Search results for: plant detection

Authors: Baltazar Ndakidemi

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The resource-constrained farmers, especially those in sub-Saharan Africa, encounter significant challenges related to agriculture, notably diseases and pests. The sustainable means of pest management are not well known to farmers. As a result, some farmers use synthetic pesticides whose environmental impacts, ill health, and other negative impacts of synthetic pesticides on natural enemies have posed a great need for more sustainable means of pest management. Pesticidal plant resources can replace synthetic pesticides because their secondary metabolites can exhibit insecticidal activities such as deterrence, repellence, and pests' mortality. Additionally, the volatiles from these plants can have positive effects of attracting populations of natural enemies. Pesticidal plants can be grown as field margin plants or in strips for supporting natural enemies' populations. However, this is practically undetermined. Hence, there is a need to investigate the roles played by pesticidal plants in supporting natural enemies of pests and their applications in different cropping systems such as legumes. This study investigates different pesticidal plants with a high potential for pest control in agricultural fields. The information sheds light on potential plants that can be used for different crop pests.

Keywords: natural enemies, biological control, synthetic pesticides, pesticidal plants, predators, parasitoids

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Authors: Pimchanok Puksisuwan, Pitak Laorattanakul, Benya Cherdhirunkorn

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The use of aluminium dross as a raw material for geopolymer synthesis via mechanochemistry method was studied. The geopolymers were prepared using aluminium dross from secondary aluminium industry, fly ash from a biomass power plant and liquid alkaline activators, which is a mixture of sodium silicate solution (Na2SiO3) and sodium hydroxide solution (NaOH) (Na2SiO3/NaOH ratio 4:1, 3:1 and 2:1). Aluminium dross consists mostly of alumina (Al2O3), silicon oxide (SiO2) and aluminium nitride (AlN). The raw materials were mixed and milled using the high energy ball milling method for 5, 10 and 15 minutes in order to reduce the particle size. The milled powders were uniaxially pressed into a cylinder die with the pressure of 2200 psi. The cylinder samples were cured in the sealed plastic bags for 3, 7 and 14 days at the room temperature and 60°C for 24 hour. The mechanical property of geopolymers was investigated. In addition, scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis were carried out in order to study the microstructure and phase structures of the geopolymers, respectively. The results showed that aluminium dross could enhance the mechanical property of geopolymers product by mechanochemistry method and meet the TISI requirements.

Keywords: aluminium dross, fly ash, geopolymer, mechanochemistry

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Authors: Shirin Aghanajafizadeh

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Nest site selection of Crested Lark was investigated in Boroyeh wildlife sanctuary of Harat during spring 2014. Habitat variables such as number of plant species, soil texture, distance to the nearest water resources, farms and roads were compared in the species presence plots with absence ones. Our analysis showed that the average number of Zygophyllum atriplicoidesand, Artemisia sieberi were higher while fine-textured soil percent cover (with very little and gravel) was lower in species presence plots than control plots. We resulted that the most affecting factor in the species nest site selection is the number of Z .atriplicoides and soil texture. Z. atriplicoides and A. sieberi can provide cover for nests and chickens against predators and environmental harsh events such as sunshine and wind. The stability of built nest forces the birds to select sites with not fine-textured soil. Some of the nests were detected in Alfalfa farms that can be related to its cover producing capability.

Keywords: habitat selection, Yazd Province, presence and absence plots, habitat variables

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Authors: Kaan Karaoglu, Raif Bayir

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In this study, a cartesian robot is developed to improve the performance and efficiency of wireless charging of electric vehicles. The cartesian robot has three axes, each of which moves linearly. Magnetic positioning is used to align the cartesian robot transmitter charging pad. There are two different wireless charging methods, static and dynamic, for charging electric vehicles. The current state of charge information (SOC State of Charge) and location information are received wirelessly from the electric vehicle. Based on this information, the power to be transmitted is determined, and the transmitter and receiver charging pads are aligned for maximum efficiency. With this study, a fully automated cartesian robot structure will be used to charge electric vehicles with the highest possible efficiency. With the wireless communication established between the electric vehicle and the charging station, the charging status will be monitored in real-time. The cartesian robot developed in this study is a fully automatic system that can be easily used in static wireless charging systems with vehicle-machine communication.

Keywords: electric vehicle, wireless charging systems, energy efficiency, cartesian robot, location detection, trajectory planning

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Authors: Tianyang Xu

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Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target.

Keywords: underwater target;, non-uniform characteristics;, cluster-driven method;, acoustic scattering characteristics

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Authors: Alemayehu Hailemicael Mezgebe, A. J. Solomon Raju

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Context: Lake Chamo is a significant lake in the Ethiopian Rift Valley, known for its diversity of wildlife and vegetation. However, the lake is facing various threats due to human activities and global effects. The poor management of resources could lead to food insecurity, ecological degradation, and loss of biodiversity. Research Aim: The aim of this study is to analyze the environmental implications of lake level changes using GIS and remote sensing. The research also aims to examine the floristic composition of the lakeside vegetation and propose spatially oriented environmental planning for the sustainable utilization of the biodiversity resources. Methodology: The study utilizes multi-temporal satellite images and aerial photographs to analyze the changes in the lake area over the past 45 years. Geospatial analysis techniques are employed to assess land use and land cover changes and change detection matrix. The composition and role of the lakeside vegetation in the ecological and hydrological functions are also examined. Findings: The analysis reveals that the lake has shrunk by 14.42% over the years, with significant modifications to its upstream segment. The study identifies various threats to the lake-wetland ecosystem, including changes in water chemistry, overfishing, and poor waste management. The study also highlights the impact of human activities on the lake's limnology, with an increase in conductivity, salinity, and alkalinity. Floristic composition analysis of the lake-wetland ecosystem showed definite pattern of the vegetation distribution. The vegetation composition can be generally categorized into three belts namely, the herbaceous belt, the legume belt and the bush-shrub-small trees belt. The vegetation belts collectively act as different-sized sieve screen system and calm down the pace of incoming foreign matter. This stratified vegetation provides vital information to decide the management interventions for the sustainability of lake-wetland ecosystem.Theoretical Importance: The study contributes to the understanding of the environmental changes and threats faced by Lake Chamo. It provides insights into the impact of human activities on the lake-wetland ecosystem and emphasizes the need for sustainable resource management. Data Collection and Analysis Procedures: The study utilizes aerial photographs, satellite imagery, and field observations to collect data. Geospatial analysis techniques are employed to process and analyze the data, including land use/land cover changes and change detection matrices. Floristic composition analysis is conducted to assess the vegetation patterns Question Addressed: The study addresses the question of how lake level changes and human activities impact the environmental health and biodiversity of Lake Chamo. It also explores the potential opportunities and threats related to water utilization and waste management. Conclusion: The study recommends the implementation of spatially oriented environmental planning to ensure the sustainable utilization and maintenance of Lake Chamo's biodiversity resources. It emphasizes the need for proper waste management, improved irrigation facilities, and a buffer zone with specific vegetation patterns to restore and protect the lake outskirt.

Keywords: buffer zone, geo-spatial, lake chamo, lake level changes, sustainable utilization

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Authors: Ikele Chika Bright, Mgbenka Bernard Obialo, Ikele Chioma Faith

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Icthyophthiriasis is a prevalent protozoan (ectoparasite) mostly affecting cultured and aquarium fishes. The majority of the chemotherapeutants lack efficacy for completely eliminating Ich parasite without affecting the environment and they are not safe for human health. The present work is focused on the evaluating different immersion treatments of African catfish (Clarias gariepinus) infected with ichthyophthiriasis and treated with a non-chemical and environmental friendly parasiticides Moringa oleifera. A total number of 800 apparently healthy parasites free (examined) post juvenile catfish were obtained from a reputable farm, disinfected with potassium permanganate in a quarantine tank to remove any possible external parasites. The fish were further challenged with approximately 44,000 infective stages of theronts which were obtained through serial passages by cohabitation. Seven groups (A-G) of post Juvenile were used for the experiment which was carried out into three stages; Dips (60minutes), short term treatment (24-96h) and prolong bath treatment (0-15 days). The concentrations selected were dependent on the outcome of the LC50 of the plant material from which dose-dependent factors were used to select various concentrations of the treatment. In Dips treatment, group D-G were treated with 1,500mg/L, 2500mg/L., 3500mg/L and 4500mg/L, short-term treatment was treated with 150mg/L, 250mg/L, 350mg/L and 450mg/L and prolong bath was treated with 15mg/L, 25mg/L, 35mg/L and 45mg/L of the plant extract whereas group A, B and C were normal control, Ich- infested not treated and Ich- infested treated with standard drug (Acriflavin), respectively. The various types of treatment applied with corresponding concentrations showed almost complete elimination of the adult parasites (trophonts) both in the gills and the body smear, thereby making M. oleifera a potential parasiticides. There were serious pathological alterations in the skin and gills which are usually the main point for Ich parasites invasion but no significant morphological characteristics was noted among the treated groups subjected to different immersion treatment patterns. Epitheliocystis, aneurysm, oedema, hemorrhage, and localization of the adult parasite in the gills were the overall common observations made in the gills whereas degeneration of muscle fibre, dermatitis, hemorrhage, oedema, abscess formation and keratinisation were observed in the skin. However, there are no pathological changes in the control group. Moreover, biochemical parameters such as urea, creatinine, albumin., globulin, total protein, ALT, AST), blood chemistry (sodium, chloride, potassium, bicarbonate), antioxidants (CAT, SOD, GPx, LPO), enzymatic activities (myeloperoxidase, thioreadoxin reductase), Inflammatory response (C-reactive protein), Stress markers (lactate dehydrogenase), heamatological parameters (RBC, PCV, WBC, HB and differential count), lipid profile (total cholesterol, tryglycerides , high density lipoprotein and low density lipoprotein) all showed various significant (P<0.05) and no significant (P>0.05) responses among the Ich-infested fish treated under three immersion treatments. It is suggested that M. oleifera may serve as an alternatives to chemotherapeutants for control of Ichthyophthiriasis in African catfish Clarias gariepinus.

Keywords: Icthyophthirius multifilis, immersion treatment, pathophysiology, African catfish

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Authors: F. Z. Aliyat, B. Ben Messaoud, L. Nassiri, E. Bouiamrine, J. Ibijbijen

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The present study aims to assess the biological nitrogen fixation in the soybean tested in different Moroccan soils combined with the rhizobial inoculation. These effects were evaluated by the plant growth mainly by the aerial biomass production, total nitrogen content and the proportion of the nitrogen fixed. This assessment clearly shows that the inoculation with bacteria increases the growth of soybean. Five different soils and a control (peat) were used. The rhizobial inoculation was performed by applying the peat that contained a mixture of 2 strains Sinorhizobium fredii HH103 and Bradyrhizobium. The biomass, the total nitrogen content and the proportion of nitrogen fixed were evaluated under different treatments. The essay was realized at the greenhouse the Faculty of Sciences, Moulay Ismail University. The soybean has shown a great response for the parameters assessed. Moreover, the best response was reported by the inoculated plants compared to non- inoculated and to the absolute control. Finally, good production and the best biological nitrogen fixation present an important ecological technology to improve the sustainable production of soybean and to ensure the increase of the fertility of soils.

Keywords: biological nitrogen fixation, inoculation, rhizobium, soybean

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Amira Shakila Razali, Faridah Lisa Supian, Muhammad Mat Salleh, Suriani Abu Bakar

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Water contamination by toxic compound is one of the serious environmental problems today. These toxic compounds mostly originated from industrial effluents, agriculture, natural sources and human waste. These study are focused on modification of multiwalled carbon nanotube (MWCNTs) with nanoparticle of calixarene and explore the possibility of using this nanocomposites for the remediation of cadmium in water. The nanocomposites were prepared by dissolving calixarene in chloroform solution as solvent, followed by additional multiwalled carbon nanotube (MWCNTs) then sonication process for 3 hour and fabricated the nanocomposites on substrate by spin coating method. Finally, the nanocomposites were tested on cadmium ion (10 mg/ml). The morphology of nanocomposites was investigated by FESEM showing the formation of calixarene on the outer walls of carbon nanotube and cadmium ion also clearly seen from the micrograph. This formation was supported by using energy dispersive x-ray (EDX). The presence of cadmium ions in the films, leads to some changes in the surface potential and Fourier Transform Infrared spectroscopy (FTIR).This nanocomposites have potential for development of sensor for pollutant monitoring and nanoelectronics devices applications

Keywords: calixarene, multiwalled carbon nanotubes, cadmium, surface potential

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Authors: Nikolaos Katsoulas, Ioannis Naounoulis, Sofia Faliagka

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Cascade hydroponic systems have the potential to minimize environmental impact and improve resource efficiency by recycling the nutrient solution drained from a hydroponic (primary-donor) crop to irrigate another (secondary-receiver), less sensitive to salinity crop. However, it remains unclear if the drained solution from the primary crop can fully meet the nutritional requirements of a secondary crop and whether the productivity of the secondary crop is affected. To address this question, a prototype cascade hydroponic system was designed and tested using a cucumber crop as the donor crop and a melon as secondary crop. The performance of the system in terms of productivity and water and nutrient use efficiency was evaluated by measuring plant growth, fresh and dry matter production, nutrients content, and photosynthesis rate in the secondary crop. The amount of water and nutrients used for the primary and secondary crops was also recorded. This work was carried out under the ECONUTRI project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Horizon Europe Grant agreement: 101081858.

Keywords: hydroponics, salinity, water use efficiencu, nutrients use efficiency

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Authors: Abdallah Sofiane Berrouk, Dara Satyadileep

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This paper investigates the feasibility of retrofitting a middle-east based commercial amine sweetening unit with a split-flow scheme which involves withdrawing a portion of partially stripped semi-lean solvent from the stripping column and re-injecting it in the absorption column to reduce the overall energy consumption of the unit. This method is comprehensively explored by performing parametric analysis of the split fraction of the semi-lean solvent using a kinetics based process simulator ProMax V 3.2. Re-boiler duty, condenser duty, solvent cooling and pumping loads are analysed as functions of a split fraction of the semi-lean solvent from the stripper. It is shown that the proposed method significantly reduces the overall energy consumption of the unit resulting in an annual savings of 325,000 USD. The thorough economic analysis is performed using Aspen Economic Evaluation V 8.4 to reveal that the retrofit scheme pays back the capital cost in less than eight years and is highly recommended for any commercial plant having suitable provisions for solvent inlet/withdrawal on the columns.

Keywords: split flow, Amine, gas processing, optimization

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Juhi Kaushik, Abhishek Agarwal, Manoj Sarda, Vatsal Sanjay, Arup Kumar Das

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Fire accidents in trains bring huge disaster to human life and property. Evacuation becomes a major challenge in such incidents owing to confined spaces, large passenger density and trains moving at high speeds. The pantry car in Indian Railways trains carry inflammable materials like cooking fuel and LPG and electrical fittings. The pantry car is therefore highly susceptible to fire accidents. Numerical simulations have been done in a pantry car of Indian locomotive train using computational fluid dynamics based software. Different scenarios of a fire outbreak have been explored by varying Heat Release Rate per Unit Area (HRRPUA) of the fire source, introduction of exhaust in the cooking area, and taking a case of an air conditioned pantry car. Temporal statures of flame and soot have been obtained for each scenario and differences have been studied and reported. Inputs from this study can be used to assess casualties in fire accidents in locomotive trains and development of smoke control/detection systems in Indian trains.

Keywords: fire propagation, flame contour, pantry fire, soot flow

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Maryam Kiani

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The self-sensing capability opens up new possibilities for structural health monitoring, offering real-time information on the condition and performance of constructions. The synthesis and characterization of these functional 2D material geopolymers will be explored in this study. Various fabrication techniques, including mixing, dispersion, and coating methods, will be employed to ensure uniform distribution and integration of the 2D materials within the geopolymers. The resulting composite materials will be evaluated for their mechanical strength, electrical conductivity, and sensing capabilities through rigorous testing and analysis. The potential applications of these self-sensing geopolymers are vast. They can be used in infrastructure projects, such as bridges, tunnels, and buildings, to provide continuous monitoring and early detection of structural damage or degradation. This proactive approach to maintenance and safety can significantly improve the lifespan and efficiency of constructions, ultimately reducing maintenance costs and enhancing overall sustainability. In conclusion, the development of functional 2D material geopolymers as self-sensing materials presents an exciting advancement in the construction industry. By integrating these innovative materials into structures, we can create a new generation of intelligent, self-monitoring constructions that can adapt and respond to their environment.

Keywords: 2D materials, geopolymers, electrical properties, self-sensing

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Authors: Wael Khalil, Elias Rahal, Ghassan Matar

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Tooth related infections or commonly named dental infections have been described as the most common causes of tooth loss in adults. These pathologies were mostly periodontitis, pericoronitis, and periapical infection. The involvement of various bacteria in the pathogenesis of these pathologies has been thoroughly mentioned and approved in the literature. However, the variability in the severity and prognosis of these lesions among patients suggests the association of other pathogens, like viruses and fungi, in the pathogenesis of these lesions. Several studies in the literature investigated the association of multiple viruses and fungi with the above-mentioned lesions, yet, a vast controversy was reached concerning this subject.Aim: Our study aims to fill the gap in the literature concerning the contribution of adenovirus, HPV-16, EBV, fungi, and candida in the pathogenesis of periodontitis, pericoronitis, and periapical infection. For this purpose, we utilized the quantitative PCR for pathogen detection in saliva, gingival, and lesions samples of involved subjects. Results: Some of these pathogens appeared to have an association with the investigated dental pathologies, while others showed no contribution to the pathogenesis of these lesions. Further investigation is required in order to identify the subtype of the involved pathogens in these tooth related oral pathology.

Keywords: periodontitis, pericoronitis, dental abscess, PCR, microbiology

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Authors: Ali M. Zaid, Muftah Mayouf, Yahya Said Farouj

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The effect of post emergence herbicides on soil micro-flora and nitrogen fixing bacteria was studied in pea field. Pea (Pisum sativum) was grown and treated with one or a mixture of two of several herbicides 2 weeks after sowing. Soil samples were collected 2 weeks after herbicides application. Average number of colony forming units per gram of soil of bacteria, actinomycetes and fungi were determined. Average number of nodules per plant was obtained at the end of the growing season. The results of the study showed MCPB, Bentazon, MCPB+Fluozifop-p-butyl, Bentazon+Fluozifop-p-butyl, Metribuzin, Flouzifop-p-butyl+Metribuzin, Cycloxydin, and Sethoxydin increased the population of soil fungi, with 4 to 10 times compared with the control. The herbicides used showed no significant effects on nitrogen fixing bacteria. The effects of herbicides on soil bacteria and actinomycetes were different. The study showed the use of herbicides could influence the biological balance of soil microflora, which has an important role in soil fertility and microbial ecosystem.

Keywords: herbicides, post emergence, nitrogen fixing bacteria, environmental systems

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Authors: Izdihar Ismail, Alona C. Linatoc, Maryati Mohamed

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The tropical rainforest of Malaysia is known for its rich biological diversity and high endemicity. The potential for these forests to hold the cure for many diseases and illnesses is high and much is yet to be discovered. This study explores the richness of the tropical rainforest of Endau-Rompin National Park in Johor, Malaysia in search of plants traditionally used by the indigenous people in the treatment of malaria and malaria-like symptoms. Seven species of plants were evaluated and tested for antiplasmodial activities. Different plant parts were subjected to methanolic and aqueous extractions. A total of 24 extracts were evaluated by histidine-rich protein II (HRP2) assay against K1 strain of Plasmodium falciparum chloroquine-resistant. Ten extracts showed significant inhibition of the growth of P. falciparum. Phytochemical screening of the same extracts revealed the presence of alkaloids, flavonoids, terpenoids and anthraquinones. This study affirms that tropical rainforests may still hold undiscovered cures for many diseases and illnesses that have inflicted millions of people worldwide. The species studied herein have not known to have been studied elsewhere before.

Keywords: Endau-Rompin, malaria, Malaysia, tropical rainforest, traditional knowledge

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Authors: Van Tang Nguyen, Jennette A. Sakoff, Christopher J. Scarlett

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Phyllanthus amarus (P. amarus) has been used as a traditional herbal plant for the treatment of chronic ailments such as hepatitis, diabetes and cancer. The objectives of this study were to determine the physicochemical properties, antioxidant and cytotoxic activities of crude P. amarus extracts and fractions using MTT and CCK-8 assays for cytotoxic evaluation. The outcomes indicated that P. amarus methanol (PAM) extract had lower residual moisture (7.40%) and water activity (0.24) and higher contents of saponins, phenolics, flavonoids and proanthocyanidins (1657.86 mg escin equivalents, 250.45 mg gallic acid equivalents, 274.73 mg rutin equivalents and 61.22 mg catechin equivalents/g dried extract, respectively) than those of P. amarus water (PAW) extract, resulting antioxidant activity of PAM extract was significantly higher (P < 0.05) than that of PAW extract, PAM fractions and phyllanthin (a major compound in P. amarus). Cytotoxic activity of PAM extract for cancer cell lines of MiaPaCa-2 (pancreas), HT29 (colon), A2780 (ovarian), H460 (lung), A431 (skin), Du145 (prostate), BE2-C (neuroblastoma), MCF-7 (breast), MCF-10A (normal breast), and U87, SJ-G2, SMA (glioblastoma) was higher than those of PAW extract and PAM fractions. Therefore, we can conclude that the PA extracts are a potential source for the development of natural antioxidant products and/or novel anticancer drugs.

Keywords: antioxidant, cytotoxicity, Phyllanthus amarus, physicochemical

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Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi

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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.

Keywords: visible light communication, lane-centerin, platooning, intelligent transportation systems, road safety applications

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Authors: Ennus Tajuddin Tamboli, Madhukar Garg, Mohd. Mujeeb, Sayeed Ahmad

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An efficient protocol for simultaneous production of forskolin and rosmarinic acid in in vitro callus derived from the leaves of Coleus forskohlii Briq. has been developed. MS media was used for the establishment of cultures and NAA + 6-BA (1.0 ppm) was found best for callus growth. The callus was further subjected to treatment with various elicitor/precursors viz. chitosan, thidiazuron and methyl jasmonate to observe their effect on production of biomass and accumulation of secondary metabolites. The content of forskolin and rosmarinic acid were estimated by HPTLC, in comparison to natural explant which showed 2 fold and 10 fold rise in forskolin and rosmarinic acid content, respectively. Methy1 jasmonate 50 µM was found best for production of forskolin, whereas thidiazuron showed best results in the yield of rosmarinic acid, separately in static culture. However, combined treatment in suspension culture showed moderated effect for increase in secondary metabolites but the biomass increased significantly as compared to static culture.

Keywords: plant tissue culture, secondary metabolites, coleus, forskolin, rosmarinic acid, HPTLC

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Authors: Rachel Bechtold, Catherine Shoulders, Donald Johnson, Jennie Popp, Elena Garcia, Lisa Wood

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Creating successfully restored urban landscapes involves both the sound design of natural resources and the incorporation of human perceptions of landscape. Moving forward with an invested interest from society is a challenge for the efficacy of reclaimed landscape design. In particular, urban areas present a dynamic environment wherein society and nature compete for resources and space. This review is meant to examine how perceptions of urban community members, the stakeholders for the plant species that share their environment, are reflected in aesthetic considerations. Findings from this literature review include themes of (1) aesthetic perceptions of stakeholders in rehabilitated landscapes and (2) the importance of organizing indicators of aesthetic perception for future design decisions. Recommendations include addressing the gap in research on aesthetic perceptions of reclaimed urban landscapes and addressing the lack of a consistent and widely accepted framework for these interdisciplinary studies. With knowledge of stakeholder perceptions, improved aesthetic and ecologic designs can more seamlessly merge into reclaimed urban landscapes.

Keywords: phytoremediation, urban landscape design, aesthetic perception, landscape ecology, phytorestoration, landscape reclamation, rehabilitation

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

Abstract:

Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

Procedia PDF Downloads 261

Authors: Mingyuan Duan

Abstract:

Many scholars have paid attention to the relationship between mobility and stillness, but most of them focus on stillness from the perspective of serving mobility. This study believes that more attention should be paid to the importance of stillness, and we suggest reexamining the meaning of stillness in terms of the value of stillness to people. The Errand Boy Project was launched by a social innovation enterprise called Bottle Dream during the May Day holiday in 2022. It linked volunteers from all over the world online to help people who are trapped at home due to the epidemic realize their outdoor wishes: get closer to nature and relieve their anxious mood. Taking Errand Boy in Tibet as a case study, this paper analyzes the emotional expressions and comments of people with limited mobility in the face of nature in the webcast room and explains the importance of stillness to humans from a non-human perspective. This study points out that the significance of stillness to human beings during the pandemic is composed of three aspects: the sense of solidity established by a steady mobile phone network connection, the stable possibility of wish fulfillment predicted by the periodic regularity of plant growth, and the transcendent spiritual power from the stable sacred mountain.

Keywords: stillness, non-human, pandemic, mobility

Procedia PDF Downloads 66

Authors: Samih Abubaker, Amjad Abuserhan, Ghandi Anfoka

Abstract:

Potato yield reduction and soil salt accumulation are the main obstacles of using brackish water in irrigation. This study was carried out at Al- Balqa` Applied University research station, to investigate the impact of compost use on potato production and salt accumulation in the soil under brackish water, during 2014 growing season. Whole tubers of three imported potato cultivars (Spunta, Faluka and Ammbetion) were planted in pots with different soil and compost percentages (0, 20, 40, 60, 80, and 100%) and were irrigated with three water salinity levels (1.25, 5 and 10 ds/cm). A split-split plot design was used, where potato cultivars were arranged in the main plots, the brackish water treatments were in the sub-main and the soil amended treatments were in the sub-sub plots. Potato yield was generally decreased only when pots were irrigated by water of 10 ds/cm salinity compared with 1.25 and 5 ds/cm. Drainage water salinity, however, was increased as compost percentage increased. Nevertheless, salt accumulation in the growing media was decreased as the compost percentage level increased. Therefore, it can be concluded that brackish water, up to 5 ds/cm can be used to irrigate potato especially, when organic amendments were added to the soil to promote plant growth, yield and reduce salt accumulation.

Keywords: brackish water, compost, potato, salt accumulation

Procedia PDF Downloads 316

Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

Abstract:

Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

Procedia PDF Downloads 256

Authors: Alesandro Romero, Inaki Maulida Hakim

Abstract:

This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck; the average efficiency was 97,4 % with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. Furthermore, from the calculation of logistics cost of the ideal condition, it brings savings of Rp53.011.800,00 in a month. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost Rp3.966.559,40 per day, and increase the average of the truck efficiency 8,78% per day.

Keywords: efficiency, logistic cost, milkrun, saving methode, simulation

Procedia PDF Downloads 441