Search results for: plant wearable sensors

Authors: Ahtesham Javaid, Costin S. Bildea

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The design and plantwide control of an integrated plant where the endothermic 1,4-butanediol dehydrogenation and the exothermic furfural hydrogenation is simultaneously performed in a single reactor is studied. The reactions can be carried out in an adiabatic reactor using small hydrogen excess and with reduced parameter sensitivity. The plant is robust and flexible enough to allow different production rates of γ-butyrolactone and 2-methyl furan, keeping high product purities. Rigorous steady state and dynamic simulations performed in AspenPlus and AspenDynamics to support the conclusions.

Keywords: dehydrogenation and hydrogenation, reaction coupling, design and control, process integration

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Authors: B. Samuel Raj, Solomon R. D. Jebakumar

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Microbial fuel cells (MFCs) are an emerging and promising method for achieving sustainable energy since they can remove contaminated organic matter and simultaneously generate electricity. Our approach was driven in three different ways like Bacterial fuel cell, Soil Microbial fuel cell (Soil MFC) and Plant Microbial fuel cell (Plant MFC). Bacterial MFC: Sulphate reducing bacteria (SRB) were isolated and identified as the efficient electricigens which is able to produce ±2.5V (689mW/m2) and it has sustainable activity for 120 days. Experimental data with different MFC revealed that high electricity production harvested continuously for 90 days 1.45V (381mW/m2), 1.98V (456mW/m2) respectively. Biofilm formation was confirmed on the surface of the anode by high content screening (HCS) and scanning electron Microscopic analysis (SEM). Soil MFC: Soil MFC was constructed with low cost and standard Mudwatt soil MFC was purchased from keegotech (USA). Vermicompost soil (V1) produce high energy (± 3.5V for ± 400 days) compared to Agricultural soil (A1) (± 2V for ± 150 days). Biofilm formation was confirmed by HCS and SEM analysis. This finding provides a method for extracting energy from organic matter, but also suggests a strategy for promoting the bioremediation of organic contaminants in subsurface environments. Our Soil MFC were able to run successfully a 3.5V fan and three LED continuously for 150 days. Plant MFC: Amaranthus candatus (P1) and Triticum aestivium (P2) were used in Plant MFC to confirm the electricity production from plant associated microbes, four uniform size of Plant MFC were constructed and checked for energy production. P2 produce high energy (± 3.2V for 40 days) with harvesting interval of two times and P1 produces moderate energy without harvesting interval (±1.5V for 24 days). P2 is able run 3.5V fan continuously for 10days whereas P1 needs optimization of growth conditions to produce high energy.

Keywords: microbial fuel cell, biofilm, soil microbial fuel cell, plant microbial fuel cell

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Authors: Abdullah Özbilgin, Oguzhan Kahraman, Mustafa Selçuk Alataş

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Plant breeders have made and will continue to make important contributions toward meeting the need for more and better feed and food. The use of new techniques to modify the genetic makeup of plants to improve their properties has led to a new generation of crops, grains and their by-products for feed. Plant breeders have made and will continue to make important contributions toward meeting the need for more and better feed and food. The use of new techniques to modify the genetic makeup of plants to improve their properties has led to a new generation of crops, grains and their by-products for feed. The land area devoted to the cultivation of genetically modified (GM) plants has increased in recent years: in 2012 such plants were grown on over 170 million hectares globally, in 28 different countries, and are at resent used by 17.3 million farmers worldwide. The majority of GM plants are used as feed material for food-producing farm animals. Despite the facts that GM plants have been used as feed for years and a number of feeding studies have proved their safety for animals, they still give rise to emotional public discussion.

Keywords: crops, genetical modified plant(GM), plant, safety

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Authors: Rahamdad Khan, Ijaz Ahmad Khan

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In modern agriculture the herbicides application are considered the most effective and fast in action against all types of weeds. But it’s a fact that the herbicide applicator cannot totally secure the crop plants from the possible herbicide injuries that further leads to several destructive changes in plant biochemistry. For the purpose pots studies were undertaken to test the tolerance order of chickpea against pre- emergence herbicides (Stomp 330 EC- Dual Gold 960 EC) and post- emergence herbicides (Topik 15 WP- Puma Super 75 EW- Isoproturon 500 EW) during 2012-13 and 2013-14. The experimental design was CRD with three replications. Plant height, number of branches plant-1, number of seeds plant-1, nodulation, seed protein contents and other growth related parameters in chickpea were examined during the investigations. The results indicate that all the enquire herbicides gave a significant variation to all recorded parameter of chick pea except nodule fresh and dray weight. Moreover the toxic effect of pre-emergence herbicide on chickpea was found higher as compared to post-emergence herbicides. Minimum chickpea plant height (50.50 cm), number of nodule plant-1 (17.83) and lowest seed protein (14.13 %) was recorded in Stomp 330 EC. Similarly the outmost seeds plant-1 (29.66) and number of nodule plant-1 (21) were found for Puma Super 75 EW. The results further showed that the highest seed protein content (21.75 and 21.15 %) was recorded for control/ untreated and Puma Super 75EW. Taking under concentration the possible negative impact of the herbicides the chemical application must be minimized up to certain extent at which the crop is mostly secure. However chemical weed control has many advantages so we should train our farmer regarding the proper use of agro chemical to minimize the loses in crops while using herbicides.

Keywords: chickpea, herbicides, protein, stomp 330 EC, weed

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Authors: Reza Sadeghi, Maryam Nazarahari

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Considering the effectiveness of plant pesticides in pest control, this group of pesticides can provide an efficient way to reduce the damage caused by pests in agriculture and maintain environmental health. Plant pesticides allow farmers to cultivate their crops by lowering the use of chemical pesticides and help improve the quality of agricultural products. In this research, various plant compounds were extracted from two different sources, thyme and eucalyptus, by using n-hexane solvent and investigated to control cotton bollworm in laboratory conditions. The mortality rates of cotton bollworm (Helicoverpa armigera) caused by different concentrations of hexanic extract formulations were evaluated. The results showed that the varied concentrations of the hexanic extract formulations of thyme and eucalyptus had significant effects on the mortality rates of cotton bollworm larvae during a 24-h exposure period. The hexanic extract of thyme as a plant pesticide can be an effective alternative in agriculture and plant pest control. The use of pesticides in agriculture can help the environment and reduce the problems related to chemical toxins. Also, this research revealed that the types and compounds of plant pesticides can be effective in pest control and help to develop more efficient agricultural strategies.

Keywords: cotton bollworm, thyme, eucalyptus, extract formulation, toxicity

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Authors: Astghik R. Sukiasyan

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The semidental sweet maize of Armenian population under drought stress and pollution by some heavy metals (HMs) in sites along the river Debet was studied. Accordingly, the objective of this work was to investigate the antioxidant status of maize plant in order to identify simple and reliable criteria for assessing the degree of adaptation of plants to abiotic stress of drought and HMs. It was found that in the case of removal from the mainstream of the river, the antioxidant status of the plant varies. As parameters, the antioxidant status of the plant has been determined by the activity of malondialdehyde (MDA) and Ferric Reducing Ability of Plasma (FRAP), taking into account the characteristics of natural drought of this region. The possibility of using some indicators which characterized the antioxidant status of the plant was concluded. The criteria for assessing the extent of environmental pollution could be HMs. This fact can be used for the early diagnosis of diseases in the population who lives in these areas and uses corn as the main food.

Keywords: antioxidant status, maize corn, drought stress, heavy metal

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Authors: Narayanakumar Somasundaram, Venkat Nihit Chirivella, Venkata Dilip Kumar Pasupuleti

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Ajakool, India, has a multi-span bridge that is constructed for rail transport with a maximum operating speed of 100 km/hr. It is a standard RDSO design of a PSC box girder carrying a single railway track. The Structural Health Monitoring System (SHM) is designed and installed to compare and analyze the vibrations and displacements on the bridge due to different live loads from moving trains. The study is conducted for three different spans of the same bridge to understand the health of the elastomeric bearings. Also, to validate the same, a three-dimensional finite element model is developed, and modal analysis is carried out. The proposed methodology can help in detecting deteriorated elastomeric bearings using only wireless tri-accelerometer sensors. Detailed analysis and results are presented in terms of mode shapes, accelerations, displacements, and their importance to each other. This can be implemented with a lot of ease and can be more accurate.

Keywords: dynamic effects, vibration analysis, accelerometer sensors, finite element analysis, structural health monitoring, elastomeric bearing

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Authors: Falodun E. J., Ogbeifun S. O.

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The objectives of this study were to investigate the yield, nutrient concentration, and uptake of fluted pumpkin (Telfairia occidentalis Hook. f.) in response to spacing and fertilizer application. Two fluted pumpkin plant populations (10,000 and 20,000 plants ha⁻¹), D1 and D2, were evaluated at three levels of NPK fertilizer (F₁, 20 t ha⁻¹ poultry manure, F₂, 300 kg ha⁻¹ NPK 15:15:15 and F₃, 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ NPK 15:15:15) using a factorial arrangement in a randomized complete block design (RCBD) with three replications. Leaf length, breadth, and the number of leaves were significantly increased at a lower plant population of 10,000 plants ha⁻¹ while herbage yield increased with a higher plant population of 20,000 plants ha⁻¹ using 300 kg ha⁻¹ inorganic NPK 15:15:15 or a combination of 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ inorganic NPK 15:15:15. Potassium (K) concentration was significantly (p < 0.05) higher at 10,000 plants ha⁻¹ and Iron (Fe) uptake was higher with combine application of organic and inorganic fertilizer (F3). To maximize the good herbage yield of fluted pumpkins, farmers in this locality should adopt a plant population of 20,000 plants ha⁻¹ using 300 kg ha⁻¹ inorganic NPK 15:15:15 (D2F2) or a combination of 10 t ha⁻¹ poultry manure + 150 kg ha⁻¹ inorganic NPK 15:15:15 (D2F3).

Keywords: fertilizers, fluted pumpkin, herbage yield, plant population

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Authors: Narin Salehiyan, Ramin Ghasemi Shayan

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The largest genus of plant viruses, the potyvirus, is responsible for significant crop losses. Potyviruses are aphid sent in a nonpersistent way, and some of them are likewise seed communicated. As significant microorganisms, potyviruses are substantially more examined than other plant infections having a place with different genera, and their review covers numerous parts of plant virology, like utilitarian portrayal of viral proteins, sub-atomic communication with hosts and vectors, structure, scientific classification, development, the study of disease transmission, and determination. Biotechnological utilizations of potyviruses are likewise being investigated. During this last ten years, significant advances have been made in the comprehension of the sub-atomic science of these infections and the elements of their different proteins. Potyvirus multiplication, movement, and transmission, as well as potyvirus/plant compatible interactions, including pathogenicity and symptom determinants, are updated following a general overview of the family Potyviridae and the potyviral proteins. it end the survey giving data on biotechnological uses of potyviruses.

Keywords: virology, poty, virus, genome, genetic

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Dana A. Thal, Heike Kahlert, Fritz Scholz

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Thiol molecules are known to easily form self-assembled monolayers (SAM) on Au surfaces. Depending on the thiol’s structure, surface modifications via SAM can be used for electrode sensor development. In the presented work, 1-decanethiol coated polycrystalline Au electrodes were applied to indirectly assess the radical scavenging potential of plant compounds and extracts. Different plant compounds with reported antioxidant properties as well as an extract from the plant Gynostemma pentaphyllum were tested for their effectiveness to prevent SAM degradation on the sensor electrodes via photolytically generated radicals in aqueous media. The SAM degradation was monitored over time by differential pulse voltammetry (DPV) measurements. The results were compared to established antioxidant assays. The obtained data showed an exposure time and concentration dependent degradation process of the SAM at the electrode’s surfaces. The tested substances differed in their capacity to prevent SAM degradation. Calculated radical scavenging activities of the tested plant compounds were different for different assays. The presented method poses a simple system for radical scavenging evaluation and, considering the importance of the test system in antioxidant activity evaluation, might be taken as a bridging tool between in-vivo and in-vitro antioxidant assay in order to obtain more biologically relevant results in antioxidant research.

Keywords: alkanethiol SAM, plant antioxidant, polycrystalline Au, radical scavenger

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Authors: Shikha Masand, Sudesh Kumar Yadav

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Certain protein kinases have been shown to be crucial for plant cell signaling pathways associated with plant immune responses. Here we identified a horsegram [Macrotyloma uniflorum (Lam.) Verdc.] malectin-like leucine rich receptor-like protein kinase (RLK) gene MuRLK. The functional MuRLK protein preferentially binds to mannose and N-acetyl glucosamine residues. MuRLK exists in the cytoplasm and also localizes to the plasma membrane of plant cells via its N-terminus. Over-expression of MuRLK in Arabidopsis enhances the basal resistance to infection with Pseudomonas syringae pv. tomato, Alternaria brassicicola and Hyaloperonospora arabidopsidis, are associated with elevated ROS bursts, MAPK activation, thus ultimately leading to hypersensitive cell death. Moreover, salicylic acid-dependent and jasmonic acid-dependent defense responses are also enhanced in the MuRLK-overexpressed plants that lead to HR-induced cell death. Together, these results suggest that MuRLK plays a key role in the regulation of plant cell death, early and late defense responses after the recognition of microbial pathogens.

Keywords: horsegram, Pseudomonas syringae pv. tomato, MuRLK, ROS burst, cell death, plant defense

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Authors: Yelbek B. Utepov, Assel S. Tulebekova, Alizhan B. Kazkeyev

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Maturity sensors are used to determine concrete strength by the non-destructive method. The method of placement of the maturity sensors determines their number required for a certain frame of a monolithic building. Previous studies weakly describe this aspect, giving only logical assumptions. This paper proposes a cheap prototype of an embedded wireless sensor for monitoring concrete structures, as well as an alternative strategy for placing sensors based on the transitional boundaries of the temperature distribution of concrete curing, which were determined by building a heat map of the temperature distribution, where unknown values are calculated by the method of inverse distance weighing. The developed prototype can simultaneously measure temperature and relative humidity over a smartphone-controlled time interval. It implements a maturity method to assess the in-situ strength of concrete, which is considered an alternative to the traditional shock impulse and compression testing method used in Kazakhstan. The prototype was tested in laboratory and field conditions. The tests were aimed at studying the effect of internal and external temperature and relative humidity on concrete's strength gain. Based on an experimentally poured concrete slab with randomly integrated maturity sensors, it was determined that the transition boundaries form elliptical forms. Temperature distribution over the largest diameter of the ellipses was plotted, resulting in correct and inverted parabolas. As a result, the distance between the closest opposite crossing points of the parabolas is accepted as the maximum permissible step for setting the maturity sensors. The proposed placement strategy can be applied to sensors that measure various continuous phenomena such as relative humidity. Prototype testing has also revealed Bluetooth inconvenience due to weak signal and inability to access multiple prototypes simultaneously. For this reason, further prototype upgrades are planned in future work.

Keywords: heat map, placement strategy, temperature and relative humidity, wireless embedded sensor

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Owing to close antenna spacing between antenna sensors within a compact space, a part of data in one antenna sensor would outflow to other antenna sensors when the antenna sensors in an antenna array operate simultaneously. This phenomenon is called mutual coupling effect (MCE). It has been shown that the performance of antenna array systems can be degraded when the antenna sensors are in close proximity. Especially, in a systems equipped with massive antenna sensors, the degradation of beamforming performance due to the MCE is significantly inevitable. Moreover, it has been shown that even a small angle error between the true direction angle of the desired signal and the steering angle deteriorates the effectiveness of an array beamforming system. However, the true direction vector of the desired signal may not be exactly known in some applications, e.g., the application in land mobile-cellular wireless systems. Therefore, it is worth developing robust techniques to deal with the problem due to the MCE and steering angle error for array beamforming systems. In this paper, we present an efficient technique for performing adaptive beamforming with robust capabilities against the MCE and the steering angle error. Only the data vector received by an antenna array is required by the proposed technique. By using the received array data vector, a correlation matrix is constructed to replace the original correlation matrix associated with the received array data vector. Then, the mutual coupling matrix due to the MCE on the antenna array is estimated through a recursive algorithm. An appropriate estimate of the direction angle of the desired signal can also be obtained during the recursive process. Based on the estimated mutual coupling matrix, the estimated direction angle, and the reconstructed correlation matrix, the proposed technique can effectively cure the performance degradation due to steering angle error and MCE. The novelty of the proposed technique is that the implementation procedure is very simple and the resulting adaptive beamforming performance is satisfactory. Simulation results show that the proposed technique provides much better beamforming performance without requiring complicated complexity as compared with the existing robust techniques.

Keywords: adaptive beamforming, mutual coupling effect, recursive algorithm, steering angle error

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Authors: T. C. Machaba, S. M. Mahlo

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The current study investigates the antifungal properties of crude plant extracts from selected medicinal plant species. Eight plant species used by the traditional healers and local people to treat fungal infections were selected for further phytochemical analysis and biological assay. The selected plant species were extracted with solvent of various polarities such as acetone, methanol, ethanol, hexane, dichloromethane, ethyl acetate and water. Leaf, roots and bark extracts of Maerua juncea Pax, Albuca seineri (Engl & K. Krause) J.C Manning & Goldblatt, Senna italica Mill., Elephantorrhiza elephantina (Burch.) Skeels, Indigofera circinata Benth., Schinus molle L., Asparagus buchananii Bak., were screened for antifungal activity against three animal fungal pathogens (Candida albicans, Aspergillus fumigatus and Cryptococcus neoformans). All plant extracts were active against the tested microorganisms. Acetone, dichloromethane, hexane and ethanol extracts of Senna italica and Elephantorrhiza elephantine had excellent activity against Candida albicans and A. fumigatus with the lowest MIC value of 0.02 mg/ml. Bioautography assay was used to determine the number of antifungal compounds presence in the plant extracts. No active compounds were observed in plant extracts of Indigofera circinnata, Schinus molle and Pentarrhinum insipidum with good antifungal activity against C. albicans and A. fumigatus indicating possible synergism between separated metabolites.

Keywords: antifungal activity, bioautography, ethnobotanical survey, minimum inhibitory concentration

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Authors: Hamid R. Lashgarian Azad, Seyed N. Shetab Boushehri

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Wireless sensor networks (WSN) have become progressively popular due to their wide range of applications. Wireless Sensor Network is made of numerous tiny sensor nodes that are battery-powered. It is a very significant problem to maximize the lifetime of wireless sensor networks. In this paper, we propose a two-stage protocol based on an imperialist competitive algorithm (2S-ICA) to solve a sensor network optimization problem. The energy of the sensors can be greatly reduced and the lifetime of the network reduced by long communication distances between the sensors and the sink. We can minimize the overall communication distance considerably, thereby extending the lifetime of the network lifetime through connecting sensors into a series of independent clusters using 2SICA. Comparison results of the proposed protocol and LEACH protocol, which is common to solving WSN problems, show that our protocol has a better performance in terms of improving network life and increasing the number of transmitted data.

Keywords: wireless sensor network, imperialist competitive algorithm, LEACH protocol, k-means clustering

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Authors: Mahdi Asghari Ozma

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Background and Objective:Maclurapomifera (Rafin.) Schneider, known as osage orange, is a north american native plant which has multiple applications in herbal medicine. The extract of this plant has many therapeutic effects, including antimicrobial, anti-tumor, anti-inflammation, etc., that discussed in this study. Materials and Methods: For this study, the keywords "Maclurapomifera", "osage orange, ""herbal medicine ", and "plant extract" in the databases PubMed and Google Scholar between 2002 and 2021 were searched, and 20 articles were chosen, studied and analyzed. Results: Due to the increased resistance of microbes to antibiotics, the need for antimicrobial plants is increasing. Maclurapomifera is one of the plants with antimicrobial properties that can affect all microbes, especially Gram-negative bacteria, and fungi. This plant also has anti-tumor, anti-inflammatory, anti-oxidant, anti-aging, antiviral, anti-fungal, anti-ulcerogenic, anti-diabetic, and anti-nociceptive effects, which can be used as a substance with many amazing therapeutic applications. Conclusion: These results suggest that the extract of Maclurapomifera can be used in clinical medicine as a remedial agent, which can be substituted for chemical drugs or help them in the treatment of diseases.

Keywords: maclura pomifera, osage orange, herbal medicine, plant extract

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Authors: J. Chandrasekhar Rao, B. G. Naidu, G. J. Naga Raju, P. Sarita

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Particle Induced X-ray Emission (PIXE) and Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) techniques have been employed in this work to determine the elements present in the root of Cyperus rotundus medicinal plant used in the treatment of rheumatoid arthritis. The elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Rb, and Sr were commonly identified and quantified by both PIXE and ICP-MS whereas the elements Li, Be, Al, As, Se, Ag, Cd, Ba, Tl, Pb and U were determined by ICP-MS and Cl, K, Ca, Ti and Br were determined by PIXE. The regional variation of elemental content has also been studied by analyzing the same plant collected from different geographical locations. Information on the elemental content of the medicinal plant would be helpful in correlating its ability in the treatment of rheumatoid arthritis and also in deciding the dosage of this herbal medicine from the metal toxicity point of view. Principal component analysis and cluster analysis were also applied to the data matrix to understand the correlation among the elements.

Keywords: PIXE, CP-MS, elements, Cyperus rotundus, rheumatoid arthritis

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Authors: E. Satoh, R. Kasahara, T. Aoki, K. Fukatsu, D. Venkata Ramanarao, H. Harayama, T. Murata, A. Suwa

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Rice plant hoppers (Hemiptera: Delphacidae) have been causing extensive economic damage in rice and are considered as serious threat in rice producing countries of Asia. They have developed resistance to major groups of chemical insecticide, and severe outbreaks occur commonly throughout Asia. To control these nuisance pests, Nihon Nohyaku Co., Ltd., recently discovered an insecticide, benzpyrimoxan (proposed ISO name), which is under development as NNI-1501 (development code). Benzpyrimoxan has a unique chemical structure which contains benzyloxy and cyclic acetal groups on pyrimidine moiety (5-(1,3-dioxan-2-yl)-4-[4- (trifluoromethyl)benzyloxy]pyrimidine). In order to clarify the biological properties of benzpyrimoxan, we conducted several experiments and found the following results. Benzpyrimoxan has high activity against nymphal stages of rice plant hoppers without any adulticidal activity. It provides excellent and long lasting control against rice plant hoppers, including populations that have developed resistance to several other chemical groups of insecticide. The study on its mode of action is undergoing. These features highlight the versatility of this insecticide as an effective and valuable tool from the viewpoints of insecticide resistance management and integrated pest management program. With the use of benzpyrimoxan, farmers shall be able to lead the best yield potential by keeping the population density of rice plant hoppers and associated virus diseases under control.

Keywords: acetal, benzpyrimoxan, insecticide, NNI-1501, pyrimidine, rice plant hoppers

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Authors: Himanshi Allahabadi

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Plants have found a widespread use in medicine traditionally, including the treatment of cognitive disorders, especially, neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. In terms of indigenous medicine, it has been found that many potential drugs can be isolated from plant products, including those for dementia. Plant product is widely distributed in plant kingdom and forms a major antioxidant source in the human diet, is Polyphenols. There are four important groups of polyphenols: phenolic acids, flavonoids, stilbenes, and lignans. Due to their high antioxidant capacity, interest in their study has greatly increased. There are several methods for discovering and characterizing active compounds isolated from plant sources, now available. The results obtained so far seem fulfilling, but additionally, mechanism of functioning of polyphenols at the molecular level, as well as their application in human health need to be researched upon. Also, even though the neuroprotective effects of flavonoids have been much talked about, much of the data in support of this statement has come from animal studies rather than human studies. This review is based on a multi-faceted study of medicinal plants, i.e. phytochemicals, with special focus on flavanones and their relevance in remedy of Parkinson's disease.

Keywords: dementia, parkinson's disease, flavanones, polyphenols, substantia nigra

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Authors: Solomon Tilahun Desisa, Muktar Seid Hussen

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Hibiscus macranthus is one of family Malvaceae and genus Hibiscus plant which grows mainly in western part of Ethiopia. Hibiscus macranthus is the most adaptable and abundant plant in the nation, which are used as an ornamental plant often a hedge or fence plant, and used as a firewood after harvesting the stem together with the bark, and used also as a fiber for trying different kinds of things by forming the rope. However, Hibiscus macranthus plant fibre has not been commercially exploited and extracted properly. This study of work describes the possibility of mechanical and retting methods of Hibiscus macranthus fibre extraction and characterization. Hibiscus macranthus fibre is a bast fibre which obtained naturally from the stem or stalks of the dicotyledonous plant since it is a natural cellulose plant fiber. And the fibre characterized by studying its physical and chemical properties. The physical characteristics were investigated as follows, including the length of 100-190mm, fineness of 1.0-1.2Tex, diameter under X100 microscopic view 16-21 microns, the moisture content of 12.46% and dry tenacity of 48-57cN/Tex along with breaking extension of 0.9-1.6%. Hibiscus macranthus fiber productivity was observed that 12-18% of the stem out of which more than 65% is primary long fibers. The fiber separation methods prove to decrease of non-cellulose ingredients in the order of mechanical, water and chemical methods. The color measurement also shows the raw Hibiscus macranthus fiber has a natural golden color according to YID1925 and paler look under both retting methods than mechanical separation. Finally, it is suggested that Hibiscus macranthus fibre can be used for manufacturing of natural and organic crop and coffee packages as well as super absorbent, fine and high tenacity textile products.

Keywords: Hibiscus macranthus, bast fiber, extraction, characterization

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Authors: Alise Senberga, Laila Dubova, Liene Strauta, Ina Alsina, Ieva Erdberga

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Legume symbiotic relationship with nitrogen fixating bacteria Rhizobim leguminosarum is an important factor used to improve the productivity of legumes, due to the fact that rhizobia can supply plant with the necessary amount of nitrogen. R. leguminosarum strains have shown different activity in fixing nitrogen. Depending on the chosen R. leguminosarum strain, host plant biochemical content can be altered. In this study we focused particularly on the changes in protein content in beans (using two different varieties) and peas (five different varieties) due to the use of several different R. leguminosarum strains (four strains for both beans and peas). Overall, the protein content increase was observed after seed inoculation with R. leguminosarum. Strain and plant cultivar interaction specification was observed. The effect of R. leguminosarum inoculation on the content of protein was dependent on the R. leguminosarum strain used. Plant cultivar also appeared to have a decisive role in protein content formation with the help of R. leguminosaru.

Keywords: legumes, protein content, rhizobia strains, soil

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Authors: Sk Shamim Hasan Abir, Karen Lozano, Mohammed Jasim Uddin

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Over the last few years, nanofiber-based triboelectric nanogenerator (TENG) has caught great attention among researchers all over the world due to its inherent capability of converting mechanical energy to usable electrical energy. In this study, poly(vinylidene fluoride) (PVDF) and thermoplastic polyurethane (TPU) nanofiber prepared by Forcespinning® (FS) technique were used to fabricate TENG for self-charging energy storage device and biomechanical body motion sensor. The surface of the TPU nanofiber was modified by uniform deposition of thin gold film to enhance the frictional properties; yielded 254 V open-circuit voltage (Voc) and 86 µA short circuit current (Isc), which were 2.12 and 1.87 times greater in contrast to bare PVDF-TPU TENG. Moreover, the as-fabricated PVDF-TPU/Au TENG was tested against variable capacitors and resistive load, and the results showed that with a 3.2 x 2.5 cm2 active contact area, it can quick charge up to 7.64 V within 30 seconds using a 1.0 µF capacitor and generate significant 2.54 mW power, enough to light 75 commercial LEDs (1.5 V each) by the hand tapping motion at 4 Hz (240 beats per minutes (bpm)) load frequency. Furthermore, the TENG was attached to different body parts to capture distinctive electrical signals for various body movements, elucidated the prospective usability of our prepared nanofiber-based TENG in wearable body motion sensor application.

Keywords: biomotion sensor, forcespinning, nanofibers, triboelectric nanogenerator

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Authors: Matthew Kostawich, Mohammed Elmorsy, Mohamed Sayed Sifat, Shoukry Shams, Mahmoud Elsaadany

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6G communication systems represent the nominal future extension of current wireless technology, where its impact is extended to touch upon all human activities, including medical, security, and entertainment applications. As a result, human needs are allocated among the highest priority aspects of the system design and requirements. 6G communications is expected to replace all the current video conferencing with interactive virtual reality meetings involving high data-rate transmission merged with massive distributed computing resources. In addition, the current expansion of IoT applications must be mitigated with significant network changes to provide a reasonable Quality of Service (QoS). This directly implies a high demand for Human-Computer Interaction (HCI) through mobile computing modules in future wireless communication systems. This article proposes the utilization of a Printed Ridge Gap Waveguide (PRGW) to host the wearable nodes. To the best of our knowledge, we propose for the first time a physical layer analysis within the context of a complete architecture. A thorough study is provided on the impact of the distortion of the guiding structure on the overall system performance. The proposed structure shows small latency and small losses, highlighting its compatibility with future applications.

Keywords: ridge gap waveguide, edge computing module, 6G, multimedia IoT applications

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Authors: Pragnyashree Mishra, Shradhanjali Mohapatra

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The present investigation is carried out to know the effect of foliar feeding of nitrogen and gibberellic acid on vegetative growth, flowering behaviour and yield of calendula variety ‘Golden Emporer’. The experiment was laid out in RBD in rabi season of 2013-14. There are 16 treatments are taken at different level such as nitrogen (at 0%,1%,2%,3%) and GA3 (at 50 ppm,100ppm,150 ppm). Among them maximum height at bud initiation stage was obtained at 3% nitrogen (27.00 cm) and at 150 ppm GA3 (26.5 cm), fist flowering was obtained at 3% nitrogen(60.00 days) and at 150 ppm GA3 (63.75 days), maximum flower stalk length was obtained at 3% nitrogen(3.50 cm) and at 150 ppm GA3 (5.42 cm),maximum duration of flowering was obtained at 3% nitrogen(46.00 days) and at 150 ppm GA3 (46.50days), maximum number of flower was obtained at 3% nitrogen (89.00per plant) and at 150 ppm GA3 (83.50 per plant), maximum flower weight was obtained at 3% nitrogen(1.25 gm per flower) and at 150 ppm GA3 (1.50 gm per flower), maximum yield was was obtained at 3% nitrogen (110.00 gm per plant) and at 150 ppm GA3 (105.00gm per plant) and minimum of all character was obtained when 0% nitrogen0 ppm GA3. All interaction between nitrogen and GA3 was found in significant except the yield .

Keywords: calendula, golden emporer, GA3, nitrogen and gibberellic acid

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Authors: Othman Maklouf, Abdunnaser Tresh

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Land vehicle navigation is subject of great interest today. Global Positioning System (GPS) is the main navigation system for positioning in such systems. GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation (INS) is the implementation of inertial sensors to determine the position and orientation of a vehicle. The availability of low-cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop INS using an inertial measurement unit (IMU). INS has unbounded error growth since the error accumulates at each step. Usually, GPS and INS are integrated with a loosely coupled scheme. With the development of low-cost, MEMS inertial sensors and GPS technology, integrated INS/GPS systems are beginning to meet the growing demands of lower cost, smaller size, and seamless navigation solutions for land vehicles. Although MEMS inertial sensors are very inexpensive compared to conventional sensors, their cost (especially MEMS gyros) is still not acceptable for many low-end civilian applications (for example, commercial car navigation or personal location systems). An efficient way to reduce the expense of these systems is to reduce the number of gyros and accelerometers, therefore, to use a partial IMU (ParIMU) configuration. For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a field experiment for a low-cost strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach, we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of our low-cost IMU (Inertial Measurement Unit) and because of the relatively small area of the trajectory.

Keywords: GPS, IMU, Kalman filter, materials engineering

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Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar

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The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.

Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system

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Authors: Lormaine Anne A. Branzuela, Elysa V. Largo, Monet Concepcion M. Detras, Neil C. Concibido

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The electricity demand is still increasing, and currently, the Philippine government is investigating the feasibility of operating the Bataan Nuclear Power Plant (BNPP) to address the country’s energy problem. However, the lack of process safety studies on BNPP focused on the effects of hazardous substances on the integrity of the structure, equipment, and other components, have made the plant operationalization questionable to the public. The three major nuclear power plant incidents – TMI-2, Chernobyl, and Fukushima – have made many people hesitant to include nuclear energy in the energy matrix. This study focused on the safety evaluation of possible operations of a nuclear power plant installed with a Pressurized Water Reactor (PWR), which is similar to BNPP. Failure Mode and Effects Analysis (FMEA) is one of the Process Hazard Analysis (PHA) techniques used for the identification of equipment failure modes and minimizing its consequences. Using the FMEA technique, this study was able to recognize 116 different failure modes in total. Upon computation and ranking of the risk priority number (RPN) and criticality rating (CR), it showed that failure of the reactor coolant pump due to earthquakes is the most critical failure mode. This hazard scenario could lead to a nuclear meltdown and radioactive release, as identified by the FMEA team. Safeguards and recommended risk reduction strategies to lower the RPN and CR were identified such that the effects are minimized, the likelihood of occurrence is reduced, and failure detection is improved.

Keywords: PHA, FMEA, nuclear power plant, bataan nuclear power plant

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Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle

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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.

Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3

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Authors: Atish Bagchi, Siva Chandrasekaran

Abstract:

Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

Procedia PDF Downloads 124