Salt stress was applied on S. lagascae plants cultivated under controlled conditions. Results show that salinity reduces biomass production especially when plants are subjected to severe stress (>200 mM NaCl). Concerning the nutritional level, the fact of enriching soil with NaCl, leads to an accumulation of Na+ against other nutritional elements (K+, Ca2+). To maintain tissues hydration, S. lagascae established osmotic adaptation by accumulation of proline and soluble sugars. Salt stress affected significantly root and foliar anatomy. Indeed, plants increased their vessels’ diameter and mesophyll surface. S. lagascae plants reduced also the surface of the belluforme cells to defeat dehydration. According to our results, S. lagascae seems to be a tolerant plant at acceptable concentrations that do not exceed 6g/l.

Keywords: anatomical adaptations, mineral nutrition, plant growth, salt stress, stipa lagascae

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Authors: Gopi Kandaswamy, P. Balamuralidhar

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Fully autonomous small Unmanned Aerial Vehicles (UAVs) are increasingly being used in many commercial applications. Although a lot of research has been done to develop safe, reliable and durable UAVs, accidents due to electronic and structural failures are not uncommon and pose a huge safety risk to the UAV operators and the public. Hence there is a strong need for an automated health monitoring system for UAVs with a view to minimizing mission failures thereby increasing safety. This paper describes our approach to monitoring the electronic and structural components in a small UAV without the need for additional sensors to do the monitoring. Our system monitors data from four sources; sensors, navigation algorithms, control inputs from the operator and flight controller outputs. It then does statistical analysis on the data and applies a rule based engine to detect failures. This information can then be fed back into the UAV and a decision to continue or abort the mission can be taken automatically by the UAV and independent of the operator. Our system has been verified using data obtained from real flights over the past year from UAVs of various sizes that have been designed and deployed by us for various applications.

Keywords: fault detection, health monitoring, unmanned aerial vehicles, vibration analysis

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Xiaoqian Zhang, Ping Zou, Pengcheng Li

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Salt stress is one of the most serious abiotic stresses, and it can lead to the reduction of agricultural productivity. High salt concentration makes it more difficult for roots to absorb water and disturbs the homeostasis of cellular ions resulting in osmotic stress, ion toxicity and generation of reactive oxygen species (ROS). Compared with the normal physiological conditions, salt stress could inhibit the photosynthesis, break metabolic balance and damage cellular structures, and ultimately results in the reduction of crop yield. Therefore it is vital to develop practical methods for improving the salt tolerance of plants. Chitooligomers (COS) is partially depolymerized products of chitosan, which is consisted of D-glucosamine and N-acetyl-D-glucosamine. In agriculture, COS has the ability to promote plant growth and induce plant innate immunity. The bioactivity of COS closely related to its degree of polymerization (DP) and acetylation (DA). However, most of the previous reports fail to mention the function of COS with different DP and DAs in improving the capacity of plants against salt stress. Accordingly, in this study, chitooligomers (COS) with different degrees of DAs were used to test wheat seedlings response to salt stress. In addition, the determined degrees of polymerization (DPs) COS(DP 4-12) and a heterogeneous COS mixture were applied to explore the relationship between the DP of COSs and its effect on the growth of wheat seedlings in response to salt stress. It showed that COSs, the exogenous elicitor, could promote the growth of wheat seedling, reduce the malondialdehyde (MDA) concentration, and increase the activities of antioxidant enzymes. The results of mRNA expression level test for salt stress-responsive genes indicated that COS keep plants away from being hurt by the salt stress via the regulation of the concentration and the increased antioxidant enzymes activities. Moreover, it was found that the activities of COS was closely related to its Das and COS (DA: 50%) displayed the best salt resistance activity to wheat seedlings. The results also showed that COS with different DP could promote the growth of wheat seedlings under salt stress. COS with a DP (6-8) showed better activities than the other tested samples, implied its activity had a close relationship with its DP. After treatment with chitohexaose, chitoheptaose, and chitooctaose, the photosynthetic parameters were improved obviously. The soluble sugar and proline contents were improved by 26.7%-53.3% and 43.6.0%-70.2%, respectively, while the concentration of malondialdehyde (MDA) was reduced by 36.8% - 49.6%. In addition, the antioxidant enzymes activities were clearly activated. At the molecular level, the results revealed that they could obviously induce the expression of Na+/H+ antiporter genes. In general, these results were fundamental to the study of action mechanism of COS on promoting plant growth under salt stress and the preparation of plant growth regulator.

Keywords: chitooligomers (COS), degree of polymerization (DP), degree of acetylation (DA), salt stress

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Authors: Patel Kailash P, Patel Parimal M

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The effect of coal fly ash treatment on the chromosomes of Raphanus sativus L. was investigated. The seeds of Raphanus sativusL. were placed in petri dishes in three replicates and allowed to germinate for five days in different concentration of coal fly ash solution. The root was treated with the diluted, semidiluted, and concentrated solution of fly ash while the control group had distilled water.The total aberration were examined. The mitotic index was calculated and the results were statically evaluated by the analysis of variance 5% significant level. The mitotic index decreased as the concentration increased. The highest mitotic index value was diluted fly ash solution while the least was concentrated fly ash treatment. The results show the most frequent chromosomal abnormalities observed included: chromatid bridge, c-mitosis, and stickiness. Concentrated fly ash solution is much more genotoxic than semidiluted fly ash solution, as it induced more aberrations having percentage abnormalities for the highest concentration tested. Increased fly ash pollution can lead to some irreversible cytogenetic effect in plants. The study is an attempt to corroborate the toxic effect of coal fly ash of thermal power plant on the chromosome of plants. These results will be useful in environmental monitoring of the cytotoxicity of coal fly ash.

Keywords: coal fly-ash, genotoxic, cytogenetic, mitotic index, Raphanus sativus L.

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Authors: Alaa El-Din Rezk

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In Egypt, management of crops still away from what is being used today by utilizing the advances of mechanical design capabilities, sensing and electronics technology. These technologies have been introduced in many places and recorm, for Straight Path, Curved Path, Sine Wave ded high accuracy in different field operations. So, an autonomous robotic platform based on machine vision has been developed and constructed to be implemented in Egyptian conditions as self-propelled mobile vehicle for carrying tools for inter/intra-row crop management based on different control modules. The experiments were carried out at plant protection research institute (PPRI) during 2014-2015 to optimize the accuracy of agricultural robotic platform control using machine vision in term of the autonomous navigation and performance of the robot’s guidance system. Results showed that the robotic platform' guidance system with machine vision was able to adequately distinguish the path and resisted image noise and did better than human operators for getting less lateral offset error. The average error of autonomous was 2.75, 19.33, 21.22, 34.18, and 16.69 mm. while the human operator was 32.70, 4.85, 7.85, 38.35 and 14.75 mm Path, Offset Discontinuity and Angle Discontinuity respectively.

Keywords: autonomous robotic, Hough transform, image processing, machine vision

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Authors: Beata J. Lehka, Samuel A. Bradley, Frederik G. Hansson, Khem B. Adhikari, Daniela Rago, Paulina Rubaszka, Ahmad K. Haidar, Ling Chen, Lea G. Hansen, Olga Gudich, Konstantina Giannakou, Yoko Nakamura, Thomas Dugé de Bernonville, Konstantinos Koudounas, Sarah E. O’Connor, Vincent Courdavault, Jay D. Keasling, Jie Zhang, Michael K. Jensen

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Monoterpenoid indole alkaloids (MIAs) represent a large class of natural plant products with marketed pharmaceutical activities against a wide range of applications, including cancer and mental disorders. Halogenated MIAs have shown improved pharmaceutical properties; however, characterisation and synthesis of new-to-nature halogenated MIAs remain a challenge in slow-growing plants with limited genetic tractability. Here, we demonstrate a platform for de novo biosynthesis of two bioactive MIAs, serpentine and alstonine, in baker’s yeast Saccharomyces cerevisiae, reaching titers of 8.85 mg/L and 4.48 mg/L, respectively, when cultivated in fed-batch micro bioreactors. Using this MIA biosynthesis platform, we undertake a systematic exploration of the derivative space surrounding these compounds and produce halogenated MIAs. The aim of the current study is to develop a fermentation process for halogenated MIAs.

Keywords: monoterpenoid indole alkaloids, Saccharomyces cerevisiae, halogenated derivatives, fermentation

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Authors: Mohsen Rabbani, Trista McLaughlin, Ehsan Vahidi

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the remediation of polluted sites with heavy metals, such as rare earth elements (REEs), has been a primary concern of researchers to decontaminate the soil. Among all developed methods to address this concern, phytoremediation has been established as efficient, cost-effective, easy-to-use, and environmentally friendly way, providing a long-term solution for addressing this global concern. Furthermore, this technology has another great potential application in the metals production sector through returning metals buried in soil via metals cropping. Considering the significant metal concentration in hyper-accumulators, the utilization of bioaccumulated metals to extract metals from plant matter has been proposed as a sub-economic area called phytomining. As a recent, more advanced technology to eliminate such pollutants from the soil and produce critical metals, bioharvesting (phytomining/agromining) has been considered another compromising way to produce metals and meet the global demand for critical/target metals. The bio-ore obtained from phytomining can be safely disposed of or introduced to metal production pathways to obtain the most demanded metals, such as REEs. It is well-known that some hyperaccumulators, e.g., fern Dicranopteris linearis, can be used to absorb REE metals from the polluted soils and accumulate them in plant organs, such as leaves and stems. After soil remediation, the plant species can be harvested and introduced to the downstream steps, namely crushing/grinding, leaching, and purification processes, to extract REEs from plant matter. This novel interdisciplinary field can fill the gap between agriculture, mining, metallurgy, and the environment. Despite the advantages of agromining for the REEs production industry, key issues related to the environmental sustainability of the entire life cycle of this new concept have not been assessed yet. Hence, a comparative life cycle assessment (LCA) study was conducted to quantify the environmental footprints of REEs phytomining. The current LCA study aims to estimate and calculate environmental effects associated with phytomining by considering critical factors, such as climate change, land use, and ozone depletion. The results revealed that phytomining is an easy-to-use and environmentally sustainable approach to either eliminate REEs from polluted sites or produce REEs, offering a new source of such metals production. This LCA research provides guidelines for researchers active in developing a reliable relationship between agriculture, mining, metallurgy, and the environment to encounter soil pollution and keep the earth green and clean.

Keywords: phytoremediation, phytomining, life cycle assessment, environmental impacts, rare earth elements, hyperaccumulator

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

Procedia PDF Downloads 57

Authors: Marta Skwarecka, Patrycja Bloch, Rafal Walkusz, Oliwia Urbanowicz, Grzegorz Zielinski, Sabina Zoledowska, Dawid Nidzworski

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Upper respiratory tract infections are one of the most common reasons for visiting a general doctor. Streptococci are the most common bacterial etiological factors in these infections. There are many different types of Streptococci and infections vary in severity from mild throat infections to pneumonia. For example, S. pyogenes mainly contributes to acute pharyngitis, palatine tonsils and scarlet fever, whereas S. Streptococcus pneumoniae is responsible for several invasive diseases like sepsis, meningitis or pneumonia with high mortality and dangerous complications. There are only a few diagnostic tests designed for detection Streptococci from the infected throat of patients. However, they are mostly based on lateral flow techniques, and they are not used as a standard due to their low sensitivity. The diagnostic standard is to culture patients throat swab on semi selective media in order to multiply pure etiological agent of infection and subsequently to perform antibiogram, which takes several days from the patients visit in the clinic. Therefore, the aim of our studies is to develop and implement to the market a Point of Care device for the rapid identification of Streptococcus pyogenes and Streptococcus pneumoniae with simultaneous identification of antibiotic resistance genes. In the course of our research, we successfully selected genes for to-species identification of Streptococci and genes encoding antibiotic resistance proteins. We have developed a reaction to amplify these genes, which allows detecting the presence of S. pyogenes or S. pneumoniae followed by testing their resistance to erythromycin, chloramphenicol and tetracycline. What is more, the detection of β-lactamase-encoding genes that could protect Streptococci against antibiotics from the ampicillin group, which are widely used in the treatment of this type of infection is also developed. The test is carried out directly from the patients' swab, and the results are available after 20 to 30 minutes after sample subjection, which could be performed during the medical visit.

Keywords: antibiotic resistance, Streptococci, respiratory infections, diagnostic test

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Authors: Varsha Gupta, Priya Datta, Gursimran Mohi, Jagdish Chander

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Fluoroquinolones form the mainstay of therapy for the treatment of infections due to Salmonella enterica subsp. enterica. There is a complex interplay between several resistance mechanisms for quinolones and various fluoroquinolones discs, giving varying results, making detection and interpretation of fluoroquinolone resistance difficult. For detection of fluoroquinolone resistance in Salmonella ssp., we compared the use of pefloxacin and nalidixic acid discs as surrogate marker. Using MIC for ciprofloxacin as the gold standard, 43.5% of strains showed MIC as ≥1 μg/ml and were thus resistant to fluoroquinoloes. Based on the performance of nalidixic acid and pefloxacin discs as surrogate marker for ciprofloxacin resistance, both the discs could correctly detect all the resistant phenotypes; however, use of nalidixic acid disc showed false resistance in the majority of the sensitive phenotypes. We have also tested newer antimicrobial agents like cefixime, imipenem, tigecycline and azithromycin against Salmonella spp. Moreover, there was a comeback of susceptibility to older antimicrobials like ampicillin, chloramphenicol, and cotrimoxazole. We can also use cefixime, imipenem, tigecycline and azithromycin in the treatment of multidrug resistant S. typhi due to their high susceptibility.

Keywords: salmonella, pefloxacin, surrogate marker, chloramphenicol

Procedia PDF Downloads 979

Authors: Monique Du Plessis, Anina Coetzee, Colleen L. Seymour, Claire N. Spottiswoode

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Artificial nectar feeders are used to attract nectarivorous birds to gardens and are increasing in popularity. The costs and benefits of these feeders remain controversial, however. Nectar feeders may have positive effects by attracting nectarivorous birds towards suburbia, facilitating their urban adaptation, and supplementing bird diets when floral resources are scarce. However, this may come at the cost of luring them away from the plants they pollinate in neighboring indigenous vegetation. This study investigated the effect of nectar feeders on an African pollinator-plant mutualism. Given that birds are important pollinators to many fynbos plant species, this study was conducted in gardens and natural vegetation along the urban edge of the Cape Peninsula. Feeding experiments were carried out to compare relative bird abundance and local distribution patterns for nectarivorous birds (i.e., sunbirds and sugarbirds) between feeder and control treatments. Resultant changes in their visitation rates to Erica flowers in the natural vegetation were tested by inspection of their anther ring status. Nectar feeders attracted higher densities of nectarivores to gardens relative to natural vegetation and decreased their densities in the neighboring fynbos, even when floral abundance in the neighboring vegetation was high. The consequent changes to their distribution patterns and foraging behavior decreased their visitation to at least Erica plukenetii flowers (but not to Erica abietina). This study provides evidence that nectar feeders may have positive effects for birds themselves by reducing their urban sensitivity but also highlights the unintended negative effects feeders may have on the surrounding fynbos ecosystem. Given that nectar feeders appear to compete with the flowers of Erica plukenetii, and perhaps those of other Erica species, artificial feeding may inadvertently threaten bird-plant pollination networks.

Keywords: avian nectarivores, bird feeders, bird pollination, indirect effects in human-wildlife interactions, sugar water feeders, supplementary feeding

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Authors: Aiswarya C. L, Swatantra Pratap Singh

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In recent years, most desalination plants have been powered by fossil fuels, and to a lesser extent, by green energy. Greenhouse gases emitted by fossil-fuelled plants significantly impact the global climate. So scientists are forced to develop a powerful energy source to protect the environment with greater sustainability due to climate change issues. Nuclear energy can supply much more fresh water than what is currently available. Furthermore, it is more affordable and does not emit any greenhouse gases. This review compares conventional desalination plants with nuclear-powered desalination plants in terms of cost, energy consumption, water recovery, and environmental issues. On the basis of the review conducted, nuclear desalination has been demonstrated to be technically feasible and economically competitive with a variety of fossil fuels, renewable energy sources, and waste heat sources. Nuclear sources have been criticized due to their lack of safety. But studies show, if we were able to handle the issue with care, the problems could be eliminated. Here we're looking at the Seawater Reverse Osmosis Plant (SWROP) at Kudankulam Nuclear Power Plant in Tamil Nadu, India and review the further possibility of implementing nuclear desalination technology in other states of India.

Keywords: energy consumption, environmental impacts, nuclear desalination, water recovery

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data-set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: temporal graph network, anomaly detection, cyber security, IDS

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Syed Beenish Rufai, Sarman Singh

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Background: Performance of Genotype MTBDRsl (Hain Life science GmbH Germany) for detection of mutations associated with second-line drug resistance is well known. However, less evidence regarding the association of mutations and genetic background of strains is known which, in the future, is essential for clinical management of anti-tuberculosis drugs in those settings where the probability of particular genotype is predominant. Material and Methods: During this retrospective study, a total of 259 MDR-TB isolates obtained from pulmonary TB patients were tested for second-line drug susceptibility testing (DST) using Genotype MTBDRsl VER 1.0 and compared with BACTEC MGIT-960 as a reference standard. All isolates were further characterized using spoligotyping. The spoligo patterns obtained were compared and analyzed using SITVIT_WEB. Results: Of total 259 MDR-TB isolates which were screened for second-line DST by Genotype MTBDRsl, mutations were found to be associated with gyrA, rrs and emb genes in 82 (31.6%), 2 (0.8%) and 90 (34.7%) isolates respectively. 16 (6.1%) isolates detected mutations associated with both FQ as well as to AG/CP drugs (XDR-TB). No mutations were detected in 159 (61.4%) isolates for corresponding gyrA and rrs genes. Genotype MTBDRsl showed a concordance of 96.4% for detection of sensitive isolates in comparison with second-line DST by BACTEC MGIT-960 and 94.1%, 93.5%, 60.5% and 50% for detection of XDR-TB, FQ, EMB, and AMK/CAP respectively. D94G was the most prevalent mutation found among (38 (46.4%)) OFXR isolates (37 FQ mono-resistant and 1 XDR-TB) followed by A90V (23 (28.1%)) (17 FQ mono-resistant and 6 XDR-TB). Among AG/CP resistant isolates A1401G was the most frequent mutation observed among (11 (61.1%)) isolates (2 AG/CP mono-resistant isolates and 9 XDR-TB isolates) followed by WT+A1401G (6 (33.3%)) and G1484T (1 (5.5%)) respectively. On spoligotyping analysis, Beijing strain (46%) was found to be the most predominant strain among pre-XDR and XDR TB isolates followed by CAS (30%), X (6%), Unique (5%), EAI and T each of 4%, Manu (3%) and Ural (2%) respectively. Beijing strain was found to be strongly associated with D94G (47.3%) and A90V mutations by (47.3%) and 34.8% followed by CAS strain by (31.6%) and 30.4% respectively. However, among AG/CP resistant isolates, only Beijing strain was found to be strongly associated with A1401G and WT+A1401G mutations by 54.5% and 50% respectively. Conclusion: Beijing strain was found to be strongly associated with the most prevalent mutations among pre-XDR and XDR TB isolates. Acknowledgments: Study was supported with Grant by All India Institute of Medical Sciences, New Delhi reference No. P-2012/12452.

Keywords: tuberculosis, line probe assay, XDR TB, drug susceptibility

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Authors: Manal Kamel, Sara Maher

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Development of sensitive non-invasive tests for detection of SARS-CoV-2 antigens is imperative to manage the extent of infection throughout the population, yet, it is still challenging. Here, we designed and optimized a sandwich enzyme-linked immunosorbent assay (ELISA) for SARS-CoV-2 S1 antigen detection in saliva. Both saliva samples and nasopharyngeal swapswere collected from 170 PCR-confirmed positive and negative cases. Gold nanoparticles (AuNPs) were conjugated with S1protein receptor binding domain (RBD) nanobodies. Recombinant S1 monoclonal antibodies (S1mAb) as primery antibody and gold conjugated nanobodies as secondary antibody were employed in sandwich ELISA. Our developed system were optimized to achieve 87.5 % sensitivity and 100% specificity for saliva samples compared to 89 % and 100% for nasopharyngeal swaps, respectively. This means that saliva could be a suitable replacement for nasopharyngeal swaps No cross reaction was detected with other corona virus antigens. These results revealed that our developed ELISAcould be establishedas a new, reliable, sensitive, and non-invasive test for diagnosis of SARS-CoV-2 infection, using the easily collected saliva samples.

Keywords: COVID 19, diagnosis, ELISA, nanobodies

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Authors: Meksem Amara Leila, Ferfar Meriem, Meksem Nabila, Djebar Mohammed Reda

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The wheat is the cereal the most consumed in the world. In Algeria, the production of this cereal covers only 20 in 25 % of the needs for the country, the rest being imported. To improve the efficiency and the productivity of the durum wheat, the farmers turn to the use of pesticides: weed-killers, fungicides and insecticides. However this use often entrains losses of products more at least important contaminating the environment and all the food chain. Weed-killers are substances developed to control or destroy plants considered unwanted. That they are natural or produced by the human being (molecule of synthesis), the absorption and the metabolization of weed-killers by plants cause the death of these plants.In this work, we set as goal the evaluation of the effect of a weed-killer sulfonylurea, the CossackOD with various concentrations (0, 2, 4 and 9 µg) on variety of Triticum durum: Cirta. We evaluated the plant growth by measuring the leaves and root length, compared with the witness as well as the content of proline and analyze the level of one of the antioxydative enzymes: catalse, after 14 days of treatment. Sulfonylurea is foliar and root weed-killers inhibiting the acetolactate synthase: a vegetable enzyme essential to the development of the plant. This inhibition causes the ruling of the growth then the death. The obtained results show a diminution of the average length of leaves and roots this can be explained by the fact that the ALS inhibitors are more active in the young and increasing regions of the plant, what inhibits the cellular division and talks a limitation of the foliar and root’s growth. We also recorded a highly significant increase in the proline levels and a stimulation of the catalase activity. As a response to increasing the herbicide concentrations a particular increases in antioxidative mechanisms in wheat cultivar Cirta suggest that the high sensitivity of Cirta to this sulfonylurea herbicide is related to the enhanced production and oxidative damage of reactive oxygen species.

Keywords: sulfonylurea, Triticum durum, oxydative stress, Toxicity

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Authors: Shih-Yu Lo

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Stereotypes exist in almost every society, affecting how people interact with each other. However, to our knowledge, the influence of stereotypes was rarely explored in the context of basic perceptual processes. This study aims to explore how the gender stereotype affects object recognition. Participants were presented with a series of scene pictures, followed by a target display with a man or a woman, holding a weapon or a non-weapon object. The task was to identify whether the object in the target display was a weapon or not. Although the gender of the object holder could not predict whether he or she held a weapon, and was irrelevant to the task goal, the participant nevertheless tended to identify the object as a weapon when the object holder was a man than a woman. The analysis based on the signal detection theory showed that the stereotype effect on object recognition mainly resulted from the participant’s bias to make a 'weapon' response when a man was in the scene instead of a woman in the scene. In addition, there was a trend that the participant’s sensitivity to differentiate a weapon from a non-threating object was higher when a woman was in the scene than a man was in the scene. The results of this study suggest that the irrelevant social cues implied in the visual scene can be very powerful that they can modulate the basic object recognition process.

Keywords: gender stereotype, object recognition, signal detection theory, weapon

Procedia PDF Downloads 202

Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: Yohana Fessehazion

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Mercury is a prominent example of a heavy metal contaminant in the environment, and it has been extensively investigated for its potential health risk in humans and other organisms. In South Africa, massive mercury contamination happened in1980s when the England-based mercury reclamation processing plant relocated to Cato Ridge, KwaZulu-Natal Province, and discharged mercury waste into the Mngceweni River. This mercury waste discharge resulted in high mercury concentration that exceeded the acceptable levels in Mngceweni River, Umgeni River, and human hair of the nearby villagers. This environmental issue raised the alarm, and over the years, several environmental assessments were reported the dire environmental crises resulting from the Thor Chemicals (now known as Metallica Chemicals) and urged the immediate removal of the around 3,000 tons of mercury waste stored in the factory storage facility over two decades. Recently theft of some containers with the toxic substance from the Thor Chemicals warehouse and the subsequent fire that ravaged the facility furtherly put the factory on the spot escalating the urgency of left behind deadly mercury waste removal. This project aims to investigate the mercury contamination leaking from an old Thor Chemicals mercury processing plant. The focus will be on sediments, water, terrestrial plants, and aquatic weeds such as the prominent water hyacinth weeds in the nearby water systems of Mngceweni River, Umgeni River, and Inanda Dam as a bio-indicator and phytoremediator for mercury pollution. Samples will be collected in spring around October when the condition is favourable for microbial activity to methylate mercury incorporated in sediments and blooming season for some aquatic weeds, particularly water hyacinth. Samples of soil, sediment, water, terrestrial plant, and aquatic weed will be collected per sample site from the point of source (Thor Chemicals), Mngceweni River, Umgeni River, and the Inanda Dam. One-way analysis of variance (ANOVA) tests will be conducted to determine any significant differences in the Hg concentration among all sampling sites, followed by Least Significant Difference post hoc test to determine if mercury contamination varies with the gradient distance from the source point of pollution. The flow injection atomic spectrometry (FIAS) analysis will also be used to compare the mercury sequestration between the different plant tissues (roots and stems). The principal component analysis is also envisaged for use to determine the relationship between the source of mercury pollution and any of the sampling points (Umgeni and Mngceweni Rivers and the Inanda Dam). All the Hg values will be expressed in µg/L or µg/g in order to compare the result with the previous studies and regulatory standards. Sediments are expected to have relatively higher levels of Hg compared to the soils, and aquatic macrophytes, water hyacinth weeds are expected to accumulate a higher concentration of mercury than terrestrial plants and crops.

Keywords: mercury, phytoremediation, Thor chemicals, water hyacinth

Procedia PDF Downloads 213

Authors: Marcel Chevalier, Léo Dupont, Sylvain Marié, Frédérique Roffet, Elena Stolyarova, William Templier, Costin Vasile

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Industrial end-users are currently facing an increasing need to reduce the risk of unexpected failures and optimize their maintenance. This calls for both short-term analysis and long-term ageing anticipation. At Schneider Electric, we tackle those two issues using both machine learning and first principles models. Machine learning models are incrementally trained from normal data to predict expected values and detect statistically significant short-term deviations. Ageing models are constructed by breaking down physical systems into sub-assemblies, then determining relevant degradation modes and associating each one to the right kinetic law. Validating such anomaly detection and maintenance models is challenging, both because actual incident and ageing data are rare and distorted by human interventions, and incremental learning depends on human feedback. To overcome these difficulties, we propose to simulate physics, systems, and humans -including asset maintenance operations- in order to validate the overall approaches in accelerated time and possibly choose between algorithmic alternatives.

Keywords: degradation models, ageing, anomaly detection, soft sensor, incremental learning

Procedia PDF Downloads 122

Authors: Mari Jaakkola, Jasmiina Haverinen, Tiina Tolonen, Vesa Virtanen

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These process monitoring of biogas plant gives valuable information of the function of the process and help to maintain a stable process. The costs of basic monitoring are often much lower than the costs associated with re-establishing a biologically destabilised plant. Reactor acidification through reactor overload is one of the most common reasons for process deterioration in anaerobic digesters. This occurs because of a build-up of volatile fatty acids (VFAs) produced by acidogenic and acetogenic bacteria. VFAs cause pH values to decrease, and result in toxic conditions in the reactor. Ammonia ensures an adequate supply of nitrogen as a nutrient substance for anaerobic biomass and increases system's buffer capacity, counteracting acidification lead by VFA production. However, elevated ammonia concentration is detrimental to the process due to its toxic effect. VFAs are considered the most reliable analytes for process monitoring. To obtain accurate results, sample storage and transportation need to be carefully controlled. This may be a challenge for off-line laboratory analyses especially when the plant is located far away from the laboratory. The aim of this study was to investigate the correlation between fatty acids, ammonium, and bacteria in the anaerobic digestion samples obtained from an industrial biogas factory. The stability of the analytes was studied comparing the results of the on-site analyses performed in the factory site to the results of the samples stored at room temperature and -18°C (up to 30 days) after sampling. Samples were collected in the biogas plant consisting of three separate mesofilic AD reactors (4000 m³ each) where the main feedstock was swine slurry together with a complex mixture of agricultural plant and animal wastes. Individual VFAs, ammonium, and nutrients (K, Ca, Mg) were studied by capillary electrophoresis (CE). Longer chain fatty acids (oleic, hexadecanoic, and stearic acids) and bacterial profiles were studied by GC-MSD (Gas Chromatography-Mass Selective Detector) and 16S rDNA, respectively. On-site monitoring of the analytes was performed by CE. The main VFA in all samples was acetic acid. However, in one reactor sample elevated levels of several individual VFAs and long chain fatty acids were detected. Also bacterial profile of this sample differed from the profiles of other samples. Acetic acid decomposed fast when the sample was stored in a room temperature. All analytes were stable when stored in a freezer. Ammonium was stable even at a room temperature for the whole testing period. One reactor sample had higher concentration of VFAs and long chain fatty acids than other samples. CE was utilized successfully in the on-site analysis of separate VFAs and NH₄ in the biogas production site. Samples should be analysed in the sampling day if stored in RT or freezed for longer storage time. Fermentation reject can be stored (and transported) at ambient temperature at least for one month without loss of NH₄. This gives flexibility to the logistic solutions when reject is used as a fertilizer.

Keywords: anaerobic digestion, capillary electrophoresis, ammonium, bacteria

Procedia PDF Downloads 167

Authors: Obulesh Avuku, Satwik Sunnam, Sri Charan Mohan Janthuka, Keerthi Yalamaddi

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In the United States alone, there are over 1.5 million spine fractures per year, resulting in about 17,730 spinal cord injuries. The cervical spine is where fractures in the spine most frequently occur. The prevalence of spinal fractures in the elderly has increased, and in this population, fractures may be harder to see on imaging because of coexisting degenerative illness and osteoporosis. Nowadays, computed tomography (CT) is almost completely used instead of radiography for the imaging diagnosis of adult spine fractures (x-rays). To stop neurologic degeneration and paralysis following trauma, it is vital to trace any vertebral fractures at the earliest. Many approaches have been proposed for the classification of the cervical spine [2d models]. We are here in this paper trying to break the bounds and use the vision transformers, a State-Of-The-Art- Model in image classification, by making minimal changes possible to the architecture of ViT and making it 3D-enabled architecture and this is evaluated using a weighted multi-label logarithmic loss. We have taken this problem statement from a previously held Kaggle competition, i.e., RSNA 2022 Cervical Spine Fracture Detection.

Keywords: cervical spine, spinal fractures, osteoporosis, computed tomography, 2d-models, ViT, multi-label logarithmic loss, Kaggle, public score, private score

Procedia PDF Downloads 104

Authors: Tomi Lois Olatunji, Frances Siebert, Ademola Emmanuel Adetunji, Brian Harvey, Johane Gericke, Josias Hamman, Frank Van Der Kooy

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Ethnopharmacological relevance: Sceletium tortuosum (L.) N.E.Br, the most sought after and widely researched species in the genus Sceletium is a succulent forb endemic to South Africa. Traditionally, this medicinal plant is mainly masticated or smoked and used for the relief of toothache, abdominal pain, and as a mood-elevator, analgesic, hypnotic, anxiolytic, thirst and hunger suppressant, and for its intoxicating/euphoric effects. Sceletium tortuosum is currently of widespread scientific interest due to its clinical potential in treating anxiety and depression, relieving stress in healthy individuals, and enhancing cognitive functions. These pharmacological actions are attributed to its phytochemical constituents referred to as mesembrine-type alkaloids. Aim of the review: The aim of this review was to comprehensively summarize and critically evaluate recent research advances on the phytochemistry, pharmacokinetics, biological and clinical activities of the medicinal plant S. tortuosum. Additionally, current ongoing research and future perspectives are also discussed. Methods: All relevant scientific articles, books, MSc and Ph.D. dissertations on botany, behavioral pharmacology, traditional uses, and phytochemistry of S. tortuosum were retrieved from different databases (including Science Direct, PubMed, Google Scholar, Scopus and Web of Science). For pharmacokinetics and pharmacological effects of S. tortuosum, the focus fell on relevant publications published between 2009 and 2021. Results: Twenty-five alkaloids belonging to four structural classes viz: mesembrine, Sceletium A4, joubertiamine, and tortuosamine, have been identified from S. tortuosum, of which the mesembrine class is predominant. The crude extracts and commercially available standardized extracts of S. tortuosum have displayed a wide spectrum of biological activities (e.g. antimalarial, anti-oxidant, immunomodulatory, anti-HIV, neuroprotection, enhancement of cognitive function) in in vitro or in vivo studies. This plant has not yet been studied in a clinical population, but has potential for enhancing cognitive function, and managing anxiety and depression. Conclusion: As an important South African medicinal plant, S. tortuosum has garnered many research advances on its phytochemistry and biological activities over the last decade. These scientific studies have shown that S. tortuosum has various bioactivities. The findings have further established the link between the phytochemistry and pharmacological application, and support the traditional use of S. tortuosum in the indigenous medicine of South Africa.

Keywords: Aizoaceae, Mesembrine, Serotonin, Sceletium tortuosum, Zembrin®, psychoactive, antidepressant

Procedia PDF Downloads 207

Authors: R. Hasterok, A. Betekhtin, N. Borowska, A. Braszewska-Zalewska, E. Breda, K. Chwialkowska, R. Gorkiewicz, D. Idziak, J. Kwasniewska, M. Kwasniewski, D. Siwinska, A. Wiszynska, E. Wolny

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In contrast to animals, the organisation of plant genomes at the cytomolecular level is still relatively poorly studied and understood. However, the Brachypodium genus in general and B. distachyon in particular represent exceptionally good model systems for such study. This is due not only to their highly desirable ‘model’ biological features, such as small nuclear genome, low chromosome number and complex phylogenetic relations, but also to the rapidly and continuously growing repertoire of experimental tools, such as large collections of accessions, WGS information, large insert (BAC) libraries of genomic DNA, etc. Advanced cytomolecular techniques, such as fluorescence in situ hybridisation (FISH) with evermore sophisticated probes, empowered by cutting-edge microscope and digital image acquisition and processing systems, offer unprecedented insight into chromatin organisation at various phases of the cell cycle. A good example is chromosome painting which uses pools of chromosome-specific BAC clones, and enables the tracking of individual chromosomes not only during cell division but also during interphase. This presentation outlines the present status of molecular cytogenetic analyses of plant genome structure, dynamics and evolution using B. distachyon and some of its relatives. The current projects focus on important scientific questions, such as: What mechanisms shape the karyotypes? Is the distribution of individual chromosomes within an interphase nucleus determined? Are there hot spots of structural rearrangement in Brachypodium chromosomes? Which epigenetic processes play a crucial role in B. distachyon embryo development and selective silencing of rRNA genes in Brachypodium allopolyploids? The authors acknowledge financial support from the Polish National Science Centre (grants no. 2012/04/A/NZ3/00572 and 2011/01/B/NZ3/00177)

Keywords: Brachypodium, B. distachyon, chromosome, FISH, molecular cytogenetics, nucleus, plant genome organisation

Procedia PDF Downloads 342