Search results for: RLS identification algorithm

Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Catelyn Coyle, Helena Kwakwa

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Objective: As novel and better tolerated therapies become available, effective HCV testing and care models become increasingly necessary to not only identify individuals with active infection but also link them to HCV providers for medical evaluation and treatment. Our aim is to describe an effective HCV testing and linkage to care model piloted in a network of five community health centers located in Philadelphia, PA. Methods: In October 2012, National Nursing Centers Consortium piloted a routine opt-out HCV testing model in a network of community health centers, one of which treats HCV, HIV, and co-infected patients. Key aspects of the model were medical assistant initiated testing, the use of laboratory-based reflex test technology, and electronic medical record modifications to prompt, track, report and facilitate payment of test costs. Universal testing on all adult patients was implemented at health centers serving patients at high-risk for HCV. The other sites integrated high-risk based testing, where patients meeting one or more of the CDC testing recommendation risk factors or had a history of homelessness were eligible for HCV testing. Mid-course adjustments included the integration of dual HIV testing, development of a linkage to care coordinator position to facilitate the transition of HIV and/or HCV-positive patients from primary to specialist care, and the transition to universal HCV testing across all testing sites. Results: From October 2012 to June 2015, the health centers performed 7,730 HCV tests and identified 886 (11.5%) patients with a positive HCV-antibody test. Of those with positive HCV-antibody tests, 838 (94.6%) had an HCV-RNA confirmatory test and 590 (70.4%) progressed to current HCV infection (overall prevalence=7.6%); 524 (88.8%) received their RNA-positive test result; 429 (72.7%) were referred to an HCV care specialist and 271 (45.9%) were seen by the HCV care specialist. The best linkage to care results were seen at the test and treat the site, where of the 333 patients were current HCV infection, 175 (52.6%) were seen by an HCV care specialist. Of the patients with active HCV infection, 349 (59.2%) were unaware of their HCV-positive status at the time of diagnosis. Since the integration of dual HCV/HIV testing in September 2013, 9,506 HIV tests were performed, 85 (0.9%) patients had positive HIV tests, 81 (95.3%) received their confirmed HIV test result and 77 (90.6%) were linked to HIV care. Dual HCV/HIV testing increased the number of HCV tests performed by 362 between the 9 months preceding dual testing and first 9 months after dual testing integration, representing a 23.7% increment. Conclusion: Our HCV testing model shows that integrated routine testing and linkage to care is feasible and improved detection and linkage to care in a primary care setting. We found that prevalence of current HCV infection was higher than that seen in locally in Philadelphia and nationwide. Intensive linkage services can increase the number of patients who successfully navigate the HCV treatment cascade. The linkage to care coordinator position is an important position that acts as a trusted intermediary for patients being linked to care.

Keywords: HCV, routine testing, linkage to care, community health centers

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Authors: M. A. Peribanez, G. Illan, I. De Blas, A. Muniesa, I. Ruiz-Zarzuela

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Intensive aquaculture is commonly associated with increased incidence of parasites. However, in Spain, the recent intensification of cyprinid production has not led to knowledge of the parasites that develop in the aquaculture facilities, the factors that affect their development and spread and the transmission between wild and cultivated fish species. The present study focuses on the knowledge of environmental factors, as well as host dependent factors, and their possible influence as risk factors in the incidence and intensity of parasitic infections. This work was conducted in the Duero River Basin, NW Spain. A total of 114 tenches (Tinca tinca) were caught in a fish farm and 667 specimens belonging to six species of cyprinid, not tench, in five rivers. An exhaustive search and microscopic identification of protozoa on skin and gills were carried out. Physical, chemical, and biological parameters of water samples from the capture points were determined. Only two ectoprotozoa were identified, Ichthyophthirius multifiliis and Tripartiella sp. In I. multifiliis, a high intensity of infection (more than 40 parasites on the body surface and more than 80 on gills) was determined in farmed tench (14%) and in Iberian barbel (Luciobarbus bocagei) (91%) and Duero nase (Pseudochondrostoma duriense) (71%) of middle stretches of rivers. The prevalence was similar between farmed tenches and cyprinids of middle courses. Tripartiella sp. was only found in barbels (prevalence in middle stretches, 0.7%) and in farmed tenches (63%), this species resulting in a high risk factor (odds ratio, OR= 1143) in the presence of the ciliate. There were no differences between the two species relative to the intensity of parasitization. Some of the physical, chemical and microbiological water quality parameters appear to be risk factors in the presence of I. multifiliis, with maximum OR of 8. Nevertheless, in Tripartiella sp., the risk is multiplied by 720 when the pH value exceeds 8.4, if we consider the total of the data, and it is increased more than 500 times if we only consider the values recorded in the fish farm (529 by nitrates > 3 mg/l; 530 by total coliforms > 100 CFU/100 ml). However, the high prevalence and risk of infection by I. multifiliis and Tripartiella sp. in fish farms should be related to environmental factors that dependent upon sampling point rather than in direct influence of the physical-chemical and biological parameters of the water. The high pH value recorded in the fish farm (9.62 ± 0.76) is the only parameter that we consider may have a substantial direct influence. Chronic exposure to alkaline pH levels can be a chronic stress generator, predisposing to parasitization by Tripartiella sp. In conclusion, often minor changes in ecosystem conditions, both natural and man-made, can modify the host-parasite relationship, resulting in an increase in the prevalence and intensity of parasitic infections in populations of cyprinids, sometimes causing disease outbreaks.

Keywords: cyprinids, fish, parasites, protozoa, risk factors

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Authors: Tiziana Pepe, Gerardo Manfreda, Adriana Ianieri, Aniello Anastasio

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The sustainable exploitation of marine biological resources is among the most important objectives of the EU's Common Fisheries Policy (CFP). Currently, Europe imports about 65% of its fish products, indicating that domestic production does not meet consumer demand. Despite the availability of numerous commercially significant fish species, European consumption is concentrated on a limited number of products (e.g., sea bass, sea bream, shrimp). Many native species, present in large quantities in the Mediterranean Sea, are little known to consumers and are therefore considered ‘fishing by-products’. All the data presented so far indicate a significant waste of local resources and the overexploitation of a few fish stocks. It is therefore necessary to develop strategies that guide the market towards sustainable conversion. The objective of this work was to valorize underutilized fish species of the Mediterranean Sea through a multidisciplinary approach. To this end, three fish species were sampled: Atlantic Horse Mackerel (Trachurus trachurus), Bogue (Boops boops), and Common Dolphinfish (Coryphaena hippurus). Nutritional properties (water %, fats, proteins, ashes, salts), physical/chemical properties (TVB-N, histamine, pH), and rheological properties (color, texture, viscosity) were analyzed. The analyses were conducted on both fillets and processing by-products. Additionally, mitochondrial DNA (mtDNA) was extracted from the muscle of each species. The mtDNA was then sequenced using the Illumina NGS technique. The analysis of nutritional properties classified the fillets of the sampled species as lean or semi-fat, as they had a fat content of less than 3%, while the by-products showed a higher lipid content (2.7-5%). The protein percentage for all fillets was 22-23%, while for processing by-products, the protein concentration was 18-19% for all species. Rheological analyses showed an increase in viscosity in saline solution in all species, indicating their potential suitability for industrial processing. High-quality and quantity complete mtDNA was extracted from all analyzed species. The complete mitochondrial genome sequences were successfully obtained and annotated. The results of this study suggest that all analyzed species are suitable for both human consumption and feed production. The sequencing of the complete mtDNA and its availability in international databases will be useful for accurate phylogenetic analysis and proper species identification, even in prepared and processed products. Underutilized fish species represent an important economic resource. Encouraging their consumption could limit the phenomenon of overfishing, protecting marine biodiversity. Furthermore, the valorization of these species will increase national fish production, supporting the local economy, cultural, and gastronomic tradition, and optimizing the exploitation of Mediterranean resources in accordance with the CFP.

Keywords: mtDNA, nutritional analysis, sustainable fisheries, underutilized fish species

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Mohit Kumar

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Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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Authors: Hamdan Hamood Aldumaini, Amjad Hussein Meqdam, Shamsaldeen kassim Ali, Hamed Mohammed Al-Yousefi, Haron Ahmed Al-Badawi

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Background: Autism Spectrum Disorder (ASD) is a complex developmental challenge characterized by significant impairments in social interaction, communication, and behavioral patterns. Diagnosing ASD is challenging due to the lack of definitive medical tests, making early identification crucial. Therefore, increasing people's awareness about autism leads to early diagnosis and better prognosis. Objective: Our study aims to identify the initial symptoms prompting families to seek medical advice, determine the timeline between symptom onset and formal diagnosis, and explore methods for assessing the severity of ASD. Subjects and Methods: The study design employed was a descriptive cross-sectional design, which was suitable for the nature of the research. The data collection took place from March 5, 2022, to April 5, 2022, in Autism Rehabilitation Centers in Sana'a, Yemen. The study population consisted of all children who were diagnosed with autism and visited Autism rehabilitation centers in Sana'a city. The sample size was determined using Epi info version 7, and a total population of 587 autistic children attending the treatment was calculated, but only 250 children were included in this study (176 were male vs. 74 female). Result: In terms of sociability problems, it was found that a significant proportion of Yemeni children with autism experienced difficulties in this area. Specifically, 39.6% were classified as having severe sociability problems, while 28.4% were classified as having moderate issues. Sensory-cognitive awareness problems were also prevalent among the respondents, with 29.6% exhibiting severe difficulties in this domain. Health and physical problems were identified as significant concerns for Yemeni children with autism. The results indicated that 38.4% of the participants experienced severe health and physical issues. Identifying the first symptoms of autism is crucial for early detection and intervention. According to the study, speech delay was the most commonly observed first abnormality, reported by 71.3% of parents. Communication difficulties with others were the second most noticed abnormality, reported by 54.9% of parents. Repetitive movements were the third most commonly observed abnormality, reported by 18% of parents. Regarding the awareness among parents of ASD, our study showed that a significant portion (62%) of parents lack awareness about Autism Spectrum Disorder (ASD) and its causes. Surprisingly, a majority of these parents (over 80%) believe that autism is a curable condition. Additionally, more than half (51.2%) of the parents surveyed reported insufficient knowledge about medication options available to support therapy and rehabilitation for their autistic children.

Keywords: autism characteristics, rehabilitation centres, yemen, children

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Authors: Monika Rani, Claudio Marchesi, Stefania Federici, Laura E. Depero

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Degradation of the aquatic environment by plastic litter, especially microplastics (MPs), i.e., any water-insoluble solid plastic particle with the longest dimension in the range 1µm and 1000 µm (=1 mm) size, is an unfortunate indication of the advancement of the Anthropocene age on Earth. Microplastics formed due to natural weathering processes are termed as secondary microplastics, while when these are synthesized in industries, they are called primary microplastics. Their presence from the highest peaks to the deepest points in oceans explored and their resistance to biological and chemical decay has adversely affected the environment, especially marine life. Even though the presence of MPs in the marine environment is well-reported, a legitimate and authentic analytical technique to sample, analyze, and quantify the MPs is still under progress and testing stages. Among the characterization techniques, vibrational spectroscopic techniques are largely adopted in the field of polymers. And the ongoing miniaturization of these methods is on the way to revolutionize the plastic recycling industry. In this scenario, the capability and the feasibility of a miniaturized near-infrared (MicroNIR) spectroscopy combined with chemometrics tools for qualitative and quantitative analysis of urban plastic waste collected from a recycling plant and microplastic mixture fragmented in the lab were investigated. Based on the Resin Identification Code, 250 plastic samples were used for macroplastic analysis and to set up a library of polymers. Subsequently, MicroNIR spectra were analysed through the application of multivariate modelling. Principal Components Analysis (PCA) was used as an unsupervised tool to find trends within the data. After the exploratory PCA analysis, a supervised classification tool was applied in order to distinguish the different plastic classes, and a database containing the NIR spectra of polymers was made. For the microplastic analysis, the three most abundant polymers in the plastic litter, PE, PP, PS, were mechanically fragmented in the laboratory to micron size. The distinctive arrangement of blends of these three microplastics was prepared in line with a designed ternary composition plot. After the PCA exploratory analysis, a quantitative model Partial Least Squares Regression (PLSR) allowed to predict the percentage of microplastics in the mixtures. With a complete dataset of 63 compositions, PLS was calibrated with 42 data-points. The model was used to predict the composition of 21 unknown mixtures of the test set. The advantage of the consolidated NIR Chemometric approach lies in the quick evaluation of whether the sample is macro or micro, contaminated, coloured or not, and with no sample pre-treatment. The technique can be utilized with bigger example volumes and even considers an on-site evaluation and in this manner satisfies the need for a high-throughput strategy.

Keywords: chemometrics, microNIR, microplastics, urban plastic waste

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Authors: Marwa Djebbi, Hakim Gabtni

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Gravity is a continuously advancing method that has become a mature technology for geological studies. Increasingly, it has been used to complement and constrain traditional seismic data and even used as the only tool to get information of the sub-surface. In fact, in some regions the seismic data, if available, are of poor quality and hard to be interpreted. Such is the case for the current study area. The Nefza zone is part of the Tellian fold and thrust belt domain in the north west of Tunisia. It is essentially made of a pile of allochthonous units resulting from a major Neogene tectonic event. Its tectonic and stratigraphic developments have always been subject of controversies. Considering the geological and hydrogeological importance of this area, a detailed interdisciplinary study has been conducted integrating geology, seismic and gravity techniques. The interpretation of Gravity data allowed the delimitation of the dune reservoir and the identification of the regional lineaments contouring the area. It revealed the presence of three gravity lows that correspond to the dune of Zouara and Ouchtata separated along with a positive gravity axis espousing the Ain Allega_Aroub Er Roumane axe. The Bouguer gravity map illustrated the compartmentalization of the Zouara dune into two depressions separated by a NW-SE anomaly trend. This constitution was confirmed by the vertical derivative map which showed the individualization of two depressions with slightly different anomaly values. The horizontal gravity gradient magnitude was performed in order to determine the different geological features present in the studied area. The latest indicated the presence of NE-SW parallel folds according to the major Atlasic direction. Also, NW-SE and EW trends were identified. The maxima tracing confirmed this direction by the presence of NE-SW faults, mainly the Ghardimaou_Cap Serrat accident. The quality of the available seismic sections and the absence of borehole data in the region, except few hydraulic wells that been drilled and showing the heterogeneity of the substratum of the dune, required the process of gravity modeling of this challenging area that necessitates to be modeled for the geometrical characterization of the dune reservoir and determine the different stratigraphic series underneath these deposits. For more detailed and accurate results, the scale of study will be reduced in coming research. A more concise method will be elaborated; the 4D microgravity survey. This approach is considered as an expansion of gravity method and its fourth dimension is time. It will allow a continuous and repeated monitoring of fluid movement in the subsurface according to the micro gal (μgall) scale. The gravity effect is a result of a monthly variation of the dynamic groundwater level which correlates with rainfall during different periods.

Keywords: 3D gravity modeling, dune reservoir, heterogeneous substratum, seismic interpretation

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Authors: Benito Minjarez, Jesse Haramati, Yury Rodriguez-Yanez, Florencio Recendiz-Hurtado, Juan-Pedro Luna-Arias, Salvador Mena-Munguia

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During the last decades, the world has experienced a rapid industrialization and an expanding economy favoring a demographic boom. As a consequence, countries around the world have focused on developing new strategies related to the production of different farm products in order to meet future demands. Consequently, different strategies have been developed seeking to improve the major food products for both humans and livestock. Corn, after wheat and rice, is the third most important crop globally and is the primary food source for both humans and livestock in many regions around the globe. In addition, maize (Zea mays) is an important source of protein accounting for up to 60% of the daily human protein supply. Generally, many of the cereal grains have proteins with relatively low nutritional value, when they are compared with proteins from meat. In the case of corn, much of the protein is found in the endosperm (75 to 85%) and is deficient in two essential amino acids, lysine, and tryptophan. This deficiency results in an imbalance of amino acids and low protein content; normal maize varieties have less than half of the recommended amino acids for human nutrition. In addition, studies have shown that this deficiency has been associated with symptoms of growth impairment, anemia, hypoproteinemia, and fatty liver. Due to the fact that most of the presently available maize varieties do not contain the quality and quantity of proteins necessary for a balanced diet, different countries have focused on the research of quality protein maize (QPM). Researchers have characterized QPM noting that these varieties may contain between 70 to 100% more residues of the amino acids essential for animal and human nutrition, lysine, and tryptophan, than common corn. Several countries in Africa, Latin America, as well as China, have incorporated QPM in their agricultural development plan. Large parts of these countries have chosen a specific QPM variety based on their local needs and climate. Reviews have described the breeding methods of maize and have revealed the lack of studies on genetic and proteomic diversity of proteins in QPM varieties, and their genetic relationships with normal maize varieties. Therefore, molecular marker identification using tools such as mass spectrometry may accelerate the selection of plants that carry the desired proteins with high lysine and tryptophan concentration. To date, QPM maize lines have played a very important role in alleviating the malnutrition, and better characterization of these lines would provide a valuable nutritional enhancement for use in the resource-poor regions of the world. Thus, the objectives of this study were to identify proteins in QPM maize in comparison with a common maize line as a control.

Keywords: corn, mass spectrometry, QPM, tryptophan

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Authors: Christian Lauter, Corin Reuter, Shuang Wu, Thomas Troester

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Lightweight construction became more and more important over the last decades in several applications, e.g. in the automotive or aircraft sector. This is the result of economic and ecological constraints on the one hand and increasing safety and comfort requirements on the other hand. In the field of lightweight design, different approaches are used due to specific requirements towards the technical systems. The use of endless carbon fiber reinforced plastics (CFRP) offers the largest weight saving potential of sometimes more than 50% compared to conventional metal-constructions. However, there are very limited industrial applications because of the cost-intensive manufacturing of the fibers and production technologies. Other disadvantages of pure CFRP-structures affect the quality control or the damage resistance. One approach to meet these challenges is hybrid materials. This means CFRP and sheet metal are combined on a material level. Therefore, new opportunities for innovative process routes are realizable. Hybrid lightweight design results in lower costs due to an optimized material utilization and the possibility to integrate the structures in already existing production processes of automobile manufacturers. In recent and current research, the advantages of two-layered hybrid materials have been pointed out, i.e. the possibility to realize structures with tailored mechanical properties or to divide the curing cycle of the epoxy resin into two steps. Current research work at the Chair for Automotive Lightweight Design (LiA) at the Paderborn University focusses on production processes for fiber-metal-laminates. The aim of this work is the development and qualification of a large-scale production process for high-performance fiber-metal-laminates (FML) for industrial applications in the automotive or aircraft sector. Therefore, the prepreg-press-technology is used, in which pre-impregnated carbon fibers and sheet metals are formed and cured in a closed, heated mold. The investigations focus e.g. on the realization of short process chains and cycle times, on the reduction of time-consuming manual process steps, and the reduction of material costs. This paper gives an overview over the considerable steps of the production process in the beginning. Afterwards experimental results are discussed. This part concentrates on the influence of different process parameters on the mechanical properties, the laminate quality and the identification of process limits. Concluding the advantages of this technology compared to conventional FML-production-processes and other lightweight design approaches are carried out.

Keywords: composite material, fiber-metal-laminate, lightweight construction, prepreg-press-technology, large-series production

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Su Hui Tsai, Weir Sen Lin, Rhay Hung Weng

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There are numerous outpatient departments at hospitals with enormous amounts of outpatients. Although the work of outpatient nursing staff does not include the ward, emergency and critical care units that involve patient life-threatening conditions, the work is cumbersome and requires facing and dealing with a large number of outpatients in a short period of time. Therefore, nursing staff often do not feel satisfied with their work and cannot identify with their professional role, leading to intentions to leave their job. Thus, the main purpose of this study is to explore the correlation between the job satisfaction and role identity of nursing staff with turnover intention. This research was conducted using a questionnaire, and the subjects were outpatient nursing staff in three regional hospitals in Southern Taiwan. A total of 175 questionnaires were distributed, and 166 valid questionnaires were returned. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The influence of role identity and job satisfaction on nursing staff’s turnover intention was analyzed by descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. Results showed that 'role identity' had significant differences in different types of marriages. Job satisfaction of 'grasp of environment' had significant differences in different levels of education. Job satisfaction of 'professional growth' and 'shifts and days off' showed significant differences in different types of marriages. 'Role identity' and 'job satisfaction' were negatively correlated with turnover intention respectively. Job satisfaction of 'salary and benefits' and 'grasp of environment' were significant predictors of role identity. The higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. Job satisfaction of 'patient and family interaction' were significant predictors of turnover intention. The lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. This study found that outpatient nursing staff had the lowest satisfaction towards salary structure. It is recommended that bonuses, promotion opportunities and other incentives be established to increase the role identity of outpatient nursing staff. The results showed that the higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. It is recommended that regular evaluations be conducted to reward nursing staff with excellent service and invite nursing staff to share their work experiences and thoughts, to enhance nursing staff’s expectation and identification of their occupational role, as well as instilling the concept of organizational service and organizational expectations of emotional display. The results showed that the lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. It is recommended that interpersonal communication and workplace violence prevention educational training courses be organized to enhance the communication and interaction of nursing staff with patients and their families.

Keywords: outpatient, job satisfaction, turnover, intention

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Authors: Madia Safdar, G. Amjad Hussain, Mashhood Ahmad

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One of the major challenges of today’s era is peak demand which causes stress on the transmission lines and also raises the cost of energy generation and ultimately higher electricity bills to the end users, and it was used to be managed by the supply side management. However, nowadays this has been withdrawn because of existence of potential in the demand side management (DSM) having its economic and- environmental advantages. DSM in domestic load can play a vital role in reducing the peak load demand on the network provides a significant cost saving. In this paper the potential of demand response (DR) in reducing the peak load demands and electricity bills to the electric users is elaborated. For this purpose the domestic appliances are modeled in MATLAB Simulink and controlled by a module called energy management controller. The devices are categorized into controllable and uncontrollable loads and are operated according to real-time tariff pricing pattern instead of fixed time pricing or variable pricing. Energy management controller decides the switching instants of the controllable appliances based on the results from optimization algorithms. In GAMS software, the MILP (mixed integer linear programming) algorithm is used for optimization. In different cases, different constraints are used for optimization, considering the comforts, needs and priorities of the end users. Results are compared and the savings in electricity bills are discussed in this paper considering real time pricing and fixed tariff pricing, which exhibits the existence of potential to reduce electricity bills and peak loads in demand side management. It is seen that using real time pricing tariff instead of fixed tariff pricing helps to save in the electricity bills. Moreover the simulation results of the proposed energy management system show that the gained power savings lie in high range. It is anticipated that the result of this research will prove to be highly effective to the utility companies as well as in the improvement of domestic DR.

Keywords: controllable and uncontrollable domestic loads, demand response, demand side management, optimization, MILP (mixed integer linear programming)

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Authors: Thaís T. Valério Caetano, João Máximo De Siqueira, Carlos Alexandre Carollo, Arthur Ladeira Macedo, Vanessa C. Stein

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Nicotiana glauca, commonly known as wild tobacco or tobacco bush, belongs to the Solanaceae family. It is native to South America but has become naturalized in various regions, including Australia, California, Africa, and the Mediterranean. N. glauca is listed in the Global Invasive Species Database (GISD) and the Invasive Species Compendium (CABI). It is known for producing pyridine alkaloids, including anabasine, which is highly toxic. Anabasine is predominantly found in the leaves and can cause severe health issues such as neuromuscular blockade, respiratory arrest, and cardiovascular problems when ingested. Mistaken identity with edible plants like spinach has resulted in food poisoning cases in Israel and Brazil. Anabasine, a minor alkaloid constituent of tobacco, may contribute to tobacco addiction by mimicking or enhancing the effects of nicotine. Therefore, it is essential to investigate the production pattern of anabasine and its relationship to the developmental stages of the plant. This study aimed to establish the relationship between the phenological plant age, cultivation place, and the increase in anabasine concentration, which can lead to human intoxication cases. In this study, N. glauca plants were collected from three different rural areas in Brazil for a year to examine leaves at various stages of development. Samples were also obtained from cultivated plants in Marilândia, Minas Gerais, Brazil, as well as from Divinópolis, Minas Gerais, Brazil, and Arraial do Cabo, Rio de Janeiro, Brazil. In vitro cultivated plants on MS medium were included in the study. The collected leaves were dried, powdered, and stored. Alkaloid extraction was performed using a methanol and water mixture, followed by liquid-liquid extraction with chloroform. The anabasine content was determined using HPLC-DAD analysis with nicotine as a standard. The results indicated that anabasine production increases with the plant's development, peaking in adult leaves during the reproduction phase and declining afterward. In vitro, plants showed similar anabasine production to young leaves. The successful adaptation of N. glauca in new environments poses a global problem, and the correlation between anabasine production and the plant's developmental stages has been understudied. The presence of substances produced by the plant can pose a risk to other species, especially when mistaken for edible plants. The findings from this study shed light on the pattern of anabasine production and its association with plant development, contributing to a better understanding of the potential risks associated with N. glauca and the importance of accurate identification.

Keywords: nicotiana glauca graham, global invasive species database, alkaloids, toxic

Procedia PDF Downloads 88

Authors: Ahmet Karagoz, Irfan Karagoz

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Synthetic Aperture Radar (SAR) is a radar mechanism that can be integrated into manned and unmanned aerial vehicles to create high-resolution images in all weather conditions, regardless of day and night. In this study, SAR images of military vehicles with different azimuth and descent angles are pre-processed at the first stage. The main purpose here is to reduce the high speckle noise found in SAR images. For this, the Wiener adaptive filter, the mean filter, and the median filters are used to reduce the amount of speckle noise in the images without causing loss of data. During the image segmentation phase, pixel values are ordered so that the target vehicle region is separated from other regions containing unnecessary information. The target image is parsed with the brightest 20% pixel value of 255 and the other pixel values of 0. In addition, by using appropriate parameters of statistical region merging algorithm, segmentation comparison is performed. In the step of feature extraction, the feature vectors belonging to the vehicles are obtained by using Gabor filters with different orientation, frequency and angle values. A number of Gabor filters are created by changing the orientation, frequency and angle parameters of the Gabor filters to extract important features of the images that form the distinctive parts. Finally, images are classified by sparse representation method. In the study, l₁ norm analysis of sparse representation is used. A joint database of the feature vectors generated by the target images of military vehicle types is obtained side by side and this database is transformed into the matrix form. In order to classify the vehicles in a similar way, the test images of each vehicle is converted to the vector form and l₁ norm analysis of the sparse representation method is applied through the existing database matrix form. As a result, correct recognition has been performed by matching the target images of military vehicles with the test images by means of the sparse representation method. 97% classification success of SAR images of different military vehicle types is obtained.

Keywords: automatic target recognition, sparse representation, image classification, SAR images

Procedia PDF Downloads 366

Authors: Sophie-Bo Heinkel, Andrea Rechenburg, Thomas Kistemann

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The current status of wellbeing and life satisfaction of subsistence farmers in a wetland in Uganda and the contributing role of place attachment has been assessed. The aim of this study is to shed light on environmental factors supporting wellbeing in a wetland setting. Furthermore, it has been assessed, how the emotional bonding to the wetland as ‘place’ influences the peoples’ wellbeing and life satisfaction. The results shed light on the human-environment-relationship. A survey was carried out in three communities in urban and rural areas in a wetland basin in Uganda. A sample (n=235) provided information about the attachment to the wetland, the participants’ relation to the place of their residence and their emotional wellbeing. The Wellbeing Index (WHO-5) was assessed as well as the Perceived Stress Scale (PSS-10) and Rosenberg’s Self-Esteem scale (RSE). Furthermore, the Satisfaction With Life Scale (SWLS) was applied as well as the Place Attachment Inventory (PAI), which consists of the two intertwined dimensions of place identity and place dependence. Beside this, binary indicators as ‘feeling save’ and ‘feeling comfortable’ and ‘enjoying to live at the place of residence’ have been assessed. A bivariate correlation analysis revealed a high interconnectivity between all metric scales. Especially, the subscale ‘place identity’ showed significances with all other scales. A cluster analysis revealed three groups, which differed in the perception of place-related indicators and their attachment to the wetland as well as the status of wellbeing. First, a cluster whose majority is dissatisfied with their lives, but mainly had a good status of emotional well-being. This group does not feel attached to the wetland and lives in a town. Comparably less persons of this group feel safe and comfortable at their place of residence. In the second cluster, persons feel highly attached to the wetland and identify with it. This group was characterized by the high number of persons preferring their current place of residence and do not consider moving. All persons feel well and satisfied with their lives. The third group of persons is mainly living in rural areas and feels highly attached to the wetland. They are satisfied with their lives, but only a small minority is in a good emotional state of wellbeing. The emotional attachment to a place influences life satisfaction and, indirectly, the emotional wellbeing. In the present study it could be shown that subsistence farmers are attached to the wetland, as it is the source of their livelihood. While those living in areas with a good infrastructure are less dependent on the wetland and, therefore, less attached to. This feeling also was mirrored in the perception of a place as being safe and comfortable. The identification with a place is crucial for the feeling of being at “home”. Subsistence farmers feel attached to the ecosystem, but they also might be exposed to environmental and social stressors influencing their short-term emotional wellbeing. The provision of place identity is an ecosystem service provided by wetlands, which supports the status of wellbeing in human beings.

Keywords: mental health, positive environments, quality of life, wellbeing

Procedia PDF Downloads 410

Authors: Shawn P. Daly

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Communities heavily engaged in the tourism industry discover their values intersect, meld, and conflict with those of visitors. Maintaining cultural integrity in the face of powerful external pressures causes stress among society members. This effect represents a less studied aspect of sustainable tourism. The present paper brings a perspective unique to the tourism literature: biculturalism. The grounded theories, coherent hypotheses, and validated constructs and indicators of biculturalism represent a sound base from which to consider sociocultural issues in sustainable tourism. Five models describe the psychological state of individuals operating at cultural crossroads: assimilation (joining the new culture), acculturation (grasping the new culture but remaining of the original culture), alternation (varying behavior to cultural context), multicultural (maintaining distinct cultures), and fusion (blending cultures). These five processes divide into two units of analysis (individual and society), permitting research questions at levels important for considering sociocultural sustainability. Acculturation modelling has morphed into dual processes of acculturation (new culture adaptation) and enculturation (original culture adaptation). This dichotomy divides sustainability research questions into human impacts from assimilation (acquiring new culture, throwing away original), separation (rejecting new culture, keeping original), integration (acquiring new culture, keeping original), and marginalization (rejecting new culture, throwing away original). Biculturalism is often cast in terms of its emotional, behavioral, and cognitive dimensions. Required cultural adjustments and varying levels of cultural competence lead to physical, psychological, and emotional outcomes, including depression, lowered life satisfaction and self-esteem, headaches, and back pain—or enhanced career success, social skills, and life styles. Numerous studies provide empirical scales and research hypotheses for sustainability research into tourism’s causality and effect on local well-being. One key issue in applying biculturalism to sustainability scholarship concerns identification and specification of the alternative new culture contacting local culture. Evidence exists for tourism industry, universal tourist, and location/event-specific tourist culture. The biculturalism paradigm holds promise for researchers examining evolving cultural identity and integrity in response to mass tourism. In particular, confirmed constructs and scales simplify operationalization of tourism sustainability studies in terms of human impact and adjustment.

Keywords: biculturalism, cultural integrity, psychological and sociocultural adjustment, tourist culture

Procedia PDF Downloads 409

Authors: Sukran Karatas

Abstract:

Authentic energy network interrelations between the Creator and the creations as well as from creations to creations are the most important points for the worlds of physics and metaphysic to unite together and work in harmony, both within human beings, on the other hand, have the ability to choose their own life style voluntarily. However, it includes the automated involuntary spirit, soul and body working systems together with the voluntary actions, which involve personal, cultural and universal, rational or irrational variable values. Therefore, it is necessary for human beings to know the methods of existing authentic energy network connections to be able to communicate correlate and accommodate the physical and metaphysical entities as a proper functioning unity; this is essential for complete human psychological, biological and social well-being. Authentic knowledge is necessary for human beings to verify the position of self within self and with others to regulate conscious and voluntary actions accordingly in order to prevent oppressions and frictions within self and between self and others. Unfortunately, the absence of genuine individual and universal basic knowledge about how to establish an authentic energy network connection within self, with the deity and the environment is the most problematic issue even in the twenty-first century. The second most problematic issue is how to maintain freedom, equality and justice among human beings during these strictly interwoven network connections, which naturally involve physical, metaphysical and behavioral actions of the self and the others. The third and probably the most complicated problem is the scientific identification and the authentication of the deity. This not only provides the whole power and control over the choosers to set their life orders but also to establish perfect physical and metaphysical links as fully coordinated functional energy network. This thus indicates that choosing an authentic deity is the key-point that influences automated, emotional, and behavioral actions altogether, which shapes human perception, personal actions, and life orders. Therefore, we will be considering the existing ‘four types of energy wave end boundary behaviors’, comprising, free end, fixed end boundary behaviors, as well as boundary behaviors from denser medium to less dense medium and from less dense medium to denser medium. Consequently, this article aims to demonstrate that the authentication and the choice of deity has an important effect on individual psychological, biological and social health. It is hoped that it will encourage new researches in the field of authentic energy network connections to establish the best position and the most correct interrelation connections with self and others without violating the authorized orders and the borders of one another to live happier and healthier lives together. In addition, the book ‘Deity and Freedom, Equality, Justice in History, Philosophy, Science’ has more detailed information for those interested in this subject.

Keywords: deity, energy network, power, freedom, equality, justice, happiness, sadness, hope, fear, psychology, biology, sociology

Procedia PDF Downloads 346

Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

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The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

Procedia PDF Downloads 118

Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

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Urban water infrastructure is crucial for efficient and reliable water supply in growing cities. With the growth of cities, the need for maintenance and renewal of these systems increases but often goes unfulfilled due to a variety of reasons, such as limited funding, political priorities, or lack of public awareness. Neglecting the renewal needs of these systems can lead to frequent malfunctions and reduced quality and reliability of water supply, as well as increased costs and health and environmental hazards. It is important for cities to prioritize investment in water infrastructure and develop long-term plans to address renewal needs. Drawing general conclusions about the rate of renewal of urban water infrastructure systems at an international or national level can be challenging due to the influence of local management decisions. In many countries, the responsibility for water infrastructure management lies with the municipal authorities, who are responsible for making decisions about the allocation of resources for repair, maintenance, and renewal. These decisions can vary widely based on factors such as local finances, political priorities, and public perception of the importance of water infrastructure. As a result, it is difficult to make generalizations about the rate of renewal across different countries or regions. In Sweden, the situation is not different, and the information from Svenskt Vatten indicates that the rate of renewal varies across municipalities and can be insufficient, leading to a buildup of maintenance and renewal needs. This study aims to examine the adequacy of the rate of renewal of urban water infrastructure in Linköping case city in Sweden. Using a case study framework, the study will assess the current status of the urban water system and the need for renewal. The study will also consider the role of factors such as proper identification processes, limited funding, competing for political priorities, and local management decisions in contributing to insufficient renewal. The study investigates the following questions: (1) What is the current status of water and sewerage networks in terms of length, age distribution, and material composition, estimated total water leakage in the network per year, damages, leaks, and outages occur per year, both overall and by district? (2) What are the main causes of these damages, leaks, and interruptions, and how are they related to lack of maintenance and renewal? (3) What is the current status of renewal work for the water and sewerage networks, including the renewal rate and changes over time, recent renewal material composition, and the budget allocation for renewal and emergency repairs? (4) What factors influence the need for renewal and what conditions should be considered in the assessment? The findings of the study provide insights into the challenges facing urban water infrastructure and identify strategies for improving the rate of renewal to ensure a reliable and sustainable water supply.

Keywords: case study, infrastructure, management, renewal need, Sweden

Procedia PDF Downloads 103

Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

Procedia PDF Downloads 203

Authors: F. DelGaudio, H. Gill

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Resuscitation during cardiopulmonary (CPA) arrest is dynamic, high stress, high acuity situation, which can easily lead to communication breakdown, and errors. The care of these high acuity patients has also been shown to increase physiologic stress and task saturation of providers, which can negatively impact the care being provided. These difficulties are further complicated during a global pandemic and pose a significant safety risk to bedside providers. Nurse-led codes are a relatively new concept that may be a potential solution for alleviating some of these difficulties. An experienced nurse who has completed advanced cardiac life support (ACLS), and additional training, assumed the responsibility of directing the mechanics of the appropriate ACLS algorithm. This was done in conjunction with a physician who also acted as a physician leader. The additional nurse-led code training included a multi-disciplinary in situ simulation of a CPA on a suspected COVID-19 patient. During the CPA, the nurse leader’s responsibilities include: ensuring adequate compression depth and rate, minimizing interruptions in chest compressions, the timing of rhythm/pulse checks, and appropriate medication administration. In addition, the nurse leader also functions as a last line safety check for appropriate personal protective equipment and limiting exposure of staff. The use of nurse-led codes for CPA has shown to decrease the cognitive overload and task saturation for the physician, as well as limiting the number of staff being exposed to a potentially infectious patient. The real-world application has allowed physicians to perform and oversee high-risk procedures such as intubation, line placement, and point of care ultrasound, without sacrificing the integrity of the resuscitation. Nurse-led codes have also given the physician the bandwidth to review pertinent medical history, advanced directives, determine reversible causes, and have the end of life conversations with family. While there is a paucity of research on the effectiveness of nurse-led codes, there are many potentially significant benefits. In addition to its value during a pandemic, it may also be beneficial during complex circumstances such as extracorporeal cardiopulmonary resuscitation.

Keywords: cardiopulmonary arrest, COVID-19, nurse-led code, task saturation

Procedia PDF Downloads 155

Authors: Thaís T. Valério Caetano, Lívia de Carvalho Ferreira, João Máximo De Siqueira, Carlos Alexandre Carollo, Arthur Ladeira Macedo, Vanessa C. Stein

Abstract:

Nicotiana glauca, commonly known as wild tobacco or tobacco bush, belongs to the Solanaceae family. It is native to South America but has become naturalized in various regions, including Australia, California, Africa, and the Mediterranean. N. glauca is listed in the Global Invasive Species Database (GISD) and the Invasive Species Compendium (CABI). It is known for producing pyridine alkaloids, including anabasine, which is highly toxic. Anabasine is predominantly found in the leaves and can cause severe health issues such as neuromuscular blockade, respiratory arrest, and cardiovascular problems when ingested. Mistaken identity with edible plants like spinach has resulted in food poisoning cases in Israel and Brazil. Anabasine, a minor alkaloid constituent of tobacco, may contribute to tobacco addiction by mimicking or enhancing the effects of nicotine. Therefore, it is essential to investigate the production pattern of anabasine and its relationship to the developmental stages of the plant. This study aimed to establish the relationship between the phenological plant age, cultivation place, and the increase in anabasine concentration, which can lead to human intoxication cases. In this study, N. glauca plants were collected from three different rural areas in Brazil during a year to examine leaves at various stages of development. Samples were also obtained from cultivated plants in Marilândia, Minas Gerais, Brazil, as well as from Divinópolis, Minas Gerais, Brazil, and Arraial do Cabo, Rio de Janeiro, Brazil. In vitro cultivated plants on MS medium were included in the study. The collected leaves were dried, powdered, and stored. Alkaloid extraction was performed using a methanol and water mixture, followed by liquid-liquid extraction with chloroform. The anabasine content was determined using HPLC-DAD analysis with nicotine as a standard. The results indicated that anabasine production increases with the plant's development, peaking in adult leaves during the reproduction phase and declining afterward. In vitro, plants showed similar anabasine production to young leaves. The successful adaptation of N. glauca in new environments poses a global problem, and the correlation between anabasine production and the plant's developmental stages has been understudied. The presence of substances produced by the plant can pose a risk to other species, especially when mistaken for edible plants. The findings from this study shed light on the pattern of anabasine production and its association with plant development, contributing to a better understanding of the potential risks associated with N. glauca and the importance of accurate identification.

Keywords: alkaloid production, invasive species, nicotiana glauca, plant phenology

Procedia PDF Downloads 83

Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 266

Authors: Gunta Resevica, Nikita Zrelovs, Ivars Silamikelis, Ieva Kalnciema, Helvijs Niedra, Gunārs Lācis, Toms Bartulsons, Inga Moročko-Bičevska, Arturs Stalažs, Kristīne Drevinska, Andris Zeltins, Ina Balke

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Newly discovered viruses provide novel knowledge for basic phytovirus research, serve as tools for biotechnology and can be helpful in identification of epidemic outbreaks. Blackcurrant-associated rhabdovirus (BCaRV) have been discovered in USA germplasm collection samples from Russia and France. As it was reported in one accession originating from France it is unclear whether the material was already infected when it entered in the USA or it became infected while in collection in the USA. Due to that BCaRV was definite as non-EU viruses. According to ICTV classification BCaRV is representative of Blackcurrant betanucleorhabdovirus specie in genus Betanucleorhabdovirus (family Rhabdoviridae). Nevertheless, BCaRV impact on the host, transmission mechanisms and vectors are still unknown. In RNA-seq data pool from Ribes plants resistance gene study by high throughput sequencing (HTS) we observed differences between sample group gene transcript heat maps. Additional analysis of the whole data pool (total 393660492 of 150 bp long read pairs) by rnaSPAdes v 3.13.1 resulted into 14424 bases long contig with an average coverage of 684x with shared 99.5% identity to the previously reported first complete genome of BCaRV (MF543022.1) using EMBOSS Needle. This finding proved BCaRV presence in EU and indicated that it might be relevant pathogen. In this study leaf tissue from twelve asymptomatic blackcurrant cv. Mara Eglite plants (negatively tested for blackcurrant reversion virus (BRV)) from Dobele, Latvia (56°36'31.9"N, 23°18'13.6"E) was collected and used for total RNA isolation with RNeasy Plant Mini Kit with minor modifications, followed by plant rRNA removal by a RiboMinus Plant Kit for RNA-Seq. HTS libraries were prepared using MGI Easy RNA Directional Library Prep Set for 16 reactions to obtain 150 bp pair-end reads. Libraries were pooled, circularized and cleaned and sequenced on DNBSEQ-G400 using PE150 flow cell. Additionally, all samples were tested by RT-PCR, and amplicons were directly sequenced by Sanger-based method. The contig representing the genome of BCaRV isolate Mara Eglite was deposited at European Nucleotide Archive under accession number OU015520. Those findings indicate a second evidence on the presence of this particular virus in the EU and further research on BCaRV prevalence in Ribes from other geographical areas should be performed. As there are no information on BCaRV impact on the host this should be investigated, regarding the fact that mixed infections with BRV and nucleorhabdoviruses are reported.

Keywords: BCaRV, Betanucleorhabdovirus, Ribes, RNA-seq

Procedia PDF Downloads 184

Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 112

Authors: Malek Miladi, Miguel Vegara, Maria Perez-Infantes, Khaled Mohamed Ramadan, Antonio Ruiz-Canales, Damaris Nunez-Gomez

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Coffee is the second consumed commodity worldwide, yet it also generates colossal waste. Proper management of coffee waste is proposed by converting them into products with higher added value to achieve sustainability of the economic and ecological footprint and protect the environment. Based on this, a study looking at the recovery of coffee waste is becoming more relevant in recent decades. Spent coffee grounds (SCG's) resulted from brewing coffee represents the major waste produced among all coffee industry. The fact that SCGs has no economic value be abundant in nature and industry, do not compete with agriculture and especially its high oil content (between 7-15% from its total dry matter weight depending on the coffee varieties, Arabica or Robusta), encourages its use as a sustainable feedstock for bio-oil production. The bio-oil extraction is a crucial step towards biodiesel production by the transesterification process. However, conventional methods used for oil extraction are not recommended due to their high consumption of energy, time, and generation of toxic volatile organic solvents. Thus, finding a sustainable, economical, and efficient extraction technique is crucial to scale up the process and to ensure more environment-friendly production. Under this perspective, the aim of this work was the statistical study to know an efficient strategy for oil extraction by n-hexane using indirect sonication. The coffee waste mixed Arabica and Robusta, which was used in this work. The temperature effect, sonication time, and solvent-to-solid ratio on the oil yield were statistically investigated as dependent variables by Central Composite Rotatable Design (CCRD) 23. The results were analyzed using STATISTICA 7 StatSoft software. The CCRD showed the significance of all the variables tested (P < 0.05) on the process output. The validation of the model by analysis of variance (ANOVA) showed good adjustment for the results obtained for a 95% confidence interval, and also, the predicted values graph vs. experimental values confirmed the satisfactory correlation between the model results. Besides, the identification of the optimum experimental conditions was based on the study of the surface response graphs (2-D and 3-D) and the critical statistical values. Based on the CCDR results, 29 ºC, 56.6 min, and solvent-to-solid ratio 16 were the better experimental conditions defined statistically for coffee waste oil extraction using n-hexane as solvent. In these conditions, the oil yield was >9% in all cases. The results confirmed the efficiency of using an ultrasound bath in extracting oil as a more economical, green, and efficient way when compared to the Soxhlet method.

Keywords: coffee waste, optimization, oil yield, statistical planning

Procedia PDF Downloads 119

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 201

Authors: Robby Y. Tallar, Nikodemus L., Yuri S., Jian P. Suen

Abstract:

Research in the subject of ecological water resources management is full of trivial questions addressed and it seems, today to be one branch of science that can strongly contribute to the study of complexity (physical, biological, ecological, socio-economic, environmental, and other aspects). Existing literature available on different facets of these studies, much of it is technical and targeted for specific users. This study offered the combination all aspects in evaluation methodology for aquaculture lakes with its paradigm refer to hierarchical theory and to the effects of spatial specific arrangement of an object into a space or local area. Therefore, the process in developing a conceptual framework represents the more integrated and related applicable concept from the grounded theory. A design of integrated evaluation methodology for aquaculture lakes is presented. The method is based on the identification of a series of attributes which can be used to describe status of aquaculture lakes using certain indicators from aquaculture water quality index (AWQI), aesthetic aquaculture lake index (AALI) and rapid appraisal for fisheries index (RAPFISH). The preliminary preparation could be accomplished as follows: first, the characterization of study area was undertaken at different spatial scales. Second, an inventory data as a core resource such as city master plan, water quality reports from environmental agency, and related government regulations. Third, ground-checking survey should be completed to validate the on-site condition of study area. In order to design an integrated evaluation methodology for aquaculture lakes, finally we integrated and developed rating scores system which called Integrated Aquaculture Lake Index (IALI).The development of IALI are reflecting a compromise all aspects and it responds the needs of concise information about the current status of aquaculture lakes by the comprehensive approach. IALI was elaborated as a decision aid tool for stakeholders to evaluate the impact and contribution of anthropogenic activities on the aquaculture lake’s environment. The conclusion was while there is no denying the fact that the aquaculture lakes are under great threat from the pressure of the increasing human activities, one must realize that no evaluation methodology for aquaculture lakes can succeed by keeping the pristine condition. The IALI developed in this work can be used as an effective, low-cost evaluation methodology of aquaculture lakes for developing countries. Because IALI emphasizes the simplicity and understandability as it must communicate to decision makers and the experts. Moreover, stakeholders need to be helped to perceive their lakes so that sites can be accepted and valued by local people. For this site of lake development, accessibility and planning designation of the site is of decisive importance: the local people want to know whether the lake condition is safe or whether it can be used.

Keywords: aesthetic value, AHP, aquaculture lakes, integrated lakes, RAPFISH

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