Search results for: plant detection

Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Christian Fercher, Jiaul Islam, Simon R. Corrie

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Fluorescence-based immunodiagnostics are an emerging field in biosensor development and exhibit several advantages over traditional detection methods. While various affinity biosensors have been developed to generate a fluorescence signal upon sensing varying concentrations of analytes, reagentless, reversible, and continuous monitoring of complex biological samples remains challenging. Here, we aimed to genetically engineer biosensors based on single-chain antibody fragments (scFv) that are site-specifically labeled with environmentally sensitive fluorescent unnatural amino acids (UAA). A rational design approach resulted in quantifiable analyte-dependent changes in peak fluorescence emission wavelength and enabled antigen detection in vitro. Incorporation of a polarity indicator within the topological neighborhood of the antigen-binding interface generated a titratable wavelength blueshift with nanomolar detection limits. In order to ensure continuous analyte monitoring, scFv candidates with fast binding and dissociation kinetics were selected from a genetic library employing a high-throughput phage display and affinity screening approach. Initial rankings were further refined towards rapid dissociation kinetics using bio-layer interferometry (BLI) and surface plasmon resonance (SPR). The most promising candidates were expressed, purified to homogeneity, and tested for their potential to detect biomarkers in a continuous microfluidic-based assay. Variations of dissociation kinetics within an order of magnitude were achieved without compromising the specificity of the antibody fragments. This approach is generally applicable to numerous antibody/antigen combinations and currently awaits integration in a wide range of assay platforms for one-step protein quantification.

Keywords: antibody engineering, biosensor, phage display, unnatural amino acids

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Authors: Harun Rashid, Keerthi S. S. Atapaththu, Takashi Asaeda

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Cesium (Cs) induced growth and stress response of Nitella were studied after exposure to four concentration of the metal; i.e. 0 (control), 0.001, 0.01, and 0.1 ppm Cs in growth media. Each treatment with three replicates were randomly allocated to 12 glass beakers in a complete randomize design and the experiment was continued for 30 days. At the end of the experiment, shoot length, cesium content, total chlorophyll, and plant stress response were compared. Anti-oxidant enzyme activities (peroxidase, catalase, and ascorbic peroxidase) and the concentration of H2O2 were measured to check plant stress. The longest shoot was found in control treatment (0 ppm Cs) and the shoot length of plants exposed to 0.001 ppm was statistically similar to that of control. Concentration of cesium in plants grown at 0.001, 0.01, and 0.1 ppm were significantly higher than those in control treatments. The antioxidant enzymes activities of plants exposed to cesium were significantly higher than those grown without any Cs (control). An elevated level of H2O2 concentration was also observed in former groups of plants. Further, the reduction in chlorophyll concentration and chlorophyll fluorescence in response to cesium exposure indicated the chronically damaged photosynthetic efficiency in cesium stressed Nitella.

Keywords: antioxidant enzymes, cesium, growth, Nitella, oxidative stress

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Authors: D. P. Houhoula, J. Papaparaskevas, S. Konteles, A. Dargenta, A. Farka, C. Spyrou, M. Ziaka, S. Koussisis, E. Charvalos

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Objectives: Nanotechnology is providing revolutionary opportunities for the rapid and simple diagnosis of many infectious diseases. Staphylococcus aureus, Listeria monocytogenes and Salmonella enteritis are important human pathogens. Diagnostic assays for bacterial culture and identification are time consuming and laborious. There is an urgent need to develop rapid, sensitive, and inexpensive diagnostic tests. In this study, a gold nanoprobe strategy developed and relies on the colorimetric differentiation of specific DNA sequences based approach on differential aggregation profiles in the presence or absence of specific target hybridization. Method: Gold nanoparticles (AuNPs) were purchased from Nanopartz. They were conjugated with thiolated oligonucleotides specific for the femA gene for the identification of members of Staphylococcus aureus, the mecA gene for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus, hly gene encoding the pore-forming cytolysin listeriolysin for the identification of Listeria monocytogenes and the invA sequence for the identification of Salmonella enteritis. DNA isolation from Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis cultures was performed using the commercial kit Nucleospin Tissue (Macherey Nagel). Specifically 20μl of DNA was diluted in 10mMPBS (pH5). After the denaturation of 10min, 20μl of AuNPs was added followed by the annealing step at 58oC. The presence of a complementary target prevents aggregation with the addition of acid and the solution remains pink, whereas in the opposite event it turns to purple. The color could be detected visually and it was confirmed with an absorption spectrum. Results: Specifically, 0.123 μg/μl DNA of St. aureus, L.monocytogenes and Salmonella enteritis was serially diluted from 1:10 to 1:100. Blanks containing PBS buffer instead of DNA were used. The application of the proposed method on isolated bacteria produced positive results with all the species of St. aureus and L. monocytogenes and Salmonella enteritis using the femA, mecA, hly and invA genes respectively. The minimum detection limit of the assay was defined at 0.2 ng/μL of DNA. Below of 0.2 ng/μL of bacterial DNA the solution turned purple after addition of HCl, defining the minimum detection limit of the assay. None of the blank samples was positive. The specificity was 100%. The application of the proposed method produced exactly the same results every time (n = 4) the evaluation was repeated (100% repeatability) using the femA, hly and invA genes. Using the gene mecA for the differentiation of Staphylococcus aureus and MRSA Staphylococcus aureus the method had a repeatability 50%. Conclusion: The proposed method could be used as a highly specific and sensitive screening tool for the detection and differentiation of Staphylococcus aureus Listeria monocytogenes and Salmonella enteritis. The use AuNPs for the colorimetric detection of DNA targets represents an inexpensive and easy-to-perform alternative to common molecular assays. The technology described here, may develop into a platform that could accommodate detection of many bacterial species.

Keywords: gold nanoparticles, pathogens, nanotechnology, bacteria

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Authors: Till Fehlauer, Blanche Collin, Bernard Angeletti, Andrea Somogyi, Claire Lallemand, Perrine Chaurand, Cédric Dentant, Clement Levard, Jerome Rose

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Over the last decades, yttrium (Y) has gained importance in high-tech applications. It is an essential part of alloys and compounds used for lasers, displays, or cell phones, for example. Due to its chemical similarities with the lanthanides, Y is often considered a rare earth element (REE). Despite their increased usage, the environmental behavior of REEs remains poorly understood. Especially regarding their interactions with plants, many uncertainties exist. On the one hand, Y is known to have a negative effect on root development and germination, but on the other hand, it appears to promote plant growth at low concentrations. In order to understand these phenomena, a precise knowledge is necessary about how Y is absorbed by the plant and how it is handled once inside the organism. Contradictory studies exist, stating that due to a similar ionic radius, Y and the other REEs might be absorbed through Ca²⁺-channels, while others suspect that Y has a shared pathway with Al³⁺. In this study, laser ablation coupled ICP-MS, and synchrotron-based micro-X-ray fluorescence (µXRF, beamline Nanoscopium, SOLEIL, France) have been used in order to localize Y within the plant tissue and identify associated elements. The plant used in this study is Saxifraga paniculata, a rugged alpine plant that has shown an affinity for Y in previous studies (in prep.). Furthermore, Saxifraga paniculata performs guttation, which means that it possesses phloem sap secreting openings on the leaf surface that serve to regulate root pressure. These so-called hydathodes could provide special insights in elemental transport in plants. The plants have been grown on Y doped soil (500mg/kg DW) for four months. The results showed that Y was mainly concentrated in the roots of Saxifraga paniculata (260 ± 85mg/kg), and only a small amount was translocated to the leaves (10 ± 7.8mg/kg). µXRF analysis indicated that within the root transects, the majority of Y remained in the epidermis and hardly penetrated the stele. Laser ablation coupled ICP-MS confirmed this finding and showed a positive correlation in the roots between Y, Fe, Al, and to a lesser extent Ca. In the stem transect, Y was mainly detected in a hotspot of approximately 40µm in diameter situated in the endodermis area. Within the stem and especially in the hotspot, Y was highly colocalized with Al and Fe. Similar-sized Y hotspots have been detected in/on the leaves. All of them were strongly colocalized with Al and Fe, except for those situated within the hydathodes, which showed no colocalization with any of the measured elements. Accordingly, a relation between Y and Ca during root uptake remains possible, whereas a correlation to Fe and Al appears to be dominant in the aerial parts, suggesting common storage compartments, the formation of complexes, or a shared pathway during translocation.

Keywords: laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), Phytoaccumulation, Rare earth elements, Saxifraga paniculata, Synchrotron-based micro-X-ray fluorescence, Yttrium

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Ihn Sook Jeong, Eun Joo Lee, Jae Hyung Kim, Gun Ho Kim, Young Jun Hwang

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This study investigated intravenous (IV) infiltration using bioelectrical impedance for 27 hospitalized patients in a long-term care hospital. Impedance parameters showed significant differences before and after infiltration as follows. First, the resistance (R) after infiltration significantly decreased compared to the initial resistance. This indicates that the IV solution flowing from the vein due to infiltration accumulates in the extracellular fluid (ECF). Second, the relative resistance at 50 kHz was 0.94 ± 0.07 in 9 subjects without infiltration and was 0.75 ± 0.12 in 18 subjects with infiltration. Third, the magnitude of the reactance (Xc) decreased after infiltration. This is because IV solution and blood components released from the vein tend to aggregate in the cell membrane (and acts analogously to the linear/parallel circuit), thereby increasing the capacitance (Cm) of the cell membrane and reducing the magnitude of reactance. Finally, the data points plotted in the R-Xc graph were distributed on the upper right before infiltration but on the lower left after infiltration. This indicates that the infiltration caused accumulation of fluid or blood components in the epidermal and subcutaneous tissues, resulting in reduced resistance and reactance, thereby lowering integrity of the cell membrane. Our findings suggest that bioelectrical impedance is an effective method for detection of infiltration in a noninvasive and quantitative manner.

Keywords: intravenous infiltration, impedance, parameters, resistance, reactance

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Authors: Kanchan J. Kakade, S. A. Annadate

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This paper presents design and development of underground coal mine monitoring using mbed arm cortex controller and ZigBee communication. Coal mine is a special type of mine which is dangerous in nature. Safety is the most important feature of a coal industry for proper functioning. It’s not only for employees and workers but also for environment and nation. Many coal producing countries in the world face phenomenal frequently occurred accidents in coal mines viz, gas explosion, flood, and fire breaking out during coal mines exploitation. Thus, such emissions of various gases from coal mines are necessary to detect with the help of robot. Coal is a combustible, sedimentary, organic rock, which is made up of mainly carbon, hydrogen and oxygen. Coal Mine Detection Robot mainly detects mash gas and carbon monoxide. The mash gas is the kind of the mixed gas which mainly make up of methane in the underground of the coal mine shaft, and sometimes it abbreviate to methane. It is formed from vegetation, which has been fused between other rock layers and altered by the combined effects of heat and pressure over millions of years to form coal beds. Coal has many important uses worldwide. The most significant uses of coal are in electricity generation, steel production, cement manufacturing and as a liquid fuel.

Keywords: Zigbee communication, various sensors, hazardous gases, mbed arm cortex M3 core controller

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Authors: I. Parkova, A. Vališevskis, A. Viļumsone

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Nocturnal enuresis or bed-wetting is intermittent incontinence during sleep of children after age 5 that may precipitate wide range of behavioural and developmental problems. One of the non-pharmacological treatment methods is the use of a bed-wetting alarm system. In order to improve comfort conditions of nocturnal enuresis alarm system, modular moisture sensor should be replaced by a textile sensor. In this study behaviour and moisture detection speed of woven and sewn sensors were compared by analysing change in electrical resistance after solution (salt water) was dripped on sensor samples. Material of samples has different structure and yarn location, which affects solution detection rate. Sensor system circuit was designed and two sensor tests were performed: system activation test and false alarm test to determine the sensitivity of the system and activation threshold. Sewn sensor had better result in system’s activation test – faster reaction, but woven sensor had better result in system’s false alarm test – it was less sensitive to perspiration simulation. After experiments it was found that the optimum switching threshold is 3V in case of 5V input voltage, which provides protection against false alarms, for example – during intensive sweating.

Keywords: conductive yarns, moisture textile sensor, industry, material

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Authors: Abdelkhalek Bouchikhi, Elyes Benmokhtar, Sebastien Saletzki

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The aeronautical field is experiencing issues with RF spectrum congestion due to the constant increase in the number of flights, aircrafts and telecom systems on board. In addition, these systems are bulky in size, weight and energy consumption. The cognitive radio helps particularly solving the spectrum congestion issue by its capacity to detect idle frequency channels then, allowing an opportunistic exploitation of the RF spectrum. The present work aims to propose a new use case for aeronautical spectrum sharing and to study the performances of three different detection techniques: energy detector, matched filter and cyclostationary detector within the aeronautical use case. The spectrum in the proposed cognitive radio is allocated dynamically where each cognitive radio follows a cognitive cycle. The spectrum sensing is a crucial step. The goal of the sensing is gathering data about the surrounding environment. Cognitive radio can use different sensors: antennas, cameras, accelerometer, thermometer, etc. In IEEE 802.22 standard, for example, a primary user (PU) has always the priority to communicate. When a frequency channel witch used by the primary user is idle, the secondary user (SU) is allowed to transmit in this channel. The Distance Measuring Equipment (DME) is composed of a UHF transmitter/receiver (interrogator) in the aircraft and a UHF receiver/transmitter on the ground. While the future cognitive radio will be used jointly to alleviate the spectrum congestion issue in the aeronautical field. LDACS, for example, is a good candidate; it provides two isolated data-links: ground-to-air and air-to-ground data-links. The first contribution of the present work is a strategy allowing sharing the L-band. The adopted spectrum sharing strategy is as follow: the DME will play the role of PU which is the licensed user and the LDACS1 systems will be the SUs. The SUs could use the L-band channels opportunely as long as they do not causing harmful interference signals which affect the QoS of the DME system. Although the spectrum sensing is a key step, it helps detecting holes by determining whether the primary signal is present or not in a given frequency channel. A missing detection on primary user presence creates interference between PU and SU and will affect seriously the QoS of the legacy radio. In this study, first brief definitions, concepts and the state of the art of cognitive radio will be presented. Then, a study of three communication channel detection algorithms in a cognitive radio context is carried out. The study is made from the point of view of functions, material requirements and signal detection capability in the aeronautical field. Then, we presented a modeling of the detection problem by three different methods (energy, adapted filter, and cyclostationary) as well as an algorithmic description of these detectors is done. Then, we study and compare the performance of the algorithms. Simulations were carried out using MATLAB software. We analyzed the results based on ROCs curves for SNR between -10dB and 20dB. The three detectors have been tested with a synthetics and real world signals.

Keywords: aeronautic, communication, navigation, surveillance systems, cognitive radio, spectrum sensing, software defined radio

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Authors: Mahendran Ganesan, Sanjeet Kumar Verma, Zafar Iqbal, Ashish Chandran, Zakir Husain, Shama Afroz, Sana Shahid, Laiq Ur Rahman

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Highly efficient in vitro regeneration system has been developed for Swertia chirayita (Roxb. ex Fleming) H. Karst, a high prized traditional medicinal plant to treat numerous ailments such as liver disorders, malaria and diabetes and are reported to have a wide spectrum of pharmacological properties. Its medicinal usage is well-documented in Indian pharmaceutical codex, the British and the American pharmacopeias, and in different traditional medicine such as the Ayurveda, Unani and Siddha medical systems. Nodal explants were cultured on MS medium supplemented with various phytohormones for multiple shoot induction. The nodal segments failed to respond in growth regulator free medium. All the concentrations of BAP, Kin and TDZ facilitated shoot bud break and multiple shoot induction. Among the various cytokinins tested, BAP was found to be more effective with respect to initiation and subsequent development of shoots. Of the various concentrations BAP tested, BAP at 4.0 mg/L showed the higher average number of shoot regeneration (10.80 shoots per explant). Kin at 4 mg/L and TDZ at 4 mg/L induced 5.70 and 04.5+0 shoots per explant, respectively. Further increase in concentration did not favour an increase in the number of shoots. However, these shoots failed to elongate further. Hence, addition of GA₃ (1 mg/L) was added to the above medium. This treatment resulted in the elongation of shoots (2.50 cm) and a further increase in the number of microshoots (34.20 shoots/explant). Roots were also induced in the same medium containing BAP (4 mg/L) + GA₃ (1 mg/L) + NAA (0.5 mg/L). In vitro derived plantlets with well-developed roots were transferred to the potting media containing garden soil: sand: vermicompost (2:1:1). Plantlets were covered with a polyethylene bag and irrigated with water. The pots were maintained at 25 ± 2ºC, and then the polyethylene cover was gradually loosened, thus dropping the humidity (65–70%). This procedure subsequently resulted in in vitro hardening of the plantlet.

Keywords: micropropagation, nodal explant, plant growth regulators, Swertia chirayita

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Authors: Ritu Chaturvedi, Manoj Paul

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A pot experiment was conducted to investigate the effect of Arbuscular mycorrhizal fungus (AMF) on metal(loid) uptake and accumulation efficiency of Pisum sativum along with physiological and biochemical response. Plants were grown in soil spiked with 50 and 100 mg kg-1 Pb, 25 and 50 mg kg-1 Cd, 50 and 100 mg kg-1 As and a combination of all three metal(loid)s. A parallel set was maintained and inoculated with arbuscular mycorrhizal fungus for comparison. After 60 days, plants were harvested and analysed for metal(loid) content. A steady increase in metal(loid) accumulation was observed on increment of metal(loid) dose and also on AMF inoculation. Plant height, biomass, chlorophyll, carotenoid and carbohydrate content reduced upon metal(loid) exposure. Increase in enzymatic (CAT, SOD and APX) and nonenzymatic (Proline) defence proteins was observed on metal(loid) exposure. AMF inoculation leads to an increase in plant height, biomass, chlorophyll, carotenoids, carbohydrate and enzymatic defence proteins (p≤0.001) under study; whereas proline content was reduced. Considering the accumulation efficiency and adaptive response of plants and alleviation of stress by AMF, this symbiosis can be applied for on-site remediation of Pb and Cd contaminated soil.

Keywords: heavy metal, mycorrhiza, pea, phyroremediation

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Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

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In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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Authors: Anupoju Rajeev, Joanne Mathew, Amit Shelke

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In the current study, a new type of Composite Structural Insulated Panels (CSIPs) is developed and investigated its performance against shock loading which can replace the conventional wooden structural materials. The CSIPs is made of Fibre Cement Board (FCB)/aluminum as the facesheet and the expanded polystyrene foam as the core material. As tornadoes are very often in the western countries, it is suggestable to monitor the health of the CSIPs during its lifetime. So, the composite structure is installed with three smart sensors located randomly at definite locations. Each smart sensor is fabricated with an embedded half stainless phononic crystal sensor attached to both ends of the nylon shaft that can resist the shock and impact on facesheet as well as polystyrene foam core and safeguards the system. In addition to the granular crystal sensors, the accelerometers are used in the horizontal spanning and vertical spanning with a definite offset distance. To estimate the health and damage of the CSIP panel using granular crystal sensor, shock wave loading experiments are conducted. During the experiments, the time of flight response from the granular sensors is measured. The main objective of conducting shock wave loading experiments on the CSIP panels is to study the effect and the sustaining capacity of the CSIP panels in the extreme hazardous situations like tornados and hurricanes which are very common in western countries. The effects have been replicated using a shock tube, an instrument that can be used to create the same wind and pressure intensity of tornado for the experimental study. Numerous experiments have been conducted to investigate the flexural strength of the CSIP. Furthermore, the study includes the damage detection using three smart sensors embedded in the CSIPs during the shock wave loading.

Keywords: composite structural insulated panels, damage detection, flexural strength, sandwich structures, shock wave loading

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Authors: Olusola Nafisat Omoniyi

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Aqueous extract of Duranta repens leaves was investigated for its allelopathic effect on Solanum lycopersicum Seedlings germinated and grown under salinity condition. The study was carried out using both laboratory petri dish and pot assays to simulate the plant’s natural environmental conditions. The experiment consisted of 5 groups (1-5), each containing 5 replicates (of 10 seeds). Group 1 was treated with distilled water; Group 2 was treated with 5 mM NaCl; Group 3 was treated with the Extract, Group 4 was treated with a mixture of 5 mM NaCl and the Extract (2:1 v/v), and Group 5 was treated with a mixture of 5 mM NaCl and the Extract (1:2 v/v). The results showed that treatment with NaCl caused significant reductions in germination, growth parameters (plumule and radicle lengths), and chlorophyll concentration of S. lycopersicum seedlings when compared to those treated with D. rupens aqueous leaf extract. Salinity also caused an increase in malondialdehyde and proline concentrations and lowered the activity of superoxide dismutase. However, in the presence of the extract, the adverse effects of the NaCl were attenuated, implying that the extract improved tolerance of S. lycopersicum seedlings. In conclusion, the findings of this study show that the extract is very important in the optimal growth of the plant in saline soil, which has become useful for the management of soil salinity problems.

Keywords: agriculture, allelopathic, salinity, soil, tomato, production, photosynthesis

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Authors: Ali Montazar

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This study aims to assess the viability of sub-surface drip irrigation (SDI) using several ongoing and conducted researches in the low desert region of California. The experiments were carried out in the University of California Desert Research and Extension Center (UC DREC) and ten commercial fields at alfalfa, sugar beets, dehydrated onions, and spinach crops. The results demonstrated greater yields, actual crop water consumption, and water productivity of SDI as compared with conventional irrigation practices (border, furrow, and sprinkler irrigation) with an average increase of 21%, 7%, and 15%, respectively. The severity of plant disease, particularly root rot in sugar beet, and downy mildew in onions and spinach, were significantly lower in SDI than furrow and sprinkler irrigation (an average of 3-5 times). While utilizing this irrigation technology may have ability to achieve higher yields, conserve water, improve the efficiency of water and nutrient use, and manage food safety risks and plant disease, further work is required to better understand the impact of management practices and strategies on the viability of SDI application, and maintain its profitability in various agricultural production systems as water, labor costs, and environmental concerns increase.

Keywords: alfalfa, onions, spinach, sugar beets, subsurface drip irrigation

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Authors: Neha Sahu, Awantika Singh, Brijesh Kumar, K. R. Arya

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Taraxacum officinale Weber or dandelion (Asteraceae) is an important Indian traditional herb used to treat liver detoxification, digestive problems, spleen, hepatic and kidney disorders, etc. The plant is well known to possess important phenolic and flavonoids to serve as a potential source of antioxidative and chemoprotective agents. Biosynthesis of bioactive compounds through in vitro cultures is a requisite for natural resource conservation and to provide an alternative source for pharmaceutical applications. Thus an efficient and reproducible protocol was developed for in vitro biosynthesis of bioactive antioxidative compounds from leaf derived callus and in vitro regenerated cultures of Taraxacum officinale using MS media fortified with various combinations of auxins and cytokinins. MS media containing 0.25 mg/l 2, 4-D (2, 4-Dichloro phenoxyacetic acid) with 0.05 mg/l 2-iP [N6-(2-Isopentenyl adenine)] was found as an effective combination for the establishment of callus with 92 % callus induction frequency. Moreover, 2.5 mg/l NAA (α-Naphthalene acetic acid) with 0.5 mg/l BAP (6-Benzyl aminopurine) and 1.5 mg/l NAA showed the optimal response for in vitro plant regeneration with 80 % regeneration frequency and rooting respectively. In vitro regenerated plantlets were further transferred to soil and acclimatized. Quantitative variability of accumulated bioactive compounds in cultures (in vitro callus, plantlets and acclimatized) were determined through UPLC-MS/MS (ultra-performance liquid chromatography-triple quadrupole-linear ion trap mass spectrometry) and compared with wild plants. The phytochemical determination of in vitro and wild grown samples showed the accumulation of 6 compounds. In in vitro callus cultures and regenerated plantlets, two major antioxidative compounds i.e. chlorogenic acid (14950.0 µg/g and 4086.67 µg/g) and umbelliferone (10400.00 µg/g and 2541.67 µg/g) were found respectively. Scopoletin was found to be highest in vitro regenerated plants (83.11 µg/g) as compared to wild plants (52.75 µg/g). Notably, scopoletin is not detected in callus and acclimatized plants, but quinic acid (6433.33 µg/g) and protocatechuic acid (92.33 µg/g) were accumulated at the highest level in acclimatized plants as compared to other samples. Wild grown plants contained highest content (948.33 µg/g) of flavonoid glycoside i.e. luteolin-7-O-glucoside. Our data suggests that in vitro callus and regenerated plants biosynthesized higher content of antioxidative compounds in controlled conditions when compared to wild grown plants. These standardized cultural conditions may be explored as a sustainable source of plant materials for enhanced production and adequate supply of oxidative polyphenols.

Keywords: anti-oxidative compounds, in vitro cultures, Taraxacum officinale, UPLC-MS/MS

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Authors: Mst Shapna Akter, Hossain Shahriar

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One of the most important challenges in the field of software code audit is the presence of vulnerabilities in software source code. Every year, more and more software flaws are found, either internally in proprietary code or revealed publicly. These flaws are highly likely exploited and lead to system compromise, data leakage, or denial of service. C and C++ open-source code are now available in order to create a largescale, machine-learning system for function-level vulnerability identification. We assembled a sizable dataset of millions of opensource functions that point to potential exploits. We developed an efficient and scalable vulnerability detection method based on deep neural network models that learn features extracted from the source codes. The source code is first converted into a minimal intermediate representation to remove the pointless components and shorten the dependency. Moreover, we keep the semantic and syntactic information using state-of-the-art word embedding algorithms such as glove and fastText. The embedded vectors are subsequently fed into deep learning networks such as LSTM, BilSTM, LSTM-Autoencoder, word2vec, BERT, and GPT-2 to classify the possible vulnerabilities. Furthermore, we proposed a neural network model which can overcome issues associated with traditional neural networks. Evaluation metrics such as f1 score, precision, recall, accuracy, and total execution time have been used to measure the performance. We made a comparative analysis between results derived from features containing a minimal text representation and semantic and syntactic information. We found that all of the deep learning models provide comparatively higher accuracy when we use semantic and syntactic information as the features but require higher execution time as the word embedding the algorithm puts on a bit of complexity to the overall system.

Keywords: cyber security, vulnerability detection, neural networks, feature extraction

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Authors: Nagendra P. Luitel, Mark J. D. Jordans

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Globally, there is a significant gap between the number of individuals in need of mental health care and those who actually receive treatment. The evidence is accumulating that mental health services can be delivered effectively by primary health care workers through community-based programs and task-sharing approaches. Changing the role of specialist mental health workers from service delivery to building clinical capacity of the primary health care (PHC) workers could help in reducing treatment gap in low and middle-income countries (LMICs). We developed a comprehensive mental health care plan in 2012 and evaluated its feasibility and effectiveness over the past three years. Initially, a mixed method formative study was conducted for the development of mental health care plan (MHCP). Routine monitoring and evaluation data, including client flow and reports of satisfaction, were obtained from beneficiaries (n=135) during the pilot-testing phase. Repeated community survey (N=2040); facility detection survey (N=4704) and the cohort study (N=576) were conducted for evaluation of the MHCP. The resulting MHCP consists of twelve packages divided over the community, health facility, and healthcare organization platforms. Detection of mental health problems increased significantly after introducing MHCP. Service implementation data support the real-life applicability of the MHCP, with reasonable treatment uptake. Currently, MHCP has been implemented in the entire Chitwan district where over 1400 people (438 people with depression, 406 people with psychosis, 181 people with epilepsy, 360 people with alcohol use disorder and 51 others) have received mental health services from trained health workers. Key barriers were identified and addressed, namely dissatisfaction with privacy, perceived burden among health workers, high drop-out rates and continue the supply of medicines. The results indicated that involvement of PHC workers in detection and management of mental health problems is an effective strategy to minimize treatment gap on mental health care in Nepal.

Keywords: mental health, Nepal, primary care, treatment gap

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Authors: Marzia Bilkiss, Muhammad J. A. Shiddiky, Mostafa K. Masud, Prabhakaran Sambasivam, Ido Bar, Jeremy Brownlie, Rebecca Ford

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A greater achievement in the Integrated Disease Management (IDM) to prevent the loss would result from early diagnosis and quantitation of the causal pathogen species for accurate and timely disease control. This could significantly reduce costs to the growers and reduce any flow on impacts to the environment from excessive chemical spraying. Necrotrophic fungal disease botrytis grey mould, caused by Botrytis cinerea and Botrytis fabae, significantly reduce temperate legume yield and grain quality during favourable environmental condition in Australia and worldwide. Several immunogenic and molecular probe-type protocols have been developed for their diagnosis, but these have varying levels of species-specificity, sensitivity, and consequent usefulness within the paddock. To substantially improve speed, accuracy, and sensitivity, advanced nanoparticle-based biosensor approaches have been developed. For this, two sets of primers were designed for both Botrytis cinerea and Botrytis fabae which have shown the species specificity with initial sensitivity of two genomic copies/µl in pure fungal backgrounds using multiplexed quantitative PCR. During further validation, quantitative PCR detected 100 spores on artificially infected legume leaves. Simultaneously an electro-catalytic assay was developed for both target fungal DNA using functionalised magnetic nanoparticles. This was extremely sensitive, able to detect a single spore within a raw total plant nucleic acid extract background. We believe that the translation of this technology to the field will enable quantitative assessment of pathogen load for future accurate decision support of informed botrytis grey mould management.

Keywords: biosensor, botrytis grey mould, sensitive, species specific

Procedia PDF Downloads 166

Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: Alim Asamatdinov

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Superabsorbent polymer hydrogels can swell to absorb huge volumes of water or aqueous solutions. This property has led to many practical applications of these new materials, particularly in agriculture for improving the water retention of soils and the water supply of plants. This article reviews the methods of polymeric hydrogels, measurements and treatments of their properties, as well as their effects on soil and on plant growth. The thermodynamic approach used to describe the swelling behaviour of polymer networks proves to be quite helpful in modelling the hydrogel efficiency of water-absorbing additives. The paper presents the results of a study of the physical and chemical properties of hydrogels based on of the production of "Nitron" (Polyacrylonitrile) wastes fibre and salts of the 3-rd transition metals and formalin. The developed hydrogels HG-Al, HG-Cr and HG-formalin have been tested for water holding the capacity of sand. Such a conclusion was also confirmed by data from the method of determining the wilting point by vegetative thumbnails. In the entering process using a dose of 0.1% of the swelling polymeric hydrogel in sand with a culture of barley the difference between the wilting point in comparison with the control was negligible. This indicates that the moisture which was contained in the hydrogel is involved in moisture availability for plant growth, to the same extent as that in the capillaries.

Keywords: hydrogel, chemical, polymer, sandy, colloid

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Authors: Tuba Zahra, Aakash Parekh

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Hyperspectral remote sensing refers to imaging of objects or materials in narrow conspicuous spectral bands. Hyperspectral images (HSI) enable the extraction of spectral signatures for objects or materials observed. These images contain information about the reflectance of each pixel across the electromagnetic spectrum. It enables the acquisition of data simultaneously in hundreds of spectral bands with narrow bandwidths and can provide detailed contiguous spectral curves that traditional multispectral sensors cannot offer. The contiguous, narrow bandwidth of hyperspectral data facilitates the detailed surveying of Earth's surface features. This would otherwise not be possible with the relatively coarse bandwidths acquired by other types of imaging sensors. Hyperspectral imaging provides significantly higher spectral and spatial resolution. There are several use cases that represent the commercial applications of hyperspectral remote sensing. Each use case represents just one of the ways that hyperspectral satellite imagery can support operational efficiency in the respective vertical. There are some use cases that are specific to VNIR bands, while others are specific to SWIR bands. This paper discusses the different commercially viable use cases that are significant for HSI application areas, such as agriculture, mining, oil and gas, defense, environment, and climate, to name a few. Theoretically, there is n number of use cases for each of the application areas, but an attempt has been made to streamline the use cases depending upon economic feasibility and commercial viability and present a review of literature from this perspective. Some of the specific use cases with respect to agriculture are crop species (sub variety) detection, soil health mapping, pre-symptomatic crop disease detection, invasive species detection, crop condition optimization, yield estimation, and supply chain monitoring at scale. Similarly, each of the industry verticals has a specific commercially viable use case that is discussed in the paper in detail.

Keywords: agriculture, mining, oil and gas, defense, environment and climate, hyperspectral, VNIR, SWIR

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Authors: Bongjae Lee, Beom Goo Hwang, Hye Mi Park

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CO₂ capture products manufactured through Carbon Capture and Utilization (CCU) Plant that collect CO₂ directly from power plants require accurate measurements of the amount of CO₂ captured. For this purpose, two tests were carried out on the weight loss test. And one was analyzed using a carbon dioxide quantification device. First, the ignition loss analysis was performed by measuring the weight of the sample at 550°C after the first conversation and then confirming the loss when ignited at 950°C. Second, in the thermogravimetric analysis, the sample was divided into two sections of 40 to 500°C and 500 to 800°C to confirm the reduction. The results of thermal weight loss analysis and thermogravimetric analysis were confirmed to be almost similar. However, the temperature of the ignition loss analysis method was 950°C, which was 150°C higher than that of the thermogravimetric method at a temperature of 800°C, so that the difference in the amount of weight loss was 3 to 4% higher by the heat loss analysis method. In addition, the tendency that the CO₂ content increases as the reaction time become longer is similarly confirmed. Third, the results of the wet titration method through the carbon dioxide quantification device were found to be significantly lower than the weight loss method. Therefore, based on the results obtained through the above three analysis methods, we will establish a method to analyze the accurate amount of CO₂. Acknowledgements: This work was supported by the Korea Institute of Energy Technology Evaluation and planning (No. 20152010201850).

Keywords: carbon capture and utilization, CCU, CO2, CO2 capture products, analysis method

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Authors: John Narh

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There is high rate of deforestation in Ghana due to agricultural expansion, illegal mining and illegal logging. While it is attempting to address the illegalities, Ghana has also initiated a reforestation program known as the Modified Taungya System (MTS). Within the MTS framework, farmers are allocated degraded forestland and provided with tree seedlings to practice agroforestry until the trees form canopy. Yet, the political, ecological and economic models that inform the selection of tree species, the motivations of participating farmers as well as the factors that accounts for differential access to the land and performance of farmers engaged in the program lie underexplored. Using a sequential explanatory mixed methods approach in five forest-fringe communities in the Eastern Region of Ghana, the study reveals that economic factors and Ghana’s commitment to international conventions on the environment underpin the selection of tree species for the MTS program. Social network and access to remittances play critical roles in having access to, and enhances poor farmers’ chances in the program respectively. Farmers are more motivated by the access to degraded forestland to cultivate food crops than having a share in the trees that they plant. As such, in communities where participating farmers are not informed about their benefit in the tree that they plant, the program is largely unsuccessful.

Keywords: translocality, deforestation, forest management, social network

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

Procedia PDF Downloads 134

Authors: Mohamed I. D. Helal, Mohamed M. El-Mogy, Hassan A. Khater, Muhammad A. Fathy, Fatma E. Ibrahim, Yuncong C. Li, Zhaohui Tong, Karima F. Abdelgawad

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Minimizing the consumption of agrochemicals, particularly nitrogen, is the ultimate goal for achieving sustainable agricultural production with low cost and high economic and environmental returns. The use of biopolymers instead of petroleum-based synthetic polymers for CRFs can significantly improve the sustainability of crop production since biopolymers are biodegradable and not harmful to soil quality. Lignin is one of the most abundant biopolymers that naturally exist. In this study, controlled-release fertilizers were developed using a biobased nanocomposite of lignin and bentonite clay mineral as a coating material for urea to increase nitrogen use efficiency. Five types of controlled-release urea (CRU) were prepared using two ratios of modified bentonite as well as techniques. The efficiency of the five controlled-release nano-urea (CRU) fertilizers in improving the growth of tomato plants was studied under field conditions. The CRU was applied to the tomato plants at three N levels representing 100, 50, and 25% of the recommended dose of conventional urea. The results showed that all CRU treatments at the three N levels significantly enhanced plant growth parameters, including plant height, number of leaves, fresh weight, and dry weight, compared to the control. Additionally, most CRU fertilizers increased total yield and fruit characteristics (weight, length, and diameter) compared to the control. Additionally, marketable yield was improved by CRU fertilizers. Fruit firmness and acidity of CRU treatments at 25 and 50% N levels were much higher than both the 100% CRU treatment and the control. The vitamin C values of all CRU treatments were lower than the control. Nitrogen uptake efficiencies (NUpE) of CRU treatments were 47–88%, which is significantly higher than that of the control (33%). In conclusion, all CRU treatments at an N level of 25% of the recommended dose showed better plant growth, yield, and fruit quality of tomatoes than the conventional fertilizer.

Keywords: nitrogen use efficiency, quality, urea, nano particles, ecofriendly

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: raman spectroscopy, mars-analog, beta-carotene, PAHs

Procedia PDF Downloads 334

Authors: Indu Verma, Santanu Kumar Pal

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Interactions between DNA and adsorbed Poly (L-lysine) (PLL) on liquid crystal (LC) droplets were investigated using polarizing optical microcopy (POM) and epi-fluorescence microscopy. Earlier, we demonstrated that adsorption of PLL to the LC/aqueous interface resulted in homeotropic orientation of the LC and thus exhibited a radial configuration of the LC confined within the droplets. Subsequent adsorption of DNA (single stranded DNA/double stranded DNA) at PLL coated LC droplets was found to trigger a LC reorientation within the droplets leading to pre-radial/bipolar configuration of those droplets. To our surprise, subsequent exposure of complementary ssDNA (c-ssDNA) to ssDNA/ adsorbed PLL modified LC droplets did not cause the LC reorientation. This is likely due to the formation of polyplexes (DNA-PLL complex) as confirmed by fluorescence microscopy and atomic force microscopy. In addition, dsDNA adsorbed PLL droplets have been found to be effectively used to displace (controlled release) propidium iodide (a model drug) encapsulated within dsDNA over time. These observations suggest the potential for a label free droplet based LC detection system that can respond to DNA and may provide a simple method to develop DNA-based drug nano-carriers.

Keywords: DNA biosensor, drug delivery, interfaces, liquid crystal droplets

Procedia PDF Downloads 293

Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman

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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10^-1 to 10^-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Keywords: halal, real-time PCR, gelatine, chemometrics

Procedia PDF Downloads 229