Search results for: plant detection

Authors: S: Kayesth, K. K. Gupta

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The indiscriminate use of insecticides causes environmental contamination, adversely affects non-target organisms and develops resistance among insects and pests. There has always been felt a need for methods of control which can overcome these environmental and other ecological issues. The present study was designed to evaluate the effect of different plants volatiles on survival, longevity, growth, development and reproduction of Dysdercus koenigii. The hexane extract of three different plants (Catharanthus roseus, Ocimum sanctum and Lantana camara) was used. The fifth instars were exposed to hexane extract with concentrations of 10%, 5%, 2.5%, 1.25%, 0.1%, 0.5%, 0.25%, 0.13% and 0.06% while adults were treated with 10%, 5%, 2.5% and 1.25%. 1-ml of each of these concentrations was used to make a thin film in sterilized glass jars of 500 ml capacity. Fifteen newly emerged fifth instar nymphs and ten pairs of adult bugs were treated separately with the extracts for 24 hour exposure to the plant volatiles. The effect of these plant extract was observed and readings were recorded for 23 days. Survival and longevity of both fifth instars and adults were in correlation with the concentrations of the plant extracts. The extracts did not influence growth of fifth instars significantly but impaired their development significantly at higher concentrations. The treated nymphs at higher concentrations either could not moult or died and those which could moult moulted into supranumery instars, adultoids or adults with wing deformities. The supranumery insects retained the nymphal characters except increased body size and wing pads. The adultoids had wing deformities and non-functional reproductive organs. Adultoids exhibited courtship and mounting attempts but were not able to mate. At lower concentrations from 0.1 to 0.06% the fifth instars developed into adults with fewer deformities. At these concentrations, the fecundity and fertility of these adults were drastically reduced. On the contrary, the treated adults also had reduced fecundity and fertility compared to control. Among three plant extracts Ocimcum was most toxic for both fifth instars and adults in terms of survival and longevity. Catharanthus, Ocimum and Lantana appeared to have potential molecules which possessed insect juvenile hormone like activity. Potential application of these plant extracts in IPM was discussed.

Keywords: Catharanthus, Ocimum, Lantana, Dysdercus koenigii

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Authors: P. Tanuska, A. Elias, P. Vazan, B. Zahradnikova

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This article describes the information system for measuring and evaluating the dose rate in the environment of nuclear power plants Mochovce and Bohunice in Slovakia. The article presents the results achieved in the implementation of the EU project–Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants. The objectives included improving the system of acquisition, measuring and evaluating data with mobile and autonomous units applying new knowledge from research. The article provides basic and specific features of the system and compared to the previous version of the system, also new functions.

Keywords: information system, dose rate, mobile devices, nuclear power plant

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Authors: Kien Xuan Ngo

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Cassiicolin (Cas), a toxin produced by Corynespora cassiicola, is responsible for corynespora leaf fall (CLF) disease in rubber trees. Currently, the molecular mechanism of the cytotoxicity of Cas isoforms (i.e., Cas1, Cas2) on rubber leaves and its host selectivity have not been fully elucidated. This study analyzed the binding of Cas1 and Cas2 to membranes consisting of different plant lipids and their membrane-disruption activities. Using high-speed atomic force microscopy and confocal microscopy, this study reveals that the binding and disruption activities of Cas1 and Cas2 on lipid membranes are strongly dependent on the specific plant lipids. The negative phospholipids, glycerolipids, and sterols are more susceptible to membrane damage caused by Cas1 and Cas2 than neutral phospholipids and betaine lipids. In summary, This study unveils that (i) Cas1 and Cas2 directly damage and cause necrosis in the leaves of specific rubber clones; (ii) Cas1 and Cas2 can form biofilm-like structures on specific lipid membranes (negative phospholipids, glycerolipids, and sterols). The biofilm-like formation of Cas toxin plays an important role in selective disruption on lipid membranes; (iii) Vulnerability of the specific cytoplasmic membranes to the selective Cas toxin is the most remarkable feature of cytotoxicity of Cas toxin on plant cells. Finally, researcher’s exploration is crucial to understand the basic molecular mechanism underlying the host-selective toxic interaction of Cas toxin with cytoplasmic membranes in plant cells.

Keywords: cassiicolin, corynespora leaf fall disease, high-speed AFM, giant liposome vesicles

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Authors: Staņislavs Gendelis, Andris Jakovičs, Jānis Ratnieks, Aigars Laizāns, Dāvids Vardanjans

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Dehumidification of biogas at the biomass plants is very important to provide the energy efficient burning of biomethane at the outlet. A few methods are widely used to reduce the water content in biogas, e.g. chiller/heat exchanger based cooling, usage of different adsorbents like PSA, or the combination of such approaches. A quite different method of biogas dehumidification is offered and analyzed in this paper. The main idea is to direct the flow of biogas from the plant around it downwards; thus, creating additional insulation layer. As the temperature in gas shell layer around the plant will decrease from ~ 38°C to 20°C in the summer or even to 0°C in the winter, condensation of water vapor occurs. The water from the bottom of the gas shell can be collected and drain away. In addition, another upward shell layer is created after the condensate drainage place on the outer side to further reducing heat losses. Thus, counterflow biogas heat exchanger is created around the biogas plant. This research work deals with the numerical modelling of biogas flow, taking into account heat exchange and condensation on cold surfaces. Different kinds of boundary conditions (air and ground temperatures in summer/winter) and various physical properties of constructions (insulation between layers, wall thickness) are included in the model to make it more general and useful for different biogas flow conditions. The complexity of this problem is fact, that the temperatures in both channels are conjugated in case of low thermal resistance between layers. MATLAB programming language is used for multiphysical model development, numerical calculations and result visualization. Experimental installation of a biogas plant’s vertical wall with an additional 2 layers of polycarbonate sheets with the controlled gas flow was set up to verify the modelling results. Gas flow at inlet/outlet, temperatures between the layers and humidity were controlled and measured during a number of experiments. Good correlation with modelling results for vertical wall section allows using of developed numerical model for an estimation of parameters for the whole biogas dehumidification system. Numerical modelling of biogas counterflow heat exchanger system placed on the plant’s wall for various cases allows optimizing of thickness for gas layers and insulation layer to ensure necessary dehumidification of the gas under different climatic conditions. Modelling of system’s defined configuration with known conditions helps to predict the temperature and humidity content of the biogas at the outlet.

Keywords: biogas dehumidification, numerical modelling, condensation, biogas plant experimental model

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Daniela Nedeltcheva-Antonova, Kamelia Getchovska, Vera Deneva, Stanislav Bozhanov, Liudmil Antonov

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Rosa damascena Mill. (Damask rose) is one of the most important plants belonging to the Rosaceae family, with a long historical use in traditional medicine and as a valuable oil-bearing plant. Many pharmacological effects have been reported from this plant, including anti-inflammatory, hypnotic, analgesic, anticonvulsant, anti-depressant, antianxiety, antitussive, antidiabetic, relaxant effects on tracheal chains, laxative, prokinetic and hepatoprotective activities. Pharmacological studies have shown that the various health effects of R. damascena flowers can mainly be attributed to its large amount of polyphenolic components. Phenolics possess a wide range of pharmacological activities, such as antioxidants, free-radical scavengers, anticancer, anti-inflammatory, antimutagenic, and antidepressant, with flavonoids being the most numerous group of natural polyphenolic compounds. According to the technological process in the production of rose concrete (solvent extraction with non-polar solvents of fresh rose flowers), it can be assumed that the resulting plant residue would be as rich of polyphenolics, as the plant itself, and could be used for the development of novel products with promising health-promoting effect. Therefore, an optimisation of the extraction procedure of the by-product from the rose concrete production was carried out. An assay of the extracts in respect of their total polyphenols and total flavonoids content was performed. HPLC analysis of quercetin and kaempferol, the two main flavonoids found in R. damascena, was also carried out. The preliminary results have shown that the flavonoid content in the rose extracts is comparable to that of the green tea or Gingko biloba, and they could be used for the development of various products (food supplements, natural cosmetics and phyto-pharmaceutical formulation, etc.). The fact that they are derived from the by-product of industrial plant processing could add the marketing value of the final products in addition to the well-known reputation of the products obtained from Bulgarian roses (R. damascena Mill.).

Keywords: gas chromatography-mass-spectromrtry, dry extract, flavonoids, Rosa damascena Mill

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Authors: Kadi-Hanifi Halima, Amghar Fateh

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Steppes of arid Mediterranean zones are deeply threatened by desertification. To stop or alleviate ecological and economic problems associated with this desertification, management actions have been implemented since the last three decades. The struggle against desertification has become a national priority in many countries. In Algeria, several management techniques have been used to cope with desertification. This study aims at investigating the effect of exclosure on floristic diversity and chemical soil properties after four years of implementation. 167 phyto-ecological samples have been studied, 122 inside the exclosure and 45 outside. Results showed that plant diversity, composition, vegetation cover, pastoral value and soil fertility were significantly higher in protected areas.

Keywords: desertification, arid, pastoral management, plant community soil fertility, gestation of environment, Algeria

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Authors: Bonginkosi A. Thango, Jacobus A. Jordaan, Agha F. Nnachi

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In this day and age, there is a proliferate concern from all governments across the globe to barricade the environment from greenhouse gases, which absorb infrared radiation. As a result, solar photovoltaic (PV) electricity has been an expeditiously growing renewable energy source and will eventually undertake a prominent role in the global energy generation. The selection and purchasing of energy-efficient transformers that meet the operational requirements of the solar photovoltaic energy generation plants then become a part of the Independent Power Producers (IPP’s) investment plan of action. Taking these into account, this paper proposes a procedure that put into effect the intricate financial analysis necessitated to precisely evaluate the transformer service lifetime no-load and load loss factors. This procedure correctly set forth the transformer service lifetime loss factors as a result of a solar PV plant’s sporadic generation profile and related levelized costs of electricity into the computation of the transformer’s total ownership cost. The results are then critically compared with the conventional transformer total ownership cost unaccompanied by the emission costs, and demonstrate the significance of the sporadic energy generation nature of the solar PV plant on the total ownership cost. The findings indicate that the latter play a crucial role for developers and Independent Power Producers (IPP’s) in making the purchase decision during a tender bid where competing offers from different transformer manufactures are evaluated. Additionally, the susceptibility analysis of different factors engrossed in the transformer service lifetime cost is carried out; factors including the levelized cost of electricity, solar PV plant’s generation modes, and the loading profile are examined.

Keywords: solar photovoltaic plant, transformer, total ownership cost, loss factors

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Authors: C. Shih, J. R. Wang, H. C. Chang, S. W. Chen, S. C. Chiang, T. Y. Yu

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After the measurement uncertainty recapture (MUR) power uprates, Kuosheng nuclear power plant (NPP) was uprated the power from 2894 MWt to 2943 MWt. For power upgrade, several codes (e.g., TRACE, RELAP5, etc.) were applied to assess the safety of Kuosheng NPP. Hence, the main work of this research is to establish a RELAP5/MOD3.3 model of Kuosheng NPP with SNAP interface. The establishment of RELAP5/SNAP model was referred to the FSAR, training documents, and TRACE model which has been developed and verified before. After completing the model establishment, the startup test scenarios would be applied to the RELAP5/SNAP model. With comparing the startup test data and TRACE analysis results, the applicability of RELAP5/SNAP model would be assessed.

Keywords: RELAP5, TRACE, SNAP, BWR

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Authors: Gramza-Michalowska Anna, Skrety Joanna, Kobus-Cisowska Joanna, Kmiecik Dominik, Korczak Jozef, Anna Zywica

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Background: Recent research presented many evidences confirming that food besides its basic nutritional function, possess significant therapeutic and prophylactic potential. Conscious consumer is aware of diet habits and well being lifestyle influencing a proper functioning that is why there is a need of new pro-health products. Objective: Proposition of the technology of unsweetened almond drinks enriched with plant extracts for pro-health oriented individuals. Research investigated the influence of selected plant extracts addition on antioxidative activity and consumer’s acceptance of drinks as all day diet product representatives. Methods: The analysis of the basic composition and antioxidant properties of the almond drink was conducted. Research included analysis of basic composition (protein, lipids and fiber content) and antioxidant capacity of drink (DPPH, ABTS, ORAC value, and FRAP). Proposed drink was also characterized with sensory analysis, including color, aroma, taste, consistency, and overall acceptance. Results: Results showed that addition of plant extracts into an almond drink allowed to improve its antioxidant capacity and sensory value of the drinks. Profitable composition and pro-health properties of designed drink permits offering healthy product for all day consumption. Conclusion: Designed almond drink would be a significant supplement for pro-healthy life style of the consumers. Results showed that plant extracts enriched almond drink would be a good source of antioxidants and accepted by the consumers.

Keywords: phytonutrients, pro-health, almond, wellbeing, antioxidant potential, sensory value

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Authors: J. R. Wang, H. T. Lin, Y. Chiang, H. C. Chen, C. Shih

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Kuosheng Nuclear Power Plant (NPP) is located on the northern coast of Taiwan. Its nuclear steam supply system is a type of BWR/6 designed and built by General Electric on a twin unit concept. First, the methodology of Kuosheng NPP SPU (Stretch Power Uprate) safety analysis TRACE/SNAP model was developed in this research. Then, in order to estimate the safety of Kuosheng NPP under the more severe condition, the SBO (Station Blackout) + LOCA (Loss-of-Coolant Accident) transient analysis of Kuosheng NPP SPU TRACE/SNAP model was performed. Besides, the animation model of Kuosheng NPP was presented using the animation function of SNAP with TRACE/SNAP analysis results.

Keywords: TRACE, safety analysis, BWR/6, severe accident

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Authors: Chandra Prayaga, Lakshmi Prayaga, Aaron Wade, Kyle Rank, Gopi Shankar Mallu, Sri Satya, Harsha Pola

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In today's tech-driven world, where connectivity shapes our daily lives, maintaining physical and emotional health is crucial. Athletic trainers play a vital role in optimizing athletes' performance and preventing injuries. However, a shortage of trainers impacts the quality of care. This study introduces a vision-based exercise monitoring system leveraging Google's MediaPipe library for precise tracking of bicep curl exercises and simultaneous posture monitoring. We propose a three-stage methodology: landmark detection, side detection, and angle computation. Our system calculates angles at the elbow, wrist, neck, and torso to assess exercise form. Experimental results demonstrate the system's effectiveness in distinguishing between good and partial repetitions and evaluating body posture during exercises, providing real-time feedback for precise fitness monitoring.

Keywords: physical health, athletic trainers, fitness monitoring, technology driven solutions, Google’s MediaPipe, landmark detection, angle computation, real-time feedback

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Authors: Endang Lukitaningsih, Fathul Jannah, Arief R. Hakim, Ratna D. Puspita, Zullies Ikawati

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Rifampicin is a semisynthetic antibiotic derivative of rifamycin B produced by Streptomyces mediterranei. RIF has been used worldwide as first line drug-prescribed throughout tuberculosis therapy. This study aims to develop and to validate an HPLC method couple with a UV detection for determination of rifampicin in spiked human plasma and its application for bioequivalence study. The chromatographic separation was achieved on an RP-C18 column (LachromHitachi, 250 x 4.6 mm., 5μm), utilizing a mobile phase of phosphate buffer/acetonitrile (55:45, v/v, pH 6.8 ± 0.1) at a flow of 1.5 mL/min. Detection was carried out at 337 nm by using spectrophotometer. The developed method was statistically validated for the linearity, accuracy, limit of detection, limit of quantitation, precise and specifity. The specifity of the method was ascertained by comparing chromatograms of blank plasma and plasma containing rifampicin; the matrix and rifampicin were well separated. The limit of detection and limit of quantification were 0.7 µg/mL and 2.3 µg/mL, respectively. The regression curve of standard was linear (r > 0.999) over a range concentration of 20.0 – 100.0 µg/mL. The mean recovery of the method was 96.68 ± 8.06 %. Both intraday and interday precision data showed reproducibility (R.S.D. 2.98% and 1.13 %, respectively). Therefore, the method can be used for routine analysis of rifampicin in human plasma and in bioequivalence study. The validated method was successfully applied in pharmacokinetic and bioequivalence study of rifampicin tablet in a limited number of subjects (under an Ethical Clearance No. KE/FK/6201/EC/2015). The mean values of Cmax, Tmax, AUC(0-24) and AUC(o-∞) for the test formulation of rifampicin were 5.81 ± 0.88 µg/mL, 1.25 hour, 29.16 ± 4.05 µg/mL. h. and 29.41 ± 4.07 µg/mL. h., respectively. Meanwhile for the reference formulation, the values were 5.04 ± 0.54 µg/mL, 1.31 hour, 27.20 ± 3.98 µg/mL.h. and 27.49 ± 4.01 µg/mL.h. From bioequivalence study, the 90% CIs for the test formulation/reference formulation ratio for the logarithmic transformations of Cmax and AUC(0-24) were 97.96-129.48% and 99.13-120.02%, respectively. According to the bioequivamence test guidelines of the European Commission-European Medicines Agency, it can be concluded that the test formulation of rifampicin is bioequivalence with the reference formulation.

Keywords: validation, HPLC, plasma, bioequivalence

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Hamid Mohammadi, S. H. Eftekhar Afzali

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The irregular usage of chemical fertilizer cause different types of water and soil pollution and problems in health of human in past decades and organic fertilizer has been considered more and more. Mycorrhizal fungi have symbiosis with plant families and significantly effect on plant growth. Proper management of these symbiosis causes to reduce the usage of chemical fertilizers and absorb nutrition especially phosphor. Pistacia vera is endemic in Iran and is one of the most important products for this country. Considering special circumstances of pistachio orchards according to increasing salinity of water and soil and mismanagement of fertilizer reveals the necessity of the usage of Mycorrhizal fungi in these orchards.

Keywords: pistachio, mycorhiza, nutrition, salinity

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Serkan Solmaz, Jean-Baptiste Gouriet, Nicolas Van de Wyer, Christophe Schram

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Efficiency of the cooling process for cryogenic propellant boiling in engine cooling channels on space applications is relentlessly affected by the phase change occurs during the boiling. The effectiveness of the cooling process strongly pertains to the type of the boiling regime such as nucleate and film. Geometric constraints like a non-transparent cooling channel unable to use any of visualization methods. The ultrasonic (US) technique as a non-destructive method (NDT) has therefore been applied almost in every engineering field for different purposes. Basically, the discontinuities emerge between mediums like boundaries among different phases. The sound wave emitted by the US transducer is both transmitted and reflected through a gas-liquid interface which makes able to detect different phases. Due to the thermal and structural concerns, it is impractical to sustain a direct contact between the US transducer and working fluid. Hence the transducer should be located outside of the cooling channel which results in additional interfaces and creates ambiguities on the applicability of the present method. In this work, an exploratory research is prompted so as to determine detection ability and applicability of the US technique on the cryogenic boiling process for a cooling cycle where the US transducer is taken place outside of the channel. Boiling of the cryogenics is a complex phenomenon which mainly brings several hindrances for experimental protocol because of thermal properties. Thus substitute materials are purposefully selected based on such parameters to simplify experiments. Aside from that, nucleate and film boiling regimes emerging during the boiling process are simply simulated using non-deformable stainless steel balls, air-bubble injection apparatuses and air clearances instead of conducting a real-time boiling process. A versatile detection algorithm is perennially developed concerning exploratory studies afterward. According to the algorithm developed, the phases can be distinguished 99% as no-phase, air-bubble, and air-film presences. The results show the detection ability and applicability of the US technique for an exploratory purpose.

Keywords: Ultrasound, ultrasonic, multiphase flow, boiling, cryogenics, detection algorithm

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Authors: Krasimir I. Ivanov, Penka S. Zapryanova, Stefan V. Krustev, Violina R. Angelova

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Three commonly used digestion methods (dry ashing, acid digestion, and microwave digestion) in different variants were compared for digestion of tobacco leaves. Three main macroelements (K, Ca and Mg) were analysed using AAS Spectrometer Spectra АА 220, Varian, Australia. The accuracy and precision of the measurements were evaluated by using Polish reference material CTR-VTL-2 (Virginia tobacco leaves). To elucidate the problems with elemental recovery X-Ray and SEM–EDS analysis of all residues after digestion were performed. The X-ray investigation showed a formation of KClO₄ when HClO4 was used as a part of the acids mixture. The use of HF at Ca and Mg determination led to the formation of CaF₂ and MgF₂. The results were confirmed by energy dispersive X-ray microanalysis. SPSS program for Windows was used for statistical data processing.

Keywords: digestion methods, plant tissue, determination of macroelements, K, Ca, Mg

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Authors: S. Yussuf Abdulmaliq

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Experiment was conducted for two years (2013 and 2014) at Ibrahim Badamasi Babangida University, Lapai, Teaching and Research Farm to study the effects of soil organic amendment types and rates on soil chemical fertility improvement, growth and yield of Amarathus cruentus in the southern guinea savannah, lapai, Niger state, Nigeria. Soil and manure samples were collected and analysed for physical and chemical components. The experiments were laid out in 3 x 4 factorial in a randomized complete block design (RCBD). Consisting of three (3) levels of soil amendment types (Poultry manure, goat manure and cowdung) and four (4) levels of amendment rates (0, 6, 12 and 18 t ha-1). Data collected include plant height/plant (cm), number of leaves/plant, leaf area/ plant (cm2) at 2, 4, 6 and 8WAT, fresh vegetable yield/plant, fresh vegetable yield/plot and fresh vegetable yield in tons ha-1. The result obtained showed that, Amaranthus cruentus height, number of leaves and leaf area were not significantly affected by the type of organic amendment and rates at 2WAT in 2013 and 2014 cropping seasons. However, at 4, 6 and 8 WAT, significant differences were observed among the types of amendment and their rates. Application of poultry manure as soil amendment supported taller, large number of leaves and wider leaf area, and higher marketable vegetable yield in 2013 and 2014 cropping seasons (Pα 0.05) which was closely followed by goat manure in the two (2) cropping seasons. In addition, the application of 18 t ha-1 was superior to 12, 6 and the control by producing tallest amaranthus plants, higher number of leaves, wider leaf area and higher marketable vegetable yield in 2013 and 2014 cropping seasons (Pα 0.05). In conclusion, the use of 18 t ha-1poultry manure is therefore recommended as soil amendment for Amaranthus cruentus in southern guinea savannah of Nigeria.

Keywords: Amaranthus cruentus, cowdung, goat manure, poultry manure, soil amendment

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Authors: Debatosh Das, Moxian Chen, Jianhua Zhang, Caroline Gutjahr

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Arbuscular mycorrhiza (AM) is a mutualistic symbiosis between plant roots and Glomeromycotina fungi, which is activated under low but inhibited by high phosphate. The effect of phosphate on AM development has been observed for many years, but mechanisms regulating it under contrasting phosphate levels remain unknown. Based on previous observations that promoters of several AM functional genes contain PHR binding motifs, we hypothesized that PHR2, a master regulator of phosphate starvation response in rice, was recruited to regulate AM symbiosis development. We observed a drastic reduction in root colonization and significant AM transcriptome modulation in phr2. PHR2 targets genes required for root colonization and AM signaling. The role of PHR2 in improving root colonization, mycorrhizal phosphate uptake, and growth response was confirmed in field soil. In conclusion, rice PHR2, which is considered a master regulator of phosphate starvation responses, acts as a positive regulator of AM symbiosis between Glomeromycotina fungi and rice roots. PHR2 directly targets the transcription of plant strigolactone and AM genes involved in the establishment of this symbiosis. Our work facilitates an understanding of ways to enhance AMF propagule populations introduced in field soils (as a biofertilizer) in order to restore the natural plant-AMF networks disrupted by modern agricultural practices. We show that PHR2 is required for AM-mediated improvement of rice yield in low phosphate paddy field soil. Thus, our work contributes knowledge for rational application of AM in sustainable agriculture. Our data provide important insights into the regulation of AM by the plant phosphate status, which has a broad significance in agriculture and terrestrial ecosystems.

Keywords: biofertilizer, phosphate, mycorrhiza, rice, sustainable, symbiosis

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Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

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Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Ravi R. Patel, Vasudev R. Thakkar

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Use of plant growth-promoting rhizobacteria (PGPR) to increase the production and decrees disease occurrence is a recent method in agriculture. An RA2 rhizospheric culture was isolated from peanut rhizosphere from Junagadh region of Gujarat, India and showed different direct and indirect plant growth promoting activity like indole acetic acid, gibberellic acid, siderophore, hydrogen cyanide, Ammonia and (1-Aminocyclopropane-1-Carboxylate) deaminase production, N2 fixation, phosphate and potassium solubilization in vitro. RA2 was able to protect peanut germinating seedling from A. niger infection and reduce collar rot disease incidence 60-35% to 72-41% and increase germination percentage from 70-82% to 75-97% in two varieties GG20 and GG2 of peanut. RA2 was found to induce resistance in A. hypogaea L. seedlings via induction of different defense-related enzymes like phenylalanine ammonia lyase, peroxidase, polyphenol oxidase, lipoxygenase and pathogenesis related protein like chitinase, ß – 1,3- glucanase. Jasmonic acid one of the major signaling molecules of inducing systemic resistance was also found to induced due to RA2 treatments. RA2 bacterium was also promoting peanut growth and reduce A. niger infection in pot studies. 16S rDNA sequence of RA2 showed 99 % homology to Azotobacter species.

Keywords: plant growth promoting rhizobacteria, peanut, aspergillus niger, induce systemic resistance

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Muhammad Tariq, Bushra Siddique, Muhammad Naeem, Asim Gulzar

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The chemical ecology of natural enemies can play a pivotal role in any Integrated Pest Management (IPM) program. Different chemical cues help to correspond in the diversity of associations between prey and host plant species. Coccinellaseptempunctata and Diaeretiellarapae have the abilities to explore several chemical cues released by plants under herbivore attack that may enhance their efficiency of foraging. In this study, the behavioral responses of Coccinellaseptempunctata and Diaeretiellarapae were examined under the application of two semiochemicals and a plant extract and their combinations using four-arm olfactometer. The bioassay was consists of a pairwise treatment comparison. Data pertaining to the preference of C. septempunctata and D. rapae after treatment application were recorded and analyzed statistically. The mean number of entries and time spent of Coccinellaseptempunctata and D. rapaewere greater in arms treated with E-β-Farnesene. However, the efficacy of E-β-Farnesene was enhanced when combined with β-pinene. Thus, the mean number of entries and time spent of C. septempunctata and D. rapaewere highest in arms treated with the combination of E-β-Farnesene x β-pinene as compared with other treatments. The current work has demonstrated that the insect-derived semiochemicals may enhance the efficacy of natural enemies when applied in combination.

Keywords: olfectometer, parasitoid, predator, preference

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Authors: N. Hammid, F. Bouarab-Dahmani, T. Berkane

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Since its appearance, the MOOC (massive open online course) is gaining more and more intention of the educational communities over the world. Apart from the current MOOCs design and purposes, the creators of MOOC focused on the importance of the connection and knowledge exchange between individuals in learning. In this paper, we present a conceptual model for massive open online blended courses where teachers over the world can collaborate and exchange their experience to get a common efficient content designed as a MOOC opened to their students to live a better learning experience. This model is based on disciplines’ concepts capitalization and the detection of the obstacles met by their students when faced with problem situations (exercises, projects, case studies, etc.). This detection is possible by analyzing the frequently of semantic errors committed by the students. The participation of teachers in the design of the course and the attendance by their students can guarantee an efficient and extensive participation (an important number of participants) in the course, the learners’ motivation and the evaluation issues, in the way that the teachers designing the course assess their students. Thus, the teachers review, together with their knowledge, offer a better assessment and efficient connections to their students.

Keywords: massive open online course, MOOC, online learning, e-learning

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Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

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Authors: Waqas Shafqat Chattha, Muhammad Iqbal, Amir Shakeel

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Transcriptional factors are proteins that play a vital role in regulating the transcription of target genes in different biological processes and are being widely studied in different plant species. In the current era of genomics, plant genomes sequencing has directed to the genome-wide identification, analyses and categorization of diverse transcription factor families and hence provide key insights into their structural as well as functional diversity. The DNA-binding with One Finger (DOF) proteins belongs to C2-C2-type zinc finger protein family. DOF proteins are plant-specific transcription factors implicated in diverse functions including seed maturation and germination, phytohormone signalling, light-mediated gene regulation, cotton-fiber elongation and responses of the plant to biotic as well as abiotic stresses. In this context, a genome-wide in-silico analysis of DOF TF family in diploid cotton species i.e. Gossypium raimondii has enabled us to identify 55 non-redundant genes encoding DOF proteins renamed as GrDofs (Gossypium raimondii Dof). Gene distribution studies have shown that all of the GrDof genes are unevenly distributed across 12 out of 13 G. raimondii chromosomes. The gene structure analysis illustrated that 34 out of 55 GrDof genes are intron-less while remaining 21 genes have a single intron. Protein sequence-based phylogenetic analysis of putative 55 GrDOFs has divided these proteins into 5 major groups with various paralogous gene pairs. Molecular evolutionary studies aided with the conserved domain as well as gene structure analysis suggested that segmental duplications were the principal contributors for the expansion of Dof genes in G. raimondii.

Keywords: diploid cotton , G. raimondii, phylogenetic analysis, transcription factor

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Authors: Muhammad Shoaib, Hassan M. Al-Swaidan

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Air pollution has been a major challenge for the scientists today, due to the release of toxic emissions from various industries like power plants, desalination plants, industrial processes and transportation vehicles. Harmful emissions into the air represent an environmental pressure that reflects negatively on human health and productivity, thus leading to a real loss in the national economy. Variety of air pollutants in the form of carbon oxides, hydrocarbons, nitrogen oxides, sulfur oxides, suspended particulate material etc. are present in air due to the combustion of different types of fuels like crude oil, diesel oil and natural gas. Among various pollutants, NOx and SOx emissions are considered as highly toxic due to its carcinogenicity and its relation with various health disorders. In Kingdom of Saudi Arabia electricity is generated by burning of crude, diesel or natural gas in the turbines of electricity stations. Out of these three, crude oil is used extensively for electricity generation. Due to the burning of the crude oil there are heavy contents of gaseous pollutants like sulfur dioxides (SOx) and nitrogen oxides (NOx), gases which are ultimately discharged in to the environment and is a serious environmental threat. The breakthrough point in case of lab studies using 1 gm of sliced activated carbon adsorbant comes after 20 and 30 minutes for NOx and SOx, respectively, whereas in case of PP8 plant breakthrough point comes in seconds. The saturation point in case of lab studies comes after 100 and 120 minutes and for actual PP8 plant it comes after 60 and 90 minutes for NOx and SOx adsorption, respectively. Surface characterization of NOx and SOx adsorption on SAC confirms the presence of peaks in the FT-IR spectrum. CHNS study verifies that the SAC is suitable for NOx and SOx along with some other C and H containing compounds coming out from stack emission stream from the turbines of a power plant.

Keywords: activated carbon, flue gases, NOx and SOx adsorption, physical activation, power plants

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Authors: Charles Lee

Abstract:

The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

Procedia PDF Downloads 76