Search results for: severity identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3731

Search results for: severity identification

3371 Correlation Matrix for Automatic Identification of Meal-Taking Activity

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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3370 Role of Surfactant Protein D (SP-D) as a Biomarker of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection

Authors: Lucia Salvioni, Pietro Giorgio Lovaglio, Valerio Leoni, Miriam Colombo, Luisa Fiandra

Abstract:

The involvement of plasmatic surfactant protein-D (SP-D) in pulmonary diseases has been long investigated, and over the last two years, more interest has been directed to determine its role as a marker of COVID-19. In this direction, several studies aimed to correlate pulmonary surfactant proteins with the clinical manifestations of the virus indicated SP-D as a prognostic biomarker of COVID-19 pneumonia severity. The present work has performed a retrospective study on a relatively large cohort of patients of Hospital Pio XI of Desio (Lombardia, Italy) with the aim to assess differences in the hematic SP-D concentrations among COVID-19 patients and healthy donors and the role of SP-D as a prognostic marker of severity and/or of mortality risk. The obtained results showed a significant difference in the mean of log SP-D levels between COVID-19 patients and healthy donors, so as between dead and survived patients. SP-D values were significantly higher for both hospitalized COVID-19 and dead patients, with threshold values of 150 and 250 ng/mL, respectively. SP-D levels at admission and increasing differences among follow-up and admission values resulted in the strongest significant risk factors of mortality. Therefore, this study demonstrated the role of SP-D as a predictive marker of SARS-CoV-2 infection and its outcome. A significant correlation of SP-D with patient mortality indicated that it is also a prognostic factor in terms of mortality, and its early detection should be considered to design adequate preventive treatments for COVID-19 patients.

Keywords: SARS-CoV-2 infection, COVID-19, surfactant protein-D (SP-D), mortality, biomarker

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3369 Bird-Adapted Filter for Avian Species and Individual Identification Systems Improvement

Authors: Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Pruchova, Pavel Linhart, Ludek Muller, Dana Jirotkova

Abstract:

One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.

Keywords: avian audiogram, bird individual identification, bird song processing, bird species recognition, filter bank

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3368 Characterisation of Meteorological Drought at Sub-Catchment Scale in Afghanistan Using Time-Series Climate Data

Authors: Yun Chen, David Penton, Fazlul Karim, Santosh Aryal, Shahriar Wahid, Peter Taylor, Susan M. Cuddy

Abstract:

Droughts have severely affected Afghanistan over the last four decades, leading to critical food shortages where two-thirds of the country’s population are in a food crisis. Long years of conflict have lowered the country’s ability to deal with hazards such as drought, which can rapidly escalate into disasters. Understanding the spatial and temporal distribution of droughts is needed to be able to respond effectively to disasters and plan for future occurrences. This study used Standardized Precipitation Evapotranspiration Index (SPEI) at monthly, seasonal, and annual temporal scales to map the spatiotemporal change dynamics of drought characteristics (distribution, frequency, duration, and severity) in Afghanistan. SPEI indices were mapped for river basins, disaggregated into 189 sub-catchments, using monthly precipitation and potential evapotranspiration derived from temperature station observations from 1980 to 2017. The results show these multi-dimensional drought characteristics vary along different years, change among sub-catchments, and differ across temporal scales. During the 38 years, the driest decade and period are the 2000s and 1999–2022, respectively. The 2000–01 water year is the driest, with the whole country experiencing ‘severe’ to ‘extreme’ drought, more than 53% (87 sub-catchments) suffering the worst drought in history, and about 58% (94 sub-catchments) having ‘very frequent’ drought (7 to 8 months) or ‘extremely frequent’ drought (9 to 10 months). The estimated seasonal duration and severity present significant variations across the study area and throughout the study period. The nation also suffered from recurring droughts with varying length and intensity in 2004, 2006, 2008, and, most recently, 2011. There is a trend towards increasing drought with longer duration and higher severity extending all over sub-catchments from southeast to north and central regions. These datasets and maps help to fill the knowledge gap on detailed sub-catchment scale meteorological drought characteristics in Afghanistan. The study findings improve our understanding of the influences of climate change on drought dynamics and can guide catchment planning for reliable adaptation to and mitigation against future droughts.

Keywords: SPEI, precipitation, evapotranspiration, climate extremes

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3367 Variable Renewable Energy Droughts in the Power Sector – A Model-based Analysis and Implications in the European Context

Authors: Martin Kittel, Alexander Roth

Abstract:

The continuous integration of variable renewable energy sources (VRE) in the power sector is required for decarbonizing the European economy. Power sectors become increasingly exposed to weather variability, as the availability of VRE, i.e., mainly wind and solar photovoltaic, is not persistent. Extreme events, e.g., long-lasting periods of scarce VRE availability (‘VRE droughts’), challenge the reliability of supply. Properly accounting for the severity of VRE droughts is crucial for designing a resilient renewable European power sector. Energy system modeling is used to identify such a design. Our analysis reveals the sensitivity of the optimal design of the European power sector towards VRE droughts. We analyze how VRE droughts impact optimal power sector investments, especially in generation and flexibility capacity. We draw upon work that systematically identifies VRE drought patterns in Europe in terms of frequency, duration, and seasonality, as well as the cross-regional and cross-technological correlation of most extreme drought periods. Based on their analysis, the authors provide a selection of relevant historical weather years representing different grades of VRE drought severity. These weather years will serve as input for the capacity expansion model for the European power sector used in this analysis (DIETER). We additionally conduct robustness checks varying policy-relevant assumptions on capacity expansion limits, interconnections, and level of sector coupling. Preliminary results illustrate how an imprudent selection of weather years may cause underestimating the severity of VRE droughts, flawing modeling insights concerning the need for flexibility. Sub-optimal European power sector designs vulnerable to extreme weather can result. Using relevant weather years that appropriately represent extreme weather events, our analysis identifies a resilient design of the European power sector. Although the scope of this work is limited to the European power sector, we are confident that our insights apply to other regions of the world with similar weather patterns. Many energy system studies still rely on one or a limited number of sometimes arbitrarily chosen weather years. We argue that the deliberate selection of relevant weather years is imperative for robust modeling results.

Keywords: energy systems, numerical optimization, variable renewable energy sources, energy drought, flexibility

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3366 Micro/Nano-Sized Emulsions Exhibit Antifungal Activity against Cucumber Downy Mildew

Authors: Kai-Fen Tu, Jenn-Wen Huang, Yao-Tung Lin

Abstract:

Cucumber is a major economic crop in the world. The global production of cucumber in 2017 was more than 71 million tonnes. Nonetheless, downy mildew, caused by Pseudoperonospora cubensis, is a devastating and common disease on cucumber in around 80 countries and causes severe economic losses. The long-term usage of fungicide also leads to the occurrence of fungicide resistance and decreases host resistance. In this study, six types of oil (neem oil, moringa oil, soybean oil, cinnamon oil, clove oil, and camellia oil) were selected to synthesize micro/nano-sized emulsions, and the disease control efficacy of micro/nano-sized emulsions were evaluated. Moreover, oil concentrations (0.125% - 1%) and droplet size of emulsion were studied. Results showed cinnamon-type emulsion had the best efficacy among these oils. The disease control efficacy of these emulsions increased as the oil concentration increased. Both disease incidence and disease severity were measured by detached leaf and pot experiment, respectively. For the droplet size effect, results showed that the 114 nm of droplet size synthesized by 0.25% cinnamon oil emulsion had the lowest disease incidence (6.67%) and lowest disease severity (33.33%). The release of zoospore was inhibited (5.33%), and the sporangia germination was damaged. These results suggest that cinnamon oil emulsion will be a valuable and environmentally friendly alternative to control cucumber downy mildew. The economic loss caused by plant disease could also be reduced.

Keywords: downy mildew, emulsion, oil droplet size, plant protectant

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3365 Self-Tuning Power System Stabilizer Based on Recursive Least Square Identification and Linear Quadratic Regulator

Authors: J. Ritonja

Abstract:

Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification

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3364 Group Boundaries against and Due to Identity Threat

Authors: Anna Siegler, Sara Bigazzi, Sara Serdult, Ildiko Bokretas

Abstract:

Social identity emerging from group membership defines the representational processes of our social reality. Based on our theoretical assumption the subjective perception of identity threat leads to an instable identity structure. The need to re-establish the positive identity will lead us to strengthen group boundaries. Prejudice in our perspective offer psychological security those who thinking in exclusive barriers, and we suggest that those who identify highly with their ingroup/national identity and less with superordinate identities take distance from others and this is related to their perception of threat. In our study we used a newly developed questionnaire, the Multiple Threat and Prejudice Questionnaire (MTPQ) which measure identity threat at different dimensions of identification (national, existential, gender, religious) and the distancing of different outgroups, over and above we worked with Social Dominance Orientation (SDO) and Identification with All Humanity Scale (IWAH). We conduct one data collection (N=1482) in a Hungarian sample to examine the connection between national threat and distance-taking, and this survey includes the investigation (N=218) of identification with different group categories. Our findings confirmed that those who feel themselves threatened in their national identity aspects are less likely to identify themselves with superordinate groups and this correlation is much stronger when they think about the nation as a bio-cultural unit, while if nation defined as a social-economy entity this connection is less powerful and has just the opposite direction.

Keywords: group boundaries, identity threat, prejudice, superordinate groups

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3363 The Impact of Streptococcus pneumoniae Colonization on Viral Bronchiolitis

Authors: K. Genise, S. Murthy

Abstract:

Introductory Statement: The results of this retrospective chart review suggest the effects of bacterial colonization in critically ill children with viral bronchiolitis, currently unproven, are clinically insignificant. Background: Viral bronchiolitis is one of the most prevalent causes of illness requiring hospitalization among children worldwide and one of the most common reasons for admission to pediatric intensive care. It has been hypothesized that co-infection with bacteria results in more severe clinical outcomes. Conversely, the effects of bacterial colonization in critically ill patients with bronchiolitis are poorly defined. Current clinical management of colonized patients consists primarily of supportive therapies with the role of antibiotics remaining controversial. Methods: A retrospective review of all critically ill children admitted to the BC Children’s Hospital Pediatric Intensive Care Unit (PICU) from 2014-2017 with a diagnosis of bronchiolitis was performed. Routine testing in this time frame consisted of complete pathogen testing, including PCR for Streptococcus pneumoniae. Analyses were performed to determine the impact of bacterial colonization and antibiotic use on a primary outcome of PICU length-of-stay, with secondary outcomes of hospital length-of-stay and duration of ventilation. Results: There were 92 patients with complete pathogen testing performed during the assessed timeframe. A comparison between children with detected Streptococcus pneumoniae (n=22) and those without (n=70) revealed no significant (p=0.20) differences in severity of illness on presentation as per Pediatric Risk of Mortality III scores (mean=3.0). Patients colonized with S. pneumoniae had significantly shorter PICU stays (p=0.002), hospital stays (p=0.0001) and duration of non-invasive ventilation (p=0.002). Multivariate analyses revealed that these effects on length of PICU stay and duration of ventilation do not persist after controlling for antibiotic use, presence of radiographic consolidation, age, and severity of illness (p=0.15, p=0.32). The relationship between colonization and duration of hospital stay persists after controlling for these variables (p=0.008). Conclusions: Children with viral bronchiolitis colonized with S. pneumoniae do not appear to have significantly different PICU length-of-stays or duration of ventilation compared to children who are not colonized. Colonized children appear to have shorter hospital stays. The results of this study suggest bacterial colonization is not associated with increased severity of presenting illness or negative clinical outcomes.

Keywords: bronchiolitis, colonization, critical care, pediatrics, pneumococcal, infection

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3362 A Review of Ultralightweight Mutual Authentication Protocols

Authors: Umar Mujahid, Greatzel Unabia, Hongsik Choi, Binh Tran

Abstract:

Radio Frequency Identification (RFID) is one of the most commonly used technologies in IoTs and Wireless Sensor Networks which makes the devices identification and tracking extremely easy to manage. Since RFID uses wireless channel for communication, which is open for all types of adversaries, researchers have proposed many Ultralightweight Mutual Authentication Protocols (UMAPs) to ensure security and privacy in a cost-effective manner. These UMAPs involve simple bitwise logical operators such as XOR, AND, OR & Rot, etc., to design the protocol messages. However, most of these UMAPs were later reported to be vulnerable against many malicious attacks. In this paper, we have presented a detailed overview of some eminent UMAPs and also discussed the many security attacks on them. Finally, some recommendations and suggestions have been discussed, which can improve the design of the UMAPs.

Keywords: RFID, Ultralightweight, UMAP, SASI

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3361 Robust Noisy Speech Identification Using Frame Classifier Derived Features

Authors: Punnoose A. K.

Abstract:

This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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3360 Morality in Actual Behavior: The Moderation Effect of Identification with the Ingroup and Religion on Norm Compliance

Authors: Shauma L. Tamba

Abstract:

This study examined whether morality is the most important aspect in actual behavior. The prediction was that people tend to behave in line with moral (as compared to competence) norms, especially when such norms are presented by their ingroup. The actual behavior that was tested was support for a military intervention without a mandate from the UN. In addition, this study also examined whether identification with the ingroup and religion moderated the effect of group and norm on support for the norm that was prescribed by their ingroup. The prediction was that those who identified themselves higher with the ingroup moral would show a higher support for the norm. Furthermore, the prediction was also that those who have religion would show a higher support for the norm in the ingroup moral rather than competence. In an online survey, participants were asked to read a scenario in which a military intervention without a mandate was framed as either the moral (but stupid) or smart (but immoral) thing to do by members of their own (ingroup) or another (outgroup) society. This study found that when people identified themselves with the smart (but immoral) norm, they showed a higher support for the norm. However, when people identified themselves with the moral (but stupid) norm, they tend to show a lesser support towards the norm. Most of the results in the study did not support the predictions. Possible explanations and implications are discussed.

Keywords: morality, competence, ingroup identification, religion, group norm

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3359 A Computational Approach for the Prediction of Relevant Olfactory Receptors in Insects

Authors: Zaide Montes Ortiz, Jorge Alberto Molina, Alejandro Reyes

Abstract:

Insects are extremely successful organisms. A sophisticated olfactory system is in part responsible for their survival and reproduction. The detection of volatile organic compounds can positively or negatively affect many behaviors in insects. Compounds such as carbon dioxide (CO2), ammonium, indol, and lactic acid are essential for many species of mosquitoes like Anopheles gambiae in order to locate vertebrate hosts. For instance, in A. gambiae, the olfactory receptor AgOR2 is strongly activated by indol, which accounts for almost 30% of human sweat. On the other hand, in some insects of agricultural importance, the detection and identification of pheromone receptors (PRs) in lepidopteran species has become a promising field for integrated pest management. For example, with the disruption of the pheromone receptor, BmOR1, mediated by transcription activator-like effector nucleases (TALENs), the sensitivity to bombykol was completely removed affecting the pheromone-source searching behavior in male moths. Then, the detection and identification of olfactory receptors in the genomes of insects is fundamental to improve our understanding of the ecological interactions, and to provide alternatives in the integrated pests and vectors management. Hence, the objective of this study is to propose a bioinformatic workflow to enhance the detection and identification of potential olfactory receptors in genomes of relevant insects. Applying Hidden Markov models (Hmms) and different computational tools, potential candidates for pheromone receptors in Tuta absoluta were obtained, as well as potential carbon dioxide receptors in Rhodnius prolixus, the main vector of Chagas disease. This study showed the validity of a bioinformatic workflow with a potential to improve the identification of certain olfactory receptors in different orders of insects.

Keywords: bioinformatic workflow, insects, olfactory receptors, protein prediction

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3358 From Primer Generation to Chromosome Identification: A Primer Generation Genotyping Method for Bacterial Identification and Typing

Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

Abstract:

A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

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3357 Disease Control of Rice Blast Caused by Pyricularia Oryzae Cavara Using Novel Chitosan-based Agronanofungicides

Authors: Abdulaziz Bashir Kutawa, Khairulmazmi Ahmad, Mohd Zobir Hussein, Asgar Ali, Mohd Aswad Abdul Wahab, Amara Rafi, Mahesh Tiran Gunasena, Muhammad Ziaur Rahman, Md. Imam Hossain, Syazwan Afif Mohd Zobir

Abstract:

Rice is a cereal crop and belongs to the family Poaceae, it was domesticated in southern China and North-Eastern India around 8000 years ago, and it’s the staple nourishment for over half of the total world’s population. Rice production worldwide is affected by different abiotic and biotic stresses. Diseases are important challenges for the production of rice, among all the diseases in rice plants, the most severe and common disease is the rice blast. Worldwide, it is one of the most damaging diseases affecting rice cultivation, the disease is caused by the non-obligate filamentous ascomycete fungus called Magnaporthe grisae or Pyricularia oryzae Cav. Nanotechnology is a new idea to improve agriculture by combating the diseases of plants, as nanoparticles were found to possess an inhibitory effect on different species of fungi. This work aimed to develop and determine the efficacy of agronanofungicides, and commercial fungicides (in-vitro and in-vivo). The agronanofungicides were developed using ionic gelation methods. In-vitro antifungal activity of the synthesized agronanofungicides was evaluated against P. oryzae using the poisoned medium technique. The potato dextrose agar (PDA) was amended in several concentrations; 0.001, 0.005, 0.01, 0.025, 0.05, 0.1, 0.15, 0.20, 0.25, 0.30, and 0.35 ppm for the agronanofungicides. Medium with the only solvent served as a control. Mycelial growth was recorded every day, and the percentage inhibition of radial growth (PIRG) was also calculated. Based on the results of the zone of inhibition, the chitosan-hexaconazole agronanofungicide (2g/mL) was the most effective fungicide to inhibit the growth of the fungus with 100% inhibition at 0.2, 0.25, 0.30, and 0.35 ppm, respectively. The least were found to be propiconazole and basamid fungicides with 100% inhibition only at 100 ppm. In terms of the glasshouse results, the chitosan-hexaconazole-dazomet agronanofungicide (CHDEN) treatment (2.5g/L) was found to be the most effective fungicide to reduce the intensity of the disease with a disease severity index (DSI) of 19.80%, protection index (PI) of 82.26%, lesion length of 1.63cm, disease reduction (DR) of 80.20%, and AUDPC (390.60 Unit2). The least effective fungicide was found to be ANV with a disease severity index (45.60%), protection index (45.24%), lesion length (3.83 cm), disease reduction (54.40%), and AUDPC (1205.75 Unit2). The negative control did not show any symptoms during the glasshouse assay, while the untreated control treatment exhibited severe symptoms of the disease with a DSI value of 64.38%, lesion length of 5.20 cm, and AUDPC value of 2201.85 Unit2, respectively. The treatments of agronanofungicides have enhanced the yield significantly with CHDEN having 239.00 while the healthy control had 113.67 for the number of grains per panicle. The use of CHEN and CHDEN will help immensely in reducing the severity of rice blast in the fields, and this will increase the yield and profit of the farmers that produced rice.

Keywords: chitosan, dazomet, disease severity, efficacy, and blast disease

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3356 Application of the Total Least Squares Estimation Method for an Aircraft Aerodynamic Model Identification

Authors: Zaouche Mohamed, Amini Mohamed, Foughali Khaled, Aitkaid Souhila, Bouchiha Nihad Sarah

Abstract:

The aerodynamic coefficients are important in the evaluation of an aircraft performance and stability-control characteristics. These coefficients also can be used in the automatic flight control systems and mathematical model of flight simulator. The study of the aerodynamic aspect of flying systems is a reserved domain and inaccessible for the developers. Doing tests in a wind tunnel to extract aerodynamic forces and moments requires a specific and expensive means. Besides, the glaring lack of published documentation in this field of study makes the aerodynamic coefficients determination complicated. This work is devoted to the identification of an aerodynamic model, by using an aircraft in virtual simulated environment. We deal with the identification of the system, we present an environment framework based on Software In the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. We propose The Total Least Squares Estimation technique (TLSE) to identify the aerodynamic parameters, which are unknown, variable, classified and used in the expression of the piloting law. In this paper, we define each aerodynamic coefficient as the mean of its numerical values. All other variations are considered as modeling uncertainties that will be compensated by the robustness of the piloting control.

Keywords: aircraft aerodynamic model, total least squares estimation, piloting the aircraft, robust control, Microsoft Flight Simulator, MQ-1 predator

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3355 Fault Analysis of Induction Machine Using Finite Element Method (FEM)

Authors: Wiem Zaabi, Yemna Bensalem, Hafedh Trabelsi

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The paper presents a finite element (FE) based efficient analysis procedure for induction machine (IM). The FE formulation approaches are proposed to achieve this goal: the magnetostatic and the non-linear transient time stepped formulations. The study based on finite element models offers much more information on the phenomena characterizing the operation of electrical machines than the classical analytical models. This explains the increase of the interest for the finite element investigations in electrical machines. Based on finite element models, this paper studies the influence of the stator and the rotor faults on the behavior of the IM. In this work, a simple dynamic model for an IM with inter-turn winding fault and a broken bar fault is presented. This fault model is used to study the IM under various fault conditions and severity. The simulation results are conducted to validate the fault model for different levels of fault severity. The comparison of the results obtained by simulation tests allowed verifying the precision of the proposed FEM model. This paper presents a technical method based on Fast Fourier Transform (FFT) analysis of stator current and electromagnetic torque to detect the faults of broken rotor bar. The technique used and the obtained results show clearly the possibility of extracting signatures to detect and locate faults.

Keywords: Finite element Method (FEM), Induction motor (IM), short-circuit fault, broken rotor bar, Fast Fourier Transform (FFT) analysis

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3354 Analyzing Keyword Networks for the Identification of Correlated Research Topics

Authors: Thiago M. R. Dias, Patrícia M. Dias, Gray F. Moita

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The production and publication of scientific works have increased significantly in the last years, being the Internet the main factor of access and distribution of these works. Faced with this, there is a growing interest in understanding how scientific research has evolved, in order to explore this knowledge to encourage research groups to become more productive. Therefore, the objective of this work is to explore repositories containing data from scientific publications and to characterize keyword networks of these publications, in order to identify the most relevant keywords, and to highlight those that have the greatest impact on the network. To do this, each article in the study repository has its keywords extracted and in this way the network is  characterized, after which several metrics for social network analysis are applied for the identification of the highlighted keywords.

Keywords: bibliometrics, data analysis, extraction and data integration, scientometrics

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3353 Development of a Multi-Locus DNA Metabarcoding Method for Endangered Animal Species Identification

Authors: Meimei Shi

Abstract:

Objectives: The identification of endangered species, especially simultaneous detection of multiple species in complex samples, plays a critical role in alleged wildlife crime incidents and prevents illegal trade. This study was to develop a multi-locus DNA metabarcoding method for endangered animal species identification. Methods: Several pairs of universal primers were designed according to the mitochondria conserved gene regions. Experimental mixtures were artificially prepared by mixing well-defined species, including endangered species, e.g., forest musk, bear, tiger, pangolin, and sika deer. The artificial samples were prepared with 1-16 well-characterized species at 1% to 100% DNA concentrations. After multiplex-PCR amplification and parameter modification, the amplified products were analyzed by capillary electrophoresis and used for NGS library preparation. The DNA metabarcoding was carried out based on Illumina MiSeq amplicon sequencing. The data was processed with quality trimming, reads filtering, and OTU clustering; representative sequences were blasted using BLASTn. Results: According to the parameter modification and multiplex-PCR amplification results, five primer sets targeting COI, Cytb, 12S, and 16S, respectively, were selected as the NGS library amplification primer panel. High-throughput sequencing data analysis showed that the established multi-locus DNA metabarcoding method was sensitive and could accurately identify all species in artificial mixtures, including endangered animal species Moschus berezovskii, Ursus thibetanus, Panthera tigris, Manis pentadactyla, Cervus nippon at 1% (DNA concentration). In conclusion, the established species identification method provides technical support for customs and forensic scientists to prevent the illegal trade of endangered animals and their products.

Keywords: DNA metabarcoding, endangered animal species, mitochondria nucleic acid, multi-locus

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3352 Forensic Comparison of Facial Images for Human Identification

Authors: D. P. Gangwar

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Identification of human through facial images has got great importance in forensic science. The video recordings, CCTV footage, passports, driver licenses and other related documents are invariably sent to the laboratory for comparison of the questioned photographs as well as video recordings with suspected photographs/recordings to prove the identity of a person. More than 300 questioned and 300 control photographs received in actual crime cases, received from various investigation agencies, have been compared by me so far using various familiar analysis and comparison techniques such as Holistic comparison, Morphological analysis, Photo-anthropometry and superimposition. On the basis of findings obtained during the examination huge photo exhibits, a realistic and comprehensive technique has been proposed which could be very useful for forensic.

Keywords: CCTV Images, facial features, photo-anthropometry, superimposition

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3351 Scientific Investigation for an Ancient Egyptian Polychrome Wooden Stele

Authors: Ahmed Abdrabou, Medhat Abdalla

Abstract:

The studied stele dates back to Third Intermediate Period (1075-664) B.C in an ancient Egypt. It is made of wood and covered with painted gesso layers. This study aims to use a combination of multi spectral imaging {visible, infrared (IR), Visible-induced infrared luminescence (VIL), Visible-induced ultraviolet luminescence (UVL) and ultraviolet reflected (UVR)}, along with portable x-ray fluorescence in order to map and identify the pigments as well as to provide a deeper understanding of the painting techniques. Moreover; the authors were significantly interested in the identification of wood species. Multispectral imaging acquired in 3 spectral bands, ultraviolet (360-400 nm), visible (400-780 nm) and infrared (780-1100 nm) using (UV Ultraviolet-induced luminescence (UVL), UV Reflected (UVR), Visible (VIS), Visible-induced infrared luminescence (VIL) and Infrared photography. False color images are made by digitally editing the VIS with IR or UV images using Adobe Photoshop. Optical Microscopy (OM), potable X-ray fluorescence spectroscopy (p-XRF) and Fourier Transform Infrared Spectroscopy (FTIR) were used in this study. Mapping and imaging techniques provided useful information about the spatial distribution of pigments, in particular visible-induced luminescence (VIL) which allowed the spatial distribution of Egyptian blue pigment to be mapped and every region containing Egyptian blue, even down to single crystals in some instances, is clearly visible as a bright white area; however complete characterization of the pigments requires the use of p. XRF spectroscopy. Based on the elemental analysis found by P.XRF, we conclude that the artists used mixtures of the basic mineral pigments to achieve a wider palette of hues. Identification of wood species Microscopic identification indicated that the wood used was Sycamore Fig (Ficus sycomorus L.) which is recorded as being native to Egypt and was used to make wooden artifacts since at least the Fifth Dynasty.

Keywords: polychrome wooden stele, multispectral imaging, IR luminescence, Wood identification, Sycamore Fig, p-XRF

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3350 Comparing Russian and American Students’ Metaphorical Competence

Authors: Svetlana L. Mishlanova, Evgeniia V. Ermakova, Mariia E. Timirkina

Abstract:

The paper is concerned with the study of metaphor production in essays written by Russian and English native speakers in the framework of cognitive metaphor theory. It considers metaphorical competence as individual’s ability to recognize, understand and use metaphors in speech. The work analyzes the influence of visual metaphor on production and density of conventional and novel verbal metaphors. The main methods of research include experiment connected with image interpretation, metaphor identification procedure (MIPVU) and visual conventional metaphors identification procedure proposed by VisMet group. The research findings will be used in the project aimed at comparing metaphorical competence of native and non-native English speakers.

Keywords: metaphor, metaphorical competence, conventional, novel

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3349 A Visual Analytics Tool for the Structural Health Monitoring of an Aircraft Panel

Authors: F. M. Pisano, M. Ciminello

Abstract:

Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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3348 Risk Factors and Biomarkers for the Recurrence of Ovarian Endometrioma: About the Immunoreactivity of Progesterone Receptor Isoform B and Nuclear Factor Kappa B.

Authors: Ae Ra Han, Taek Hoo Lee, Sun Zoo Kim, Hwa Young Lee

Abstract:

Introduction: Ovarian endometrioma is one of the important causes of poor ovarian reserve and up to half of them have recurred. However, the treatment for recurrence prevention has limited efficiency and repeated surgical management makes worsen the ovarian reserve. To find better management for recurrence prevention, we investigated risk factors and biomarkers for the recurrence of ovarian endometrioma. Methods: The medical records of women with the history of surgical dissection for ovarian endometrioma were collected. After exclusion of the cases with concurrent hysterectomy, been menopaused during follow-up, incomplete medical record, and loss of follow-up, a total of 134 women were enrolled. Immunohistochemical staining for progesterone receptor isoform B (PR-B) and nuclear factor kappa B (NFκB) was done with the fixed tissue blocks of their endometriomas which were collected at the time of surgery. Results: Severity of dysmenorrhea and co-existence of adenomyosis had significant correlation with recurrence of endometrioma. Increased PR-B (P = .041) and decreased NFκB (P = .036) immunoreactivity were found in recurrent group. Serum CA-125 level at the time of recurrence was higher than the highest level of CA-125 during follow-up in unrecurred group (55.6 vs. 21.3 U/mL, P = .014). Conclusion: We found that the severity of dysmenorrhea and coexistence of adenomyosis are risk factors for recurrence of ovarian endometrioma, and serial follow-up of CA-125 is effective to detect and prevent the recurrence. However, to determine the possibility of immunoreactivity of PR-B and NFκB as biomarkers for ovarian endometrioma, further studies of various races and large numbers with prospective design are needed.

Keywords: endometriosis, recurrence, biomarker, risk factor

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3347 The Marker Active Compound Identification of Calotropis gigantea Roots Extract as an Anticancer

Authors: Roihatul Mutiah, Sukardiman, Aty Widyawaruyanti

Abstract:

Calotropis gigantiea (L.) R. Br (Apocynaceae) commonly called as “Biduri” or “giant milk weed” is a well-known weed to many cultures for treating various disorders. Several studies reported that C.gigantea roots has anticancer activity. The main aim of this research was to isolate and identify an active marker compound of C.gigantea roots for quality control purpose of its extract in the development as anticancer natural product. The isolation methods was bioactivity guided column chromatography, TLC, and HPLC. Evaluated anticancer activity of there substances using MTT assay methods. Identification structure active compound by UV, 1HNMR, 13CNMR, HMBC, HMQC spectral and other references. The result showed that the marker active compound was identical as Calotropin.

Keywords: calotropin, Calotropis gigantea, anticancer, marker active

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3346 Fault Location Identification in High Voltage Transmission Lines

Authors: Khaled M. El Naggar

Abstract:

This paper introduces a digital method for fault section identification in transmission lines. The method uses digital set of the measured short circuit current to locate faults in electrical power systems. The digitized current is used to construct a set of overdetermined system of equations. The problem is then constructed and solved using the proposed digital optimization technique to find the fault distance. The proposed optimization methodology is an application of simulated annealing optimization technique. The method is tested using practical case study to evaluate the proposed method. The accurate results obtained show that the algorithm can be used as a powerful tool in the area of power system protection.

Keywords: optimization, estimation, faults, measurement, high voltage, simulated annealing

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3345 Fungi Associated with Decline of Kikar (Acacia nilotica) and Red River Gum (Eucalyptus camaldulensis) in Faisalabad

Authors: I. Ahmad, A. Hannan, S. Ahmad, M. Asif, M. F. Nawaz, M. A. Tanvir, M. F. Azhar

Abstract:

During this research, a comprehensive survey of tree growing areas of Faisalabad district of Pakistan was conducted to observe the symptoms, spectrum, occurrence and severity of A. nilotica and E. camaldulensis decline. Objective of current research was to investigate specific fungal pathogens involved in decline of A. nilotica and E. camaldulensis. For this purpose, infected roots, bark, neck portion, stem, branches, leaves and infected soils were collected to identify associated fungi. Potato dextrose agar (PDA) and Czepak dox agar media were used for isolations. Identification of isolated fungi was done microscopically and different fungi were identified. During survey of urban locations of Faisalabad, disease incidence on Kikar and Eucalyptus was recorded as 3.9-7.9% and 2.6-7.1% respectively. Survey of Agroforest zones of Faisalabad revealed decline incidence on kikar 7.5% from Sargodha road while on Satiana and Jhang road it was not planted. In eucalyptus trees, 4%, 8% and 0% disease incidence was observed on Jhang road, Sargodha road and Satiana road respectively. The maximum fungus isolated from the kikar tree was Drechslera australiensis (5.00%) from the stem part. Aspergillus flavus also gave the maximum value of (3.05%) from the bark. Alternaria alternata gave the maximum value of (2.05%) from leaves. Rhizopus and Mucor spp. were recorded minimum as compared to the Drechslera, Alternaria and Aspergillus. The maximum fungus isolated from the Eucalyptus tree was Armillaria luteobubalina (5.00%) from the stem part. The other fungi isolated were Macrophamina phaseolina and A. niger.

Keywords: decline, frequency of mycoflora, A. nilotica and E. camaldulensis, Drechslera australiensis, Armillaria luteobubalina

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3344 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

Procedia PDF Downloads 378
3343 Low-Cost Image Processing System for Evaluating Pavement Surface Distress

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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3342 Comparing Effects of Supervised Exercise Therapy versus Home-Based Exercise Therapy on Low Back Pain Severity, Muscle Strength and Anthropometric Parameters in Patients with Nonspecific Chronic Low Back Pain

Authors: Haleh Dadgostar, Faramarz Akbari, Hosien Vahid Tari, Masoud Solaymani-Dodaran, Mohammad Razi

Abstract:

Introduction: There are a number of exercises-protocols have been applied to improve low back pain. We compared the effect of supervised exercise therapy and home-based exercise therapy among patients with nonspecific chronic low back pain. Methods: 70 patients with nonspecific chronic low back pain were randomly (using a random number generator, excel) divided into two groups to compare the effects of two types of exercise therapy. After a common educational session to learn how to live with low back pain as well as to use core training protocols to strengthen the muscles, the subjects were randomly assigned to follow supervised exercise therapy (n = 31) or home-based exercise therapy (n = 34) for 20 weeks. Results: Although both types of exercise programs resulted in reduced pain, this factor decreased more significantly in supervised exercise program. All scores of fitness improved significantly in supervised exercise group. But only knee extensor strength score was increased in the home base exercise group. Conclusion: Comparing between two types of exercise, supervised group exercise showed more effective than the other one. Reduction in low back pain severity and improvement in muscle flexibility and strength can be more achieved by using a 20-week supervised exercise program compared to the home-based exercise program in patients with nonspecific chronic low back pain.

Keywords: low back pain, anthropometric parameters, supervised exercise therapy, home-based exercise therapy

Procedia PDF Downloads 309