Search results for: model-free damage detection

Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Patrick M. Garvey, Roger P. Pech, Daniel M. Tompkins

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Competition is a widespread interaction and natural selection will encourage the development of mechanisms that recognise and respond to dominant competitors, if this information reduces the risk of a confrontation. As olfaction is the primary sense for most mammals, our research tested whether olfactory ‘eavesdropping’ mediates alien species interactions and whether we could exploit our understanding of this behaviour to create ‘super-lures’. We used a combination of pen and field experiments to evaluate the importance of this behaviour. In pen trials, stoats (Mustela erminea) were exposed to the body odour of three dominant predators (cat / ferret / African wild dog) and these scents were found to be attractive. A subsequent field trial tested whether attraction displayed towards predator odour, particularly ferret (Mustela furo) pheromones, could be replicated with invasive predators in the wild. We found that ferret odour significantly improved detection and activity of stoats and hedgehogs (Erinaceus europaeus), while also improving detections of ship rats (Rattus rattus). Our current research aims to identify the key components of ferret odour, using chemical analysis and behavioural experiments, so that we can produce ‘scent from a can’. A lure based on a competitors’ odour would be beneficial in many circumstances including: (i) where individuals display variability in attraction to food lures, (ii) there are plentiful food resources available, (iii) new immigrants arrive into an area, (iv) long-life lures are required. Pest management can therefore benefit by exploiting behavioural responses to odours to achieve conservation goals.

Keywords: predator interactions, invasive species, eavesdropping, semiochemicals

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Authors: Eryati Darwin, Eka Fithra Elfi, Indria Hafizah

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Background: Physical exercise induces a pattern of hormonal and immunological responses that prevent endothelial dysfunction by maintaining the availability of nitric oxide (NO). Regular and moderate exercise stimulates NO release, that can be considered as protective factor of cardiovascular diseases, while strenuous exercise induces increased levels in a number of pro-inflammatory and anti-inflammatory cytokines. Pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) triggers endothelial activation which results in an increased vascular permeability. Nuclear gene factor kappa B (NF-κB) activates biological effect of TNF-α. Aim of Study: To determine the effect of physical exercise on the endothelial and skeletal muscle, we measured the level of NF-κB on rats’ serum, macrophages, and myocytes after strenuous physical exercise. Methods: 30 male Rattus norvegicus in the age of eight weeks were randomly divided into five groups (each containing six), and there were treated groups (T) and control group (C). The treated groups obtain strenuous physical exercise by ran on treadmill at 32 m/minutes for 1 hour or until exhaustion. Blood samples, myocytes of gastrocnemius muscle, and intraperitoneal macrophages were collected sequentially. There were investigated immediately, 2 hours, 6 hours, and 24 hours (T1, T2, T3, and T4) after sacrifice. The levels of NF-κB were measured by ELISA methods. Results: From our study, we found that the levels of NF-κB on myocytes in treated group from which its specimen was taken immediately (T1), 2 hours after treadmill (T2), and 6 hours after treadmill (T3) were significantly higher than control group (p<0.05), while the group from which its specimen was taken 24 hours after treadmill, was no significantly different (p>0.05). Also on macrophages, NF-κB in treated groups T1, T2, and T3 was significantly higher than control group (p<0.05), but there was no difference between T4 and control group (p>0.05). The level of serum NF-κB was not significantly different between treatment group as well as compared to control group (p>0.05). Serum NF-κB was significantly higher than the level on macrophages and myocytes (p<0.05). Conclusion: This study demonstrated that strenuous physical exercise stimulates the activation of NF-κB that plays a role in vascular inflammation and muscular damage, and may be recovered after resting period.

Keywords: endothelial function, inflammation, NFkB, physical exercise

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Authors: Daniele Losanno, Giorgio Serino

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This paper focuses on parametric analysis of reinforced concrete structures equipped with supplemental damping braces. Practitioners still luck sufficient data for current design of damper added structures and often reduce the real model to a pure damper braced structure even if this assumption is neither realistic nor conservative. In the present study, the damping brace is modelled as made by a linear supporting brace connected in series with the viscous/hysteretic damper. Deformation capacity of existing structures is usually not adequate to undergo the design earthquake. In spite of this, additional dampers could be introduced strongly limiting structural damage to acceptable values, or in some cases, reducing frame response to elastic behavior. This work is aimed at providing useful considerations for retrofit of existing buildings by means of supplemental damping braces. The study explicitly takes into consideration variability of (a) relative frame to supporting brace stiffness, (b) dampers’ coefficient (viscous coefficient or yielding force) and (c) non-linear frame behavior. Non-linear time history analysis has been run to account for both dampers’ behavior and non-linear plastic hinges modelled by Pivot hysteretic type. Parametric analysis based on previous studies on SDOF or MDOF linear frames provide reference values for nearly optimal damping systems design. With respect to bare frame configuration, seismic response of the damper-added frame is strongly improved, limiting deformations to acceptable values far below ultimate capacity. Results of the analysis also demonstrated the beneficial effect of stiffer supporting braces, thus highlighting inadequacy of simplified pure damper models. At the same time, the effect of variable damping coefficient and yielding force has to be treated as an optimization problem.

Keywords: brace stiffness, dissipative braces, non-linear analysis, plastic hinges, reinforced concrete frames

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Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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Authors: Herke Csongor

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The artificial intelligence (AI) has been used in the United States of America in the decisionmaking process of the criminal justice system for decades. In the field of law, including criminal law, AI can provide serious assistance in decision-making in many places. The paper reviews four main areas where AI still plays a role in the criminal justice system and where it is expected to play an increasingly important role. The first area is the predictive policing: a number of algorithms are used to prevent the commission of crimes (by predicting potential crime locations or perpetrators). This may include the so-called linking hot-spot analysis, crime linking and the predictive coding. The second area is the Big Data analysis: huge amounts of data sets are already opaque to human activity and therefore unprocessable. Law is one of the largest producers of digital documents (because not only decisions, but nowadays the entire document material is available digitally), and this volume can only and exclusively be handled with the help of computer programs, which the development of AI systems can have an increasing impact on. The third area is the criminal statistical data analysis. The collection of statistical data using traditional methods required enormous human resources. The AI is a huge step forward in that it can analyze the database itself, based on the requested aspects, a collection according to any aspect can be available in a few seconds, and the AI itself can analyze the database and indicate if it finds an important connection either from the point of view of crime prevention or crime detection. Finally, the use of AI during decision-making in both investigative and judicial fields is analyzed in detail. While some are skeptical about the future role of AI in decision-making, many believe that the question is not whether AI will participate in decision-making, but only when and to what extent it will transform the current decision-making system.

Keywords: artificial intelligence, international criminal cooperation, planning and organizing of the investigation, risk assessment

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Authors: Chia-Ting Chang, Chia-Yu Lin

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We report on the decisive role of iron phosphate (FePO₄), formed in-situ during the electrochemical characterization, played in the electrocatalytic activity, especially its oxygen tolerance of iron oxides towards H₂O₂ reduction. Iron oxides studied including, Nanorod arrays (NRs) of β-FeOOH, γ-Fe₂O₃, α-Fe₂O₃, α-Fe₂O₃ nanosheets (α-Fe₂O₃NS), α-Fe₂O₃ nanoparticles (α-Fe₂O₃NP), were synthesized using chemical bath deposition. The nanostructure was controlled simply by adjusting the composition of precursor solution and reaction duration for CBD process, whereas the crystal phase was controlled by adjusting the annealing temperature. It was found that iron phosphate (FePO₄) was deposited in-situ onto the surface of this nanostructured α-Fe₂O₃ during the electrochemical pretreatment in the phosphate electrolyte, and both FePO₄ and α-Fe₂O₃ showed the activity in catalysing the electrochemical reduction of H₂O₂. In addition, the interaction/compatibility between deposited FePO₄ and iron oxides has a decisive effect on the overall electrocatalytic activity of the resultant electrodes; FePO₄ only showed synergetic effect on the overall electrocatalytic activity of α-Fe₂O₃NR and α-Fe2O₃NS. Both α-Fe₂O₃NR and α-Fe₂O₃NS showed two reduction peaks in phosphate electrolyte containing H₂O₂, one being pH-dependent and related to the electrocatalytic properties of FePO₄, and the other one being pH-independent and only related to the intrinsic electrocatalytic properties of α-Fe₂O₃NR and α-Fe₂O₃NS. However, all iron oxides showed only one pH-independent reductive peak in non-phosphate electrolyte containing H₂O₂. The synergesitic catalysis exerted by FePO₄ with α-Fe₂O₃NR or α-Fe₂O₃NS providing additional oxygen-insensitive active site for H₂O₂ reduction, which allows their applications to electrochemical detection of H₂O₂ without the interference of O₂ involving in oxidase-catalyzed chemical processes.

Keywords: H₂O₂ reduction, Iron oxide, iron phosphate, O₂ tolerance

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Authors: Krish Jhurani

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The research paper presents an in-depth analysis of symmetry properties in linear algebraic systems under the operation of non-canonical scalar multiplication structures, specifically semirings, and near-rings. The objective is to unveil the profound alterations that occur in traditional linear algebraic structures when we replace conventional field multiplication with these non-canonical operations. In the methodology, we first establish the theoretical foundations of non-canonical scalar multiplication, followed by a meticulous investigation into the resulting symmetry properties, focusing on eigenvectors, eigenspaces, and invariant subspaces. The methodology involves a combination of rigorous mathematical proofs and derivations, supplemented by illustrative examples that exhibit these discovered symmetry properties in tangible mathematical scenarios. The core findings uncover unique symmetry attributes. For linear algebraic systems with semiring scalar multiplication, we reveal eigenvectors and eigenvalues. Systems operating under near-ring scalar multiplication disclose unique invariant subspaces. These discoveries drastically broaden the traditional landscape of symmetry properties in linear algebraic systems. With the application of these findings, potential practical implications span across various fields such as physics, coding theory, and cryptography. They could enhance error detection and correction codes, devise more secure cryptographic algorithms, and even influence theoretical physics. This expansion of applicability accentuates the significance of the presented research. The research paper thus contributes to the mathematical community by bringing forth perspectives on linear algebraic systems and their symmetry properties through the lens of non-canonical scalar multiplication, coupled with an exploration of practical applications.

Keywords: eigenspaces, eigenvectors, invariant subspaces, near-rings, non-canonical scalar multiplication, semirings, symmetry properties

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

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Current flooding risk modeling focuses on resilience, defined as the probability of recovery from a severe flooding event. However, the long-term damage to property and well-being by nuisance flooding and its long-term effects on communities are not typically included in risk assessments. An approach was developed to address the probability of recovering from a severe flooding event combined with the probability of community performance during a nuisance event. A consolidated model, namely the conflation flooding recovery (&FR) model, evaluates risk-coping mitigation strategies for communities based on the recovery time from catastrophic events, such as hurricanes or extreme surges, and from everyday nuisance flooding events. The &FR model assesses the variation contribution of each independent input and generates a weighted output that favors the distribution with minimum variation. This approach is especially useful if the input distributions have dissimilar variances. The &FR is defined as a single distribution resulting from the product of the individual probability density functions. The resulting conflated distribution resides between the parent distributions, and it infers the recovery time required by a community to return to basic functions, such as power, utilities, transportation, and civil order, after a flooding event. The &FR model is more accurate than averaging individual observations before calculating the mean and variance or averaging the probabilities evaluated at the input values, which assigns the same weighted variation to each input distribution. The main disadvantage of these traditional methods is that the resulting measure of central tendency is exactly equal to the average of the input distribution’s means without the additional information provided by each individual distribution variance. When dealing with exponential distributions, such as resilience from severe flooding events and from nuisance flooding events, conflation results are equivalent to the weighted least squares method or best linear unbiased estimation. The combination of severe flooding risk with nuisance flooding improves flood risk management for highly populated coastal communities, such as in South Florida, USA, and provides a method to estimate community flood recovery time more accurately from two different sources, severe flooding events and nuisance flooding events.

Keywords: community resilience, conflation, flood risk, nuisance flooding

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: Agatha Bebbington, Terry Tetley, Kathryn Hadler

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Background: Astronauts will set foot on the Moon later this decade, and are at high risk of lunar dust inhalation. Freshly-fractured lunar dust produces reactive oxygen species in solution, which are known to cause cellular damage and inflammation. Cytotoxicity and inflammatory mediator release was measured in pulmonary alveolar epithelial cells (cells that line the gas-exchange zone of the lung) exposed to a lunar dust simulant, LMS-1. It was hypothesised that freshly-fractured LMS-1 would result in increased cytotoxicity and inflammatory mediator release, owing to the angular morphology and high reactivity of fractured particles. Methods: A human alveolar epithelial type 1-like cell line (TT1) and a human macrophage-like cell line (THP-1) were exposed to 0-200μg/ml of unground, aged-ground, and freshly-ground LMS-1 (screened at <22μm). Cell viability, cytotoxicity, and inflammatory mediator release (IL-6, IL-8) were assessed using MMT, LDH, and ELISA assays, respectively. LMS-1 particles were characterised for their size, surface area, and morphology before and after grinding. Results: Exposure to LMS-1 particles did not result in overt cytotoxicity in either TT1 epithelial cells or THP-1 macrophage-like cells. A dose-dependent increase in IL-8 release was observed in TT1 cells, whereas THP-1 cell exposure, even at low particle concentrations, resulted in increased IL-8 release. Both cytotoxic and pro-inflammatory responses were most marked and significantly greater in TT1 and THP-1 cells exposed to freshly-fractured LMS-1. Discussion: LMS-1 is a novel lunar dust simulant; this is the first study to determine its toxicological effects on respiratory cells in vitro. An increased inflammatory response in TT1 and THP-1 cells exposed to ground LMS-1 suggests that low particle size, increased surface area, and angularity likely contribute to toxicity. Conclusions: Evenlow levels of exposure to LMS-1 could result in alveolar inflammation. This may have pathological consequences for astronauts exposed to lunar dust on future long-duration missions. Future research should test the effect of low-dose, intermittent lunar dust exposure on the respiratory system.

Keywords: lunar dust, LMS-1, lunar dust simulant, long-duration space travel, lunar dust toxicity

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Prittesh Patel, Rushabh Shah, Krishnamurthy Ramar, Vakulbhushan Bhaskar

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The present research work aims at finding genetic differences in the genomes of sugarcane red rot isolates Colletotrichum falcatum Went using Random Amplified Polymorphic DNA (RAPD) and interspersed simple sequence repeat (ISSR) molecular markers. Ten isolates of C. falcatum isolated from different red rot infected sugarcane cultivars stalk were used in present study. The amplified bands were scored across the lanes obtained in 15 RAPD primes and 21 ISSR primes successfully. The data were analysed using NTSYSpc 2.2 software. The results showed 80.6% and 68.07% polymorphism in RPAD and ISSR analysis respectively. Based on the RAPD analysis, ten genotypes were grouped into two major clusters at a cut-off value of 0.75. Geographically distant C. falcatum isolate cfGAN from south Gujarat had a level of similarity with Coimbatore isolate cf8436 presented on separate clade of bootstrapped dendrograms. First and second cluster consisted of five and three isolates respectively, indicating the close relation among them. The 21 ISSR primers produced 119 distinct and scorable loci in that 38 were monomorphic. The number of scorable loci for each primer varied from 2 (ISSR822) to 8 (ISSR807, ISSR823 and ISSR15) with an average of 5.66 loci per primer. Primer ISSR835 amplified the highest number of bands (57), while only 16 bands were obtained by primers ISSR822. Four primers namely ISSR830, ISSR845, ISSR4 and ISSR15 showed the highest value of percentage of polymorphism (100%). The results indicated that both of the marker systems RAPD and ISSR, individually can be effectively used in determination of genetic relationship among C falcatum accessions collected from different parts of south Gujarat.

Keywords: Colletotrichum falcatum, ISSR, RAPD, Red Rot

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Authors: Sanjeewa Seneviratne, Ian Campbell, Nina Scott, Ross Lawrenson

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Introduction: Indigenous Māori women experience a 60% higher breast cancer mortality rate compared with European women in New Zealand. We explored the impact of difference in the rate of screen detected breast cancer between Māori and European women on more advanced disease at diagnosis and lower survival in Māori women. Methods: All primary in-situ and invasive breast cancers diagnosed in screening age women (as defined by the New Zealand National Breast Cancer Screening Programme) between 1999 and 2012 in the Waikato area were identified from the Waikato Breast Cancer Register and the national screening database. Association between screen versus non-screen detection and cancer stage at diagnosis and survival were compared by ethnicity and socioeconomic deprivation. Results: Māori women had 50% higher odds of being diagnosed with more advance staged cancer compared with NZ European women, a half of which was explained by the lower rate of screen detected cancer in Māori women. Significantly lower breast cancer survival rates were observed for Māori compared with NZ European and most deprived compared with most affluent socioeconomic groups for symptomatically detected breast cancer. No significant survival differences by ethnicity or socioeconomic deprivation were observed for screen detected breast cancer. Conclusions: Low rate of screen detected breast cancer appears to be a major contributor for more advanced stage disease at diagnosis and lower breast cancer survival in Māori compared with NZ European women. Increasing screening participation for Māori has the potential to substantially reduce breast cancer mortality inequity between Māori and NZ European women.

Keywords: breast cancer, screening, ethnicity, inequity

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Authors: Gulnaz Khan, Meha F. Aftab, Munazza Murtaza, Rizwana S. Waraich

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Advanced glycation end products (AGEs) precursor and its abnormal accumulation cause damage to various tissues and organs. AGEs have pathogenic implication in several diseases including diabetes. Existing AGEs inhibitors are not in clinical use, and there is a need for development of novel inhibitors. The present investigation aimed at identifying the novel AGEs inhibitors and assessing their mechanism of action for treating insulin resistance in mice model of diabetes. Novel derivatives of benzylidene of indan-1,3-dione were synthesized. The compounds were selected to study their action mechanism in improving insulin resistance, in vitro, in human hepatocytes and murine adipocytes and then, in vivo, in mice genetic model of diabetes (db/db). Mice were treated with novel derivatives of benzylidene of indane 1,3-dione. AGEs mediated ROS production was measured by dihydroethidium fluorescence assay. AGEs level in the serum of treated mice was observed by ELISA. Gene expression of receptor for AGEs (RAGE), PPAR-gamma, TNF-alpha and GLUT-4 was evaluated by RT-PCR. Glucose uptake was measured by fluorescent method. Microscopy was used to analyze glycogen synthesis in muscle. Among several derivatives of benzylidene of indan-1,3-dione, IDD-24, demonstrated highest inhibition of AGESs. IDD-24 significantly reduced AGEs formation and expression of receptor for advanced glycation end products (RAGE) in fat, liver of db/db mice. Suppression of AGEs mediated ROS production was also observed in hepatocytes and fat cell, after treatment with IDD-24. Glycogen synthesis was increased in muscle tissue of mice treated with IDD-24. In adipocytes, IDD-24 prevented AGEs induced reduced glucose uptake. Mice treated with IDD-24 exhibited increased glucose tolerance, serum adiponectin levels and decreased insulin resistance. The result of present study suggested that IDD-24 can be a possible treatment target to address glycotoxins induced insulin resistance.

Keywords: advance glycation end product, hyperglycemia, indan-1, 3-dione, insulin resistance

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Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 161

Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS

Procedia PDF Downloads 196

Authors: Chang Yu Chuan

Abstract:

Background and Aim: Pressure sore is not only the consequence of any gradual damage of the skin leading to tissue defects but also an important indicator of clinical care. If hospitalized patients develop pressure sores without proper care, it would result in delayed healing, wound infection, increase patient physical pain, prolonged hospital stay and even death, which would have a negative impact on the quality of care and also increase nursing manpower and medical costs. This project is aimed at decreasing the incidence of pressure sore in one ward of internal medicine. Our data showed 53 cases (0.61%) of pressure sore in 2015, which exceeded the average (0.5%) of Taiwan Clinical Performance Indicator (TCPI) for medical centers. The purpose of this project is to reduce the incidence rate of pressure sore in the ward. After data collection and analysis from January to December 2016, the reasons of developing pressure sore were found: 1. Lack of knowledge to prevent pressure among nursing staffs; 2. No relevant courses about preventing pressure ulcers and pressure wound care being held in this unit; 3. Low complete rate of pressure sore care education that family members should receive from nursing staffs; 4. Decompression equipment is not enough; 5. Lack of standard procedures for body-turning and positioning care. After team members brainstorming, several strategies were proposed, including holding in-service education, pressure sore care seed training, purchasing decompression mattress and memory pillows, designing more elements of health education tools, such as health education pamphlet, posters and multimedia films of body-turning and positioning demonstration, formulation and promotion of standard operating procedures. In this way, nursing staffs can understand the body-turning and positioning guidelines for pressure sore prevention and enhance the quality of care. After the implementation of this project, the pressure sore density significantly decreased from 0.61%(53 cases) to 0.45%(28 cases) in this ward. The project shows good results and good example for nurses working at the ward and helps to enhance quality of care.

Keywords: body-turning and positioning, incidence density, nursing, pressure sore

Procedia PDF Downloads 253

Authors: Petcharat  Kerdonfag, Surasak Taneepanichskul, Winai Wadwongtham

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Industrial noise is usually considered as the main impact of the environmental health and safety because its exposure can cause permanently serious hearing damage. Despite providing strictly hearing protection standards and campaigning extensively encouraging public health awareness among industrial workers in Thailand, hazard noise-induced hearing loss has dramatically been massive obstacles for workers’ health. The aims of the study were to explore and specify the hearing threshold levels among steel industrial workers responsible in which higher noise levels of work zone and to examine the relationships of hearing loss and workers’ age and the length of employment in Samut Prakan province, Thailand. Cross-sectional study design was done. Ninety-three steel industrial workers in the designated zone of higher noise (> 85dBA) with more than 1 year of employment from two factories by simple random sampling and available to participate in were assessed by the audiometric screening at regional Samut Prakan hospital. Data of doing screening were collected from October to December, 2016 by the occupational medicine physician and a qualified occupational nurse. All participants were examined by the same examiners for the validity. An Audiometric testing was performed at least 14 hours after the last noise exposure from the workplace. Workers’ age and the length of employment were gathered by the developed occupational record form. Results: The range of workers’ age was from 23 to 59 years, (Mean = 41.67, SD = 9.69) and the length of employment was from 1 to 39 years, (Mean = 13.99, SD = 9.88). Fifty three (60.0%) out of all participants have been exposing to the hazard of noise in the workplace for more than 10 years. Twenty-three (24.7%) of them have been exposing to the hazard of noise less than or equal to 5 years. Seventeen (18.3%) of them have been exposing to the hazard of noise for 5 to 10 years. Using the cut point of less than or equal to 25 dBA of hearing thresholds, the average means of hearing thresholds for participants at 4, 6, and 8 kHz were 31.34, 29.62, and 25.64 dB, respectively for the right ear and 40.15, 32.20, and 25.48 dB for the left ear, respectively. The more developing age of workers in the work zone with hazard of noise, the more the hearing thresholds would be increasing at frequencies of 4, 6, and 8 kHz (p =.012, p =.026, p =.024) for the right ear, respectively and for the left ear only at the frequency 4 kHz (p =.009). Conclusion: The participants’ age in the hazard of noise work zone was significantly associated with the hearing loss in different levels while the length of participants’ employment was not significantly associated with the hearing loss. Thus hearing threshold levels among industrial workers would be regularly assessed and needed to be protected at the beginning of working.

Keywords: hearing threshold levels, hazard of noise, hearing loss, audiometric testing

Procedia PDF Downloads 212

Authors: S. Koppikar, P. Kulkarni, D. Ingale , N. Wagh, S. Deshpande, A. Mahajan, A. Harsulkar

Abstract:

Crucial role of reactive oxygen species (ROS) in the progression Osteoarthritis (OA) pathogenesis has been endorsed several times though its exact mechanism remains unclear. Oxidative stress is known to instigate classical stress factors such as cytokines, chemokines and ROS, which hampers cartilage remodelling process and ultimately results in worsening the disease. Synovial fluid (SF) is a biological communicator between cartilage and synovium that accumulates redox and biochemical signalling mediators. The present work attempts to measure several oxidative stress markers in the synovial fluid obtained from knee OA patients with varying degree of disease severity. Thirty OA and five Meniscal-tear (MT) patients were graded using Kellgren-Lawrence scale and assessed for Nitric oxide (NO), Nitrate-Nitrite (NN), 2,2-diphenyl-1-picrylhydrazyl (DPPH), Ferric Reducing Antioxidant Potential (FRAP), Catalase (CAT), Superoxide dismutase (SOD) and Malondialdehyde (MDA) levels for comparison. Out of various oxidative markers studied, NO and SOD showed significant difference between moderate and severe OA (p= 0.007 and p= 0.08, respectively), whereas CAT demonstrated significant difference between MT and mild group (p= 0.07). Interestingly, NN revealed statistically positive correlation with OA severity (p= 0.001 and p= 0.003). MDA, a lipid peroxidation by-product was estimated maximum in early OA when compared to MT (p= 0.06). However, FRAP did not show any correlation with OA severity or MT control. NO is an essential bio-regulatory molecule essential for several physiological processes, and inflammatory conditions. However, due to its short life, exact estimation of NO becomes difficult. NO and its measurable stable products are still it is considered as one of the important biomarker of oxidative damage. Levels of NO and nitrite-nitrate in SF of patients with OA indicated its involvement in the disease progression. When SF groups were compared, a significant correlation among moderate, mild and MT groups was established. To summarize, present data illustrated higher levels of NO, SOD, CAT, DPPH and MDA in early OA in comparison with MT, as a control group. NN had emerged as a prognostic bio marker in knee OA patients, which may act as futuristic targets in OA treatment.

Keywords: antioxidant, knee osteoarthritis, oxidative stress, synovial fluid

Procedia PDF Downloads 464

Authors: Mukesh Lal Das, Muthukumar Muthuchamy

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Climate change Adaptation strategy (AS) is a scientific approach to dealing with the impacts of climate change (CC). Efforts are being made to contain the global emission of greenhouse gas within threshold limits, thereby limiting the rise of global temperature to an optimal level. Global Climate change is a spontaneous process; therefore, reversing the damage would take decades. The climate change adaptation strategy recommended by various stakeholders could be a key to resilience for biodiversity. The Indian Government has constituted the panel to synthesize the climate change action report at the federal and state levels. This review scavenged the published literature on the Western Ghats hotspots. And highlight the adaptation strategy recommended by diverse scientific actors to conserve biodiversity. It also reviews the grey literature adopted by state and federal governments and its effectiveness in mitigating the impacts on biodiversity. We have narrowed the scope of interest to the state action report by 6 Indian states such as Gujarat, Maharashtra, Goa, Karnataka, Kerala and Tamil Nadu, which host Western Ghats global biodiversity hotspot. Western Ghats(WGs) act as the water tower to the peninsular part of India, and its extensive watershed caters to the water demand of the Industry sector, Agriculture and urban community. Conservation of WGs is the key to the prosperity of Peninsular India. The global scientific community suggested more than 600+ Climate change adaptation strategies for the policymakers, stakeholders, and other state actors to take proactive actions. The preliminary analysis of the federal and the state action plan on climate change in the wake of CC indicate inadequacy in motion as per recommended scientific adaptation strategies. Tamil Nadu and Kerala state constitute nine effective adaptation strategies out of the 40+ recommended for Western Ghats conservation. And other four states' adaptation strategies are deficient, confusing and vague. Western Ghats' resilience capacity will soon or might have reached its threshold, and the frequency of severe drought and flash floods might upsurge manifold in the decades to come. The lack of a clear roadmap to climate change adaptation strategies in the federal and state action stirred us to identify the gap and address it by offering a holistic approach to WGs biodiversity conservation.

Keywords: adaptation strategy, biodiversity conservation, climate change, resilience, Western Ghats

Procedia PDF Downloads 92

Authors: F. Z. Tighilt, N. Belhaneche-Bensemra, S. Belhousse, S. Sam, K. Lasmi, N. Gabouze

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Recently, the gold nanoparticles (Au NPs) became an active multidisciplinary research topic. First, Au thin films fabricated by alkylthiol-functionalized Au NPs were found to have vapor sensitive conductivities, they were hence widely investigated as electrical chemiresistors for sensing different vapor analytes and even organic molecules in aqueous solutions. Second, Au thin films were demonstrated to have speciallocalized surface plasmon resonances (LSPR), so that highly ordered 2D Au superlattices showed strong collective LSPR bands due to the near-field coupling of adjacent nanoparticles and were employed to detect biomolecular binding. Particularly when alkylthiol ligands were replaced by thiol-terminated polymers, the resulting polymer-modified Au NPs could be readily assembled into 2D nanostructures on solid substrates. Monolayers of polystyrene-coated Au NPs showed typical dipolar near-field interparticle plasmon coupling of LSPR. Such polymer-modified Au nanoparticle films have an advantage that the polymer thickness can be feasibly controlled by changing the polymer molecular weight. In this article, the effect of tin-doped indium oxide (ITO) coatings on the plasmonic properties of ITO interfaces modified with gold nanostructures (Au NSs) is investigated. The interest in developing ITO overlayers is multiple. The presence of a con-ducting ITO overlayer creates a LSPR-active interface, which can serve simultaneously as a working electrode in an electro-chemical setup. The surface of ITO/ Au NPs contains hydroxyl groups that can be used to link functional groups to the interface. Here the covalent linking of nickel /Au NSs/ITO hybrid LSPR platforms will be presented.

Keywords: conducting polymer, metal nanoparticles (NPs), LSPR, poly (3-(pyrrolyl)–carboxylic acid), polypyrrole

Procedia PDF Downloads 258

Authors: Chairul Fajar, Muhammad Nur Hidayat, Muksalmina

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The issue of Over Dimension Over Loading (ODOL) in Indonesia remains a significant challenge, causing traffic accidents, disrupting traffic flow, accelerating road damage, and potentially leading to bridge collapses. Klaten Regency, located on the slopes of Mount Merapi along the Woro River in Kemalang District, has potential Class C excavation materials such as sand and stone. Data from the Klaten Regency Transportation Department indicates that ODOL violations account for 72%, while non-violating vehicles make up only 28%. ODOL involves modifying factory-standard vehicles beyond the limits specified in the Type Test Registration Certificate (SRUT) to save costs and travel time. This study aims to develop a prototype ‘Sabrang’ monitoring system based on Arduino Mega to control and monitor ODOL freight transportation in the mining of Class C excavation materials in Klaten Regency. The prototype is designed to automatically measure the dimensions and weight of objects using a microcontroller. The data analysis techniques used in this study include the Normality Test and Paired T-Test, comparing sensor measurement results on scaled objects. The study results indicate differences in measurement validation under room temperature and ambient temperature conditions. Measurements at room temperature showed that the majority of H0 was accepted, meaning there was no significant difference in measurements when the prototype tool was used. Conversely, measurements at ambient temperature showed that the majority of H0 was rejected, indicating a significant difference in measurements when the prototype tool was used. In conclusion, the ‘Sabrang’ monitoring system prototype is effective for controlling ODOL, although measurement results are influenced by temperature conditions. This study is expected to assist in the monitoring and control of ODOL, thereby enhancing traffic safety and road infrastructure.

Keywords: over dimension over loading, prototype, microcontroller, Arduino, normality test, paired t-test

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

Abstract:

Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a real-time simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three Velmex XSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: surgical robot, haptic feedback, MATLAB, strain gage, simulink

Procedia PDF Downloads 522

Authors: Irfan Ahmad Afip

Abstract:

This main research objective is to accurately identify the possibility for a Leptospirosis outbreak severity of a certain area based on its input features into a multivariate regression model. The research question is the possibility of an outbreak in a specific area being influenced by this feature, such as social demographics and hydrometeorological extremes. If the occurrence of an outbreak is being subjected to these features, then the epidemic severity for an area will be different depending on its environmental setting because the features will influence the possibility and severity of an outbreak. Specifically, this research objective was three-fold, namely: (a) to identify the relevant multivariate features and visualize the patterns data, (b) to develop a multivariate regression model based from the selected features and determine the possibility for Leptospirosis outbreak in an area, and (c) to compare the predictive ability of multivariate regression model and machine learning algorithms. Several secondary data features were collected locations in the state of Negeri Sembilan, Malaysia, based on the possibility it would be relevant to determine the outbreak severity in the area. The relevant features then will become an input in a multivariate regression model; a linear regression model is a simple and quick solution for creating prognostic capabilities. A multivariate regression model has proven more precise prognostic capabilities than univariate models. The expected outcome from this research is to establish a correlation between the features of social demographic and hydrometeorological with Leptospirosis bacteria; it will also become a contributor for understanding the underlying relationship between the pathogen and the ecosystem. The relationship established can be beneficial for the health department or urban planner to inspect and prepare for future outcomes in event detection and system health monitoring.

Keywords: geographical information system, hydrometeorological, leptospirosis, multivariate regression

Procedia PDF Downloads 101

Authors: Asma Chbani, Douaa Salim, Josephine Al Alam, Pascale De Caro

Abstract:

Penicillium digitatum, the causal agent of citrus green mold, is responsible for 90% of post-harvest losses. Chemical fungicides remain the most used products for protection against this pathogen but are also responsible for damage to human health and the environment. The aim of this study is to evaluate the ability of Spinacia oleracea extract to serve as biological control agents, an alternative to harmful synthetic fungicides, against orange decay for storing fruit caused by P. digitatum. In this study, we studied the implication of a crude extract of a green plant, Spinacia oleracea, in the protection of oranges against P. digitatum. Thus, in vivo antifungal tests as well as adhesion test were done. For in vivo antifungal test, oranges were pulverized with the prepared crude extracts at different concentrations ranged from 25 g L⁻¹ to 200 g L⁻¹, contaminated by the fungus and then observed during 8 weeks for their macroscopic changes at 24°C. For adhesion test, the adhesion index is defined as the number of Penicillium digitatum spores fixed per orange cell. An index greater than 25 is the indicator of a strong adhesion, whereas for an index less than 10, the adhesion is low. Ten orange cells were examined in triplicate for each extract, and the averages of adherent cells were calculated. Obtained results showed an inhibitory activity of the Penicillium development with the aqueous extract of dry Spinacia oleracea with a concentration of 50 g L⁻¹ considered as the minimal protective concentration. The prepared extracts showed a greater inhibition of the development of P. digitatum up to 10 weeks, even greater than the fungicide control Nystatin. Adhesion test’s results showed that the adhesion of P. digitatum spores to the epidermal cells of oranges in the presence of the crude spinach leaves extract is weak; the mean of the obtained adhesion index was estimated to 2.7. However, a high adhesion was observed with water used a negative control. In conclusion, all these results confirm that the use of this green plant highly rich in chlorophyll having several phytotherapeutic activities, could be employed as a great treatment for protection of oranges against mold and also as an alternative for chemical fungicides.

Keywords: Penicillium digitatum, Spinacia oleracea, oranges, biological control, postharvest diseases

Procedia PDF Downloads 160