Search results for: forensic accounting & fraud detection

Authors: Nader Nciri, Suil Song, Namho Kim, Namjun Cho

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Properties and compositions of bitumen and bitumen-derived liquids have significant influences on the selection of recovery, upgrading and refining processes. Optimal process conditions can often be directly related to these properties. The end uses of bitumen and bitumen products are thus related to their compositions. Because it is not possible to conduct a complete analysis of the molecular structure of bitumen, characterization must be made in other terms. The present paper focuses on physico-chemical analysis of two different types of bitumens. These bitumen samples were chosen based on: the original crude oil (sand oil and crude petroleum), and mode of process. The aim of this study is to determine both the manufacturing effect on chemical species and the chemical organization as a function of the type of bitumen sample. In order to obtain information on bitumen chemistry, elemental analysis (C, H, N, S, and O), heavy metal (Ni, V) concentrations, IATROSCAN chromatography (thin layer chromatography-flame ionization detection), FTIR spectroscopy, and 1H NMR spectroscopy have all been used. The characterization includes information about the major compound types (saturates, aromatics, resins and asphaltenes) which can be compared with similar data for other bitumens, more importantly, can be correlated with data from petroleum samples for which refining characteristics are known. Examination of Asphalt Ridge froth bitumen showed that it differed significantly from representative petroleum pitches, principally in their nonhydrocarbon content, heavy metal content and aromatic compounds. When possible, properties and composition were related to recovery and refining processes. This information is important because of the effects that composition has on recovery and processing reactions.

Keywords: froth bitumen, oil sand, asphalt ridge, petroleum pitch, thin layer chromatography-flame ionization detection, infrared spectroscopy, 1H nuclear magnetic resonance spectroscopy

Procedia PDF Downloads 427

Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: Abdela Bulbula

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Background: Marek’s disease virus is a devastating infection, causing high morbidity and mortality in chickens in Ethiopia. Methods: The current study was conducted from March to November, 2021 with the general objective of performing antemortem and postmortem, isolation, and molecular detection of Marek’s disease virus from outbreak cases in southwestern Ethiopia. Accordingly, based on outbreak information reported from the study sites namely, Bedelle, Yayo, and Bonga towns in southwestern Ethiopia, 50 sick chickens were sampled. The backyard and intensive farming systems of chickens were included in the sampling and priorities were given for chickens that showed clinical signs that are characteristics of Marek’s disease. Results: By clinical examinations, paralysis of legs and wings, gray eye, loss of weight, difficulty in breathing, and depression were recorded on all chickens sampled for this study and death of diseased chickens was observed. In addition, enlargement of the spleen and gross lesions of the liver and heart were recorded during postmortem examination. The death of infected chickens was observed in both vaccinated and non-vaccinated flocks. Out of 50 pooled feather follicle samples, Marek’s disease virus was isolated from 14/50 (28%) by cell culture method and out of six tissue samples, the virus was isolated from 5/6(83.30%). By Real time polymerization chain reaction technique, which was targeted to detect the Meq gene, Marek’s disease virus was detected from 18/50 feather follicles which accounts for 36% of sampled chickens. Conclusion: In general, the current study showed that the circulating Marek’s disease virus in southwestern Ethiopia was caused by the oncogenic Gallid herpesvirus-2 (Serotype-1). Further research on molecular characterization of revolving virus in current and other regions is recommended for effective control of the disease through vaccination.

Keywords: Ethioi, Marek's disease, isolation, molecular

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Authors: S. M. Rashed Ul Islam, Shahina Tabassum, Afsana Anwar Miti

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Objective: HIV testing and counseling center (HTC) is an important component of the HIV/AIDS detection, prevention and control interventions. The service was first initiated at the Department of Virology, Bangabandhu Sheikh Mujib Medical University (BSMMU) since the first case detection in 1989. The present study aimed to describe the demographic profile among the attendees tested HIV positive. Methods: The present study was carried out among 219 HIV positive cases detected through screening at the Department of Virology of BSMMU during the year of 2012-2016. Data were collected through pre-structured written questionnaire during the counseling session. Data were expressed as frequency and percentages and analyzed using SPSS v20.0 program. Results: Out of 219 HIV cases detected, 77.6% were males, and 22.4% were females with a mean age (mean±SD) of 35.46±9.46 years. Among them, 70.7% belonged to the 26-45 age groups representing the sexually active age. The majority of the cases were married (86.3%) and 49.8% had primary level of education whereas, 8.7% were illiterate. Nearly 42% of cases were referred from Chittagong division (south-east part of the country) followed by Dhaka division (35.6%). The bulk of study population admitted to involvement in high-risk behaviour (90%) in the past and 42% of them had worked overseas. The Pearson Chi-square (χ2) analysis revealed significant relationship of gender with marital (χ2=7.88 at 2% level) and occupation status (χ2=120.48 at 6% level); however, no association was observed with risk behaviour and educational status. Recommendations: HIV risk behavior was found to be a prime source for HIV infection among the study population. So, there is need for health education and awareness program to bring about behavioral changes to halt the yearly increase of new cases in the country with special attention to our overseas workers on HIV/AIDS risk and safety.

Keywords: Bangladesh, health education, HIV testing and counseling (HTC), HIV/AIDS, risk behavior

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Authors: M. Taleb, G. Tail, F. Z. Kara, B. Djedouani T. Moussa

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Necrophagous insects usually colonize cadavers within a short time after death. However, they are influenced by weather conditions, and their distribution and activity vary according to different time scales, which can affect the post-mortem interval (PMI) estimation. As no data have been published in Algeria on necrophagous insects visiting corpses, two field surveys were conducted in July 2012 and March 2013 at the National Institute for Criminalistics and Criminology (INCC) using rabbit carcasses (Oryctolagus cuniculus L.). The trials were designed to identify the necrophagous Diptera fauna of Algiers, Algeria and examine their variations according to environmental variables. Four hundred and eighteen Diptera adults belonging to five families were captured during this study. The species which were identified on human corpses in different regions of Algeria were also observed on the rabbit carcasses. Although seasonal variations of the species were observed, their abundance did not significantly vary between the two seasons. In addition to seasonal effects, the ambient temperature, the wind speed, and precipitation affect the number of trapped flies. These conclusions highlight the necessity of considering the environmental factors at a scene to estimate the post-mortem interval accurately. It is hoped that these findings provide basic information regarding the necrophagous Diptera fauna of Algeria.

Keywords: forensic entomology, necrophagous diptera, post-mortem interval, abiotic factors, Algeria

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Authors: R. Zh. Abdukerim, D. A. Absatarova, A. T. Aitbayeva, M. A. Askarova, S. T. Turuspekova, E. V. Zhunus

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The resilience of agricultural systems at the global level to climate change and their ability to recover determines the prospects for food security on a global scale. Since climate change will lead to changes in temperatures, precipitation, weather conditions and mass outbreaks of harmful organisms. The issue of adaptation to climate change in the agricultural sector is one of the priorities of Kazakhstan's Development Strategy for the period up to 2050. Since Kazakhstan is an agroindustrial country in which agriculture plays an important economic role. Kazakhstan is the largest potato producer in Central Asia, accounting for about 60% of the total vegetable production, which determines the urgency of solving the problem of increasing yields and quality. The control harmful organisms plays an important role in solving this issue. Due to the fact that climate change can lead to an increase in the number of harmful organisms and, accordingly, to a complete loss of harvest.

Keywords: potato pests, Colorado potato beetle, soil pests, global climate change

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Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

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Authors: R. Abdeldjebar, B. Labbaci, L. Missoum, B. Moudden, M. Djermane

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The basic components of a composite material made him very sensitive to damage, which requires techniques for detecting damage reliable and efficient. This work focuses on the detection of damage by vibration analysis, whose main objective is to exploit the dynamic response of a structure to detect understand the damage. The experimental results are compared with those predicted by numerical models to confirm the effectiveness of the approach.

Keywords: experimental, composite, vibration analysis, damage

Procedia PDF Downloads 674

Authors: Christine Fräulin, Daniela Schurr, Hamed Shahidi Rad, Gerrit Waters, Günter Rinke, Roland Dittmeyer, Michael Nilles

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The reaction mechanisms of many liquid-phase reactions in organic chemistry have not yet been sufficiently clarified. Process conditions of several hundred degrees celsius and pressures to ten megapascals complicate the sampling and the determination of kinetic data. Space resolved in-situ measurements promises new insights. A non-invasive in-situ measurement technique has the advantages that no sample preparation is necessary, there is no change in sample mixture before analysis and the sampling do no lead to interventions in the flow. Thus, the goal of our research was the development of a contact-free spatially resolved measurement technique for kinetic studies of liquid phase reaction under process conditions. Therefore we used laser Raman spectroscopy combined with an optical transparent microchannel reactor. To show the performance of the system we choose the oxidation of cyclohexane as sample reaction. Cyclohexane oxidation is an economically important process. The products are intermediates for caprolactam and adipic acid, which are starting materials for polyamide 6 and 6.6 production. To maintain high selectivities of 70 to 90 %, the reaction is performed in industry at a low conversion of about six percent. As Raman spectroscopy is usually very selective but not very sensitive the detection of the small product concentration in cyclohexane oxidation is quite challenging. To meet these requirements, an optical experimental setup was optimized to determine the concentrations by laser Raman spectroscopy with respect to good detection sensitivity. With this measurement technique space resolved kinetic studies of uncatalysed and homogeneous catalyzed cyclohexane oxidation were carried out to obtain details about the reaction mechanism.

Keywords: in-situ laser raman spectroscopy, space resolved kinetic measurements, homogeneous catalysis, chemistry

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Authors: Mrinal Kanti Bhowmik, Usha Rani Gogoi Jr., Anjan Kumar Ghosh, Debotosh Bhattacharjee

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In the last few decades, breast thermography has achieved an average sensitivity and specificity of 90% for breast tumor detection. Breast thermography is a non-invasive, cost-effective, painless and radiation-free breast imaging modality which makes a significant contribution to the evaluation and diagnosis of patients, suspected of having breast cancer. An abnormal breast thermogram may indicate significant biological risk for the existence or the development of breast tumors. Breast thermography can detect a breast tumor, when the tumor is in its early stage or when the tumor is in a dense breast. The infrared breast thermography is very sensitive to environmental changes for which acquisition of breast thermography should be performed under strictly controlled conditions by undergoing some standard protocols. Several factors like air, temperature, humidity, etc. are there to be considered for characterizing thermal images as an imperative tool for detecting breast cancer. A detailed study of various breast thermogram acquisition protocols adopted by different researchers in their research work is provided here in this paper. After going through a rigorous study of different breast thermogram acquisition protocols, a new standard breast thermography acquisition setup is proposed here in this paper for proper and accurate capturing of the breast thermograms. The proposed breast thermogram acquisition setup is being built in the Radiology Department, Agartala Government Medical College (AGMC), Govt. of Tripura, Tripura, India. The breast thermograms are captured using FLIR T650sc thermal camera with the thermal sensitivity of 20 mK at 30 degree C. The paper is an attempt to highlight the importance of different critical parameters of breast thermography like different thermography views, patient preparation protocols, acquisition room requirements, acquisition system requirements, etc. This paper makes an important contribution by providing a detailed survey and a new efficient approach on breast thermogram capturing.

Keywords: acquisition protocol, breast cancer, breast thermography, infrared thermography

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Authors: Siti Sofo Ismail, Siti Noraina Wahida Mohd Alwi, Mohamad Hafiz Ameran, Masrudin M. Yusoff

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Locating clandestine cadaver is crucially important in forensic investigations. However, it requires a lot of man power, costly and time consuming. Therefore, the development of a new method to locate the clandestine graves is urgently needed as the cases involve burial of cadaver in different types of soils under tropical climates are still not well explored. This study focused on the burial in mangrove and oil palm plantation soils, comparing the fatty acid distributions in different soil acidities. A stimulated burial experiment was conducted using domestic pig (Sus scrofa) to substitute human tissues. Approximately 20g of pig fatty flesh was allowed to decompose in mangrove and oil palm plantation soils, mimicking burial in a shallow grave. The associated soils were collected at different designated sampling points, corresponding different decomposition stages. Modified Bligh-Dyer Extraction method was applied to extract the soil free fatty acids. Then, the obtained free fatty acids were analyzed with gas chromatography-flame ionization (GC-FID). A similar fatty acid distribution was observed for both mangrove and oil palm plantations soils. Palmitic acid (C₁₆) was the most abundance of free fatty acid, followed by stearic acid (C₁₈). However, the concentration of palmitic acid (C₁₆) higher in oil palm plantation compare to mangrove soils. Conclusion, the decomposition rate of cadaver can be affected by different type of soils.

Keywords: clandestine grave, burial, soils, free fatty acid

Procedia PDF Downloads 399

Authors: Vivek B. Ravindran, Aravind Surapaneni, Rebecca Traub, Sarvesh K. Soni, Andrew S. Ball

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Parasitic diseases have a devastating, long-term impact on human health and welfare. More than two billion people are infected with soil-transmitted helminths (STHs), including the roundworms (Ascaris), hookworms (Necator and Ancylostoma) and whipworm (Trichuris) with majority occurring in the tropical and subtropical regions of the world. Despite its low prevalence in developed countries, the removal of STHs from wastewater remains crucial to allow the safe use of sludge or recycled water in agriculture. Conventional methods such as incubation and optical microscopy are cumbersome; consequently, the results drastically vary from person-to-person observing the ova (eggs) under microscope. Although PCR-based methods are an alternative to conventional techniques, it lacks the ability to distinguish between viable and non-viable helminth ova. As a result, wastewater treatment industries are in major need for radically new and innovative tools to detect and quantify STHs eggs with precision, accuracy and being cost-effective. In our study, we focus on the following novel and innovative techniques: -Recombinase polymerase amplification and Surface enhanced Raman spectroscopy (RPA-SERS) based detection of helminth ova. -Use of metal nanoparticles and their relative nanozyme activity. -Colorimetric detection, differentiation and enumeration of genera of helminth ova using hydrolytic enzymes (chitinase and lipase). -Propidium monoazide (PMA)-qPCR to detect viable helminth ova. -Modified assay to recover and enumerate helminth eggs from fresh raw sewage. -Transcriptome analysis of ascaris ova in fresh raw sewage. The aforementioned techniques have the potential to replace current conventional and molecular methods thereby producing a standard protocol for the determination and enumeration of helminth ova in sewage sludge.

Keywords: colorimetry, helminth, PMA-QPCR, nanoparticles, RPA, viable

Procedia PDF Downloads 299

Authors: C. Vázquez, L. M. Gigirey, C. P. del Oro, S. Seoane

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Early detection of visual problems plays a key role in the aging process. However, although vision problems are common among older people, the percentage of aging people who perform regular optometric exams is low. In fact, uncorrected refractive errors are one of the main causes of visual impairment in this group of the population. Purpose: To evaluate functional vision of older residents in order to show the urgent need of visual screening programs in Galician nursing homes. Methodology: We examined 364 older adults aged 65 years and over. To measure vision of the daily living, we tested distance and near presenting visual acuity (binocular visual acuity with habitual correction if warn, directional E-Snellen) Presenting near vision was tested at the usual working distance. We defined visual impairment (distance and near) as a presenting visual acuity less than 0.3. Exclusion criteria included immobilized residents unable to reach the USC Dual Sensory Loss Unit for visual screening. Association between categorical variables was performed using chi-square tests. We used Pearson and Spearman correlation tests and the variance analysis to determine differences between groups of interest. Results: 23,1% of participants have visual impairment for distance vision and 16,4% for near vision. The percentage of residents with far and near visual impairment reaches 8,2%. As expected, prevalence of visual impairment increases with age. No differences exist with regard to the level of functional vision between gender. Differences exist between age group respect to distance vision, but not in case of near vision. Conclusion: prevalence of visual impairment is high among the older people tested in this pilot study. This means a high percentage of older people with limitations in their daily life activities. It is necessary to develop an effective vision screening program for early detection of vision problems in Galician nursing homes.

Keywords: functional vision, elders, aging, nursing homes

Procedia PDF Downloads 408

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Azar Sharafianpor, Hossein Rassi, Fahimeh Nemati Mansur

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Cardiovascular diseases (CVD) are the most important cause of death in industrialized and developing countries such as Iran. The most important risk factors for the CVD, genetic factors and chronic infectious agents, such as Helicobacter pylori, can be mentioned. The TNFα gene is one of the most important anti-inflammatory cytokines that can affect the sensitivity, efficacy, and ability of the immune response to chronic infections. Some TNF-α gene polymorphisms, including the replacement of the G nucleotide G with A at position 308 in the promoter region of TNF-α, increase the transcription of cytokines in the target cells and thus predispose a person to chronic infections. This study examines the TNF-α 308 polymorphism and its association with Helicobacter pylori infection in this disease. This study was a case-control study in which 154 patients were examined as cases or patients with symptoms of myocardial infarction or angina and 160 as controls or healthy subjects. All of the subjects at different ages were given venous blood and age, BMI, cholesterol, LDL, and HDL were determined. DNA was extracted from the specimens, and the cagA gene from H. pylori and the TNF-α-308 polymorphism were determined by PCR in patients and healthy subjects. Statistical analysis was performed with Epi Info software. The results showed that the frequency of H. pylori infection in the patients and healthy group were 53.23% (82 out of 154) and 47.5% (76 out of 160). There was no significant difference in H. pylori outbreak between the two groups. The frequencies of TNF-α-308 genotype for GG, GA, and AA in patients were 0.17, 0.49, and 0.34, respectively, whereas for controls 0.47, 0.35, and 0.18 for GG, GA, and AA, respectively. The frequency of genotype analysis of TNF-α-308 polymorphisms in both patients and healthy groups showed that there was a significant difference in the frequency of genotypes and the AA genotype was higher in the affected individuals. Also, there was a significant relationship between the genotype and the contamination with H. pylori and changes in cholesterol, LDL, and HDL levels were observed. The results of the study indicate that H. pylori detection in individuals with AA genotype in people under 50 years of age can play an important role in early diagnosis and treatment of cardiovascular disease.

Keywords: Helicobacter pylori, TNFα gene, cardiovascular diseases, TNFα-308 polymorphism

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Authors: Oludare Isaac Abiodun, Esther Omolara Abiodun

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The purpose of this paper is to demonstrate that cyberterrorism is existing and poses a threat to computer security and national security. Nowadays, people have become excitedly dependent upon computers, phones, the Internet, and the Internet of things systems to share information, communicate, conduct a search, etc. However, these network systems are at risk from a different source that is known and unknown. These network systems risk being caused by some malicious individuals, groups, organizations, or governments, they take advantage of vulnerabilities in the computer system to hawk sensitive information from people, organizations, or governments. In doing so, they are engaging themselves in computer threats, crime, and terrorism, thereby making the use of computers insecure for others. The threat of cyberterrorism is of various forms and ranges from one country to another country. These threats include disrupting communications and information, stealing data, destroying data, leaking, and breaching data, interfering with messages and networks, and in some cases, demanding financial rewards for stolen data. Hence, this study identifies many ways that cyberterrorists utilize the Internet as a tool to advance their malicious mission, which negatively affects computer security and safety. One could identify causes for disparate anomaly behaviors and the theoretical, ideological, and current forms of the likelihood of cyberterrorism. Therefore, for a countermeasure, this paper proposes the use of previous and current computer security models as found in the literature to help in countering cyberterrorism

Keywords: cyberterrorism, computer security, information, internet, terrorism, threat, digital forensic solution

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Authors: Ugbor Raphael Oluchukwu

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The survey research design was adopted to examine whether liquidity and cash management practices of owner-managed firms in South East Nigeria influence their profitability, growth and survival. Four independent variables (accounting systems, working capital management, budgetary control, and managerial planning) were used in the evaluation which was restricted to eight small firms. Results indicate that one variable, working capital management alone dominate the liquidity perception of owner managers. As a result, owner managers find it difficult to meet maturing business obligations as growth sets in. The study also reveals that the four independent variables have significant impact on the profitability, growth and survival of owner managed firms. Owner managers are therefore advised to undertake regular entrepreneurship training in order to upgrade their liquidity and cash management knowledge and practices to enhance their overall performance.

Keywords: liquidity management, owner-managed firm, profitability, survival

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Authors: Vanessa Roulet, Marc Turini, Juliane Hey, Stéphanie Bord-Romeu, Emilie Bonzom, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Vanessa Viotti, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

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Background: Beckman Coulter, Inc. has recently developed fully automated assays for the detection of HBsAg on a new immunoassay platform. The objective of this European multicenter study was to evaluate the performance of the ACCESS HBsAg and ACCESS HBsAg Confirmatory assays† on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer. Methods: The clinical specificity of the ACCESS HBsAg and HBsAg Confirmatory assays was determined using HBsAg-negative samples from blood donors and hospitalized patients. The clinical sensitivity was determined using presumed HBsAg-positive samples. Sample HBsAg status was determined using a CE-marked HBsAg assay (Abbott ARCHITECT HBsAg Qualitative II, Roche Elecsys HBsAg II, or Abbott PRISM HBsAg assay) and a CE-marked HBsAg confirmatory assay (Abbott ARCHITECT HBsAg Qualitative II Confirmatory or Abbott PRISM HBsAg Confirmatory assay) according to manufacturer package inserts and pre-determined testing algorithms. False initial reactive rate was determined on fresh hospitalized patient samples. The sensitivity for the early detection of HBV infection was assessed internally on thirty (30) seroconversion panels. Results: Clinical specificity was 99.95% (95% CI, 99.86 – 99.99%) on 6047 blood donors and 99.71% (95%CI, 99.15 – 99.94%) on 1023 hospitalized patient samples. A total of six (6) samples were found false positive with the ACCESS HBsAg assay. None were confirmed for the presence of HBsAg with the ACCESS HBsAg Confirmatory assay. Clinical sensitivity on 455 HBsAg-positive samples was 100.00% (95% CI, 99.19 – 100.00%) for the ACCESS HBsAg assay alone and for the ACCESS HBsAg Confirmatory assay. The false initial reactive rate on 821 fresh hospitalized patient samples was 0.24% (95% CI, 0.03 – 0.87%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS HBsAg assay had equivalent sensitivity performances compared to the Abbott ARCHITECT HBsAg Qualitative II assay with an average bleed difference since first reactive bleed of 0.13. All bleeds found reactive in ACCESS HBsAg assay were confirmed in ACCESS HBsAg Confirmatory assay. Conclusion: The newly developed ACCESS HBsAg and ACCESS HBsAg Confirmatory assays from Beckman Coulter have demonstrated high clinical sensitivity and specificity, equivalent to currently marketed HBsAg assays, as well as a low false initial reactive rate. †Pending achievement of CE compliance; not yet available for in vitro diagnostic use. 2023-11317 Beckman Coulter and the Beckman Coulter product and service marks mentioned herein are trademarks or registered trademarks of Beckman Coulter, Inc. in the United States and other countries. All other trademarks are the property of their respective owners.

Keywords: dxi 9000 access immunoassay analyzer, hbsag, hbv, hepatitis b surface antigen, hepatitis b virus, immunoassay

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Authors: C. Bolakis, I. S. Karanasiou, D. Grbovic, G. Karunasiri, N. Uzunoglu

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A new approach for efficient detection of THz radiation in biomedical imaging applications is proposed. A double-layered absorber consisting of a 32 nm thick aluminum (Al) metallic layer, located on a glass medium (SiO2) of 1 mm thickness, was fabricated and used to design a fine-tuned absorber through a theoretical and finite element modeling process. The results indicate that the proposed low-cost, double-layered absorber can be tuned based on the metal layer sheet resistance and the thickness of various glass media taking advantage of the diversity of the absorption of the metal films in the desired THz domain (6 to 10 THz). It was found that the composite absorber could absorb up to 86% (a percentage exceeding the 50%, previously shown to be the highest achievable when using single thin metal layer) and reflect less than 1% of the incident THz power. This approach will enable monitoring of the transmission coefficient (THz transmission ‘’fingerprint’’) of the biosample with high accuracy, while also making the proposed double-layered absorber a good candidate for a microbolometer pixel’s active element. Based on the aforementioned promising results, a more sophisticated and effective double-layered absorber is under development. The glass medium has been substituted by diluted poly-si and the results were twofold: An absorption factor of 96% was reached and high TCR properties acquired. In addition, a generalization of these results and properties over the active frequency spectrum was achieved. Specifically, through the development of a theoretical equation having as input any arbitrary frequency in the IR spectrum (0.3 to 405.4 THz) and as output the appropriate thickness of the poly-si medium, the double-layered absorber retains the ability to absorb the 96% and reflects less than 1% of the incident power. As a result, through that post-optimization process and the spread spectrum frequency adjustment, the microbolometer detector efficiency could be further improved.

Keywords: bio-imaging, fine-tuned absorber, fingerprint, microbolometer

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Authors: Pooja Ahuja, Tejal Bhutani, M. S. Dahiya

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Cheiloscopy, the study of lip prints, is a tool in forensic investigation technique that deals with identification of individuals based on lips patterns. The objective of this study is to determine predominant lip print pattern found among the Gujarati population, to evaluate whether any sex difference exists and to study the permanence of the pattern over six months duration. The study comprised of 100 healthy individuals (50 males and 50 females), in the age group of 18 to 25 years of Gujarati population of the Gandhinagar region of the Gujarat state, India. By using Suzuki and Tsuchihashi classification, Lip prints were then divided into four quadrants and also classified on the basis of peripheral shape of the lips. Materials used to record the lip prints were dark brown colored lipstick, cellophane tape, and white bond paper. Lipstick was applied uniformly, and lip prints were taken on the glued portion of cellophane tape and then stuck on to a white bond paper. These lip prints were analyzed with magnifying lens and virtually with stereo microscope. On the analysis of the subject population, results showed Branched pattern Type II (29.57 percentage) to be most predominant in the Gujarati population. Branched pattern Type II (35.60 percentage) and long vertical Type I (28.28 percentage) were most prevalent in males and females respectively and large full lips were most predominantly present in both the sexes. The study concludes that lip prints in any form can be an effective tool for identification of an individual in a closed or open group forms.

Keywords: cheiloscopy, lip pattern, predomianant, Gujarati population

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Authors: Manal Hassan Abdel Aziz, Fatma Mohamed Magdy Badr El Dine, Nourhan Mohamed Mohamed Saeed

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Establishing association between lip print patterns and those of fingerprints as well as blood groups is of fundamental importance in the forensic identification domain. The first aim of the current study was to determine the prevalent types of ABO blood groups, lip prints and fingerprints patterns in both studied populations. Secondly, to analyze any relation found between the different print patterns and the blood groups, which would be valuable in identification purposes. The present study was conducted on 60 healthy volunteers, (30 males and 30 females) from each of the studied population. Lip prints and fingerprints were obtained and classified according to Tsuchihashi's classification and Michael Kuchen’s classification, respectively. The results show that the ulnar loop was the most frequent among both populations. Blood group A was the most frequent among Egyptians, while blood groups O and B were the predominant among Malaysians. Significant relations were observed between lip print patterns and fingerprint (in the second quadrant for Egyptian males and the first one for Malaysian). For Malaysian females, a statistically significant association was proved in the fourth quadrant. Regarding the blood groups, 89.5% of ulnar loops were significantly related to blood group A among Egyptian males. The results proved an association between the fingerprint pattern and the lip prints, as well as between the ABO blood group and the pattern of fingerprints. However, further researches with larger sample sizes need to be directed to approve the current results.

Keywords: ABO, cheiloscopy, dactylography, Egyptians, Malaysians

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Authors: Rishabh Beri, Sahil Shah

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We have applied a range of filters and processing in order to extract out the various features of the football game, like the field lines of a football field. Another important aspect was the detection of the players in the field and tagging them according to their teams distinguished by their jersey colours. This extracted information combined about the players and field helped us to create a virtual field that consists of the playing field and the players mapped to their locations in it.

Keywords: Detect, Football, Players, Virtual

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Authors: Romain Ben Taleb, Aurélie Montarnal, Matthieu Lauras, Mathieu Dahan, Romain Miclo

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To be competitive and sustainable, any company has to maximize its value. However, unlike listed companies that can assess their values based on market shares, most Small and Medium Enterprises (SMEs) which are non-listed cannot have direct and live access to this critical information. Traditional accounting reports only give limited insights to SME decision-makers about the real impact of their day-to-day decisions on the company’s performance and value. Most of the time, an SME’s financial valuation is made one time a year as the associated process is time and resource-consuming, requiring several months and external expertise to be completed. To solve this issue, we propose in this paper a value-oriented metamodel that enables real-time and dynamic assessment of the SME’s value based on the large definition of their assets. These assets cover a wider scope of resources of the company and better account for immaterial assets. The proposal, which is illustrated in a case study, discusses the benefits of incorporating assets in the SME valuation.

Keywords: SME, metamodel, decision support system, financial valuation, assets

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Authors: Katarzyna Lubecka, Kirsty Flower, Megan Beetch, Lucinda Kurzava, Hannah Buvala, Samer Gawrieh, Suthat Liangpunsakul, Tracy Gonzalez, George McCabe, Naga Chalasani, James M. Flanagan, Barbara Stefanska

Abstract:

Hepatocellular carcinoma (HCC), the most prevalent type of primary liver cancer, is the second leading cause of cancer death worldwide. Late onset of clinical symptoms in HCC results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable early detection biomarkers that can distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed and could increase the cure rate from 5% to 80%. We used Illumina-450K microarray to test whether blood DNA, an easily accessible source of DNA, bear site-specific changes in DNA methylation in response to HCC before diagnosis with conventional tools (pre-diagnostic). Top 11 differentially methylated sites were selected for validation by pyrosequencing. The diagnostic potential of the 11 pyrosequenced probes was tested in blood samples from a prospective cohort of cirrhotic patients. We identified 971 differentially methylated CpG sites in pre-diagnostic HCC cases as compared with healthy controls (P < 0.05, paired Wilcoxon test, ICC ≥ 0.5). Nearly 76% of differentially methylated CpG sites showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test). Classification of the CpG sites according to their location relative to CpG islands and transcription start site revealed that those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5’UTR at higher frequency than hypermethylated sites. Among 735 CpG sites hypomethylated in cases vs. controls, 482 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 160 genes. Bioinformatics analysis using GO, KEGG and DAVID knowledgebase indicate that differentially methylated CpG sites are located in genes associated with functions that are essential for gene transcription, cell adhesion, cell migration, and regulation of signal transduction pathways. Taking into account the magnitude of the difference, statistical significance, location, and consistency across the majority of matched pairs case-control, we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing. We established that methylation of CpG sites within 5 out of those 10 genes distinguish cirrhotic patients who subsequently developed HCC from those who stayed cancer free (cirrhotic controls), demonstrating potential as biomarkers of early detection in populations at risk. The best predictive value was detected for CpGs located within BARD1 (AUC=0.70, asymptotic significance ˂0.01). Using an additive logistic regression model, we further showed that 9 CpG loci within those 5 genes, that were covered in pyrosequenced probes, constitute a panel with high diagnostic accuracy (AUC=0.887; 95% CI:0.80-0.98). The panel was able to distinguish pre-diagnostic cases from cirrhotic controls free of cancer with 88% sensitivity at 70% specificity. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established biomarker panel has high potential to be developed into a routine clinical test after validation in larger cohorts. This study was supported by Showalter Trust, American Cancer Society (IRG#14-190-56), and Purdue Center for Cancer Research (P30 CA023168) granted to BS.

Keywords: biomarker, DNA methylation, early detection, hepatocellular carcinoma

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Authors: Alhamdi Alfi Fajri

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The purpose of this study is to analyze and to give empirical proof about the effect of fair value implementation on financial asset against information asymmetry in Indonesia’s banking sector. This research tested the effect of fair value implementation on financial asset based on Statement of Financial Accounting Standard (PSAK) No. 55 and the fair value reliability measurement based on PSAK No. 60 against level of information asymmetry. The scope of research is Indonesia’s banking sector. The test’s result shows that the use of fair value based on PSAK No. 55 is significantly associated with information asymmetry. This positive relation is higher than the amortized cost implementation on financial asset. In addition, the fair value hierarchy based on PSAK No. 60 is significantly associated with information asymmetry. This research proves that the more reliable measurement of fair value on financial asset, the more observable fair value measurement and reduces level of information asymmetry.

Keywords: fair value, PSAK No. 55, PSAK No. 60, information asymmetry, bank

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Authors: Mirza Waseem Abbas, Syed Danish Raza

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For many countries agriculture is still the major force driving the economy and a critically important socioeconomic sector, despite exceptional industrial development across the globe. In countries like Pakistan, this sector is considered the backbone of the economy, and most of the economic decision making revolves around agricultural outputs and data. Timely and accurate facts and figures about this vital sector hold immense significance and have serious implications for the long-term development of the economy. Therefore, any significant improvements in the statistics and other forms of data regarding agriculture sector are considered important by all policymakers. This is especially true for decision making for the betterment of crops and the agriculture sector in general. Provincial and federal agricultural departments collect data for all cash and non-cash crops and the sector, in general, every year. Traditional data collection for such a large sector i.e. agriculture, being time-consuming, prone to human error and labor-intensive, is slowly but gradually being replaced by remote sensing techniques. For this study, remotely sensed data were used for change detection (machine learning, supervised & unsupervised classification) to assess the increase or decrease in area under agriculture over the last fifteen years due to urbanization. Detailed Landsat Images for the selected agricultural districts were acquired for the year 2000 and compared to images of the same area acquired for the year 2016. Observed differences validated through detailed analysis of the areas show that there was a considerable decrease in vegetation during the last fifteen years in four major agricultural districts of the Punjab province due to urbanization (housing societies).

Keywords: change detection, area estimation, machine learning, urbanization, remote sensing

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Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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Authors: Janusz Bobulski, Mariusz Kubanek

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The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

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Authors: Yatimah Alias, Tilagam Marimuthu, M. R. Mahmoudian, Sharifah Mohamad

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The rapid growth of science and technology in energy and environmental fields has enlightened the substantial importance of the conducting polymer and metal composite materials engineered at nano-scale. In this study, polypyrrole-cobalt composites (PPy-Co Cs) and polypyrrole-nickel oxide composites (PPy-NiO Cs) were prepared by a simple and facile chemical polymerization method with an aqueous solution of pyrrole monomer in the presence of metal salt. These composites then fabricated into non-enzymatic hydrogen peroxide (H2O2) and glucose sensor. The morphology and composition of the composites are characterized by the Field Emission Scanning Electron Microscope, Fourier Transform Infrared Spectrum and X-ray Powder Diffraction. The obtained results were compared with the pure PPy and metal oxide particles. The structural and morphology properties of synthesized composites are different from those of pure PPy and metal oxide particles, which were attributed to the strong interaction between the PPy and the metal particles. Besides, a favorable micro-environment for the electrochemical oxidation of H2O2 and glucose was achieved on the modified glassy carbon electrode (GCE) coated with PPy-Co Cs and PPy-NiO Cs respectively, resulting in an enhanced amperometric response. Both PPy-Co/GCE and PPy-NiO/GCE give high response towards target analyte at optimum condition of 500 μl pyrrole monomer content. Furthermore, the presence of pyrrole monomer greatly increases the sensitivity of the respective modified electrode. The PPy-Co/GCE could detect H2O2 in a linear range of 20 μM to 80 mM with two linear segments (low and high concentration of H2O2) and the detection limit for both ranges is 2.05 μM and 19.64 μM, respectively. Besides, PPy-NiO/GCE exhibited good electrocatalytic behavior towards glucose oxidation in alkaline medium and could detect glucose in linear ranges of 0.01 mM to 0.50 mM and 1 mM to 20 mM with detection limit of 0.33 and 5.77 μM, respectively. The ease of modifying and the long-term stability of this sensor have made it superior to enzymatic sensors, which must kept in a critical environment.

Keywords: metal oxide, composite, non-enzymatic sensor, polypyrrole

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Authors: Emad Al-Abdallat, Faris G. Bakri, Azmi Mahafza, Rayyan Al Ali, Nidaa Ababneh, Ahmed Idhair

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Background: Morgues are high-risk areas for the spread of infection from the cadavers to the staff during the postmortem examination. Infection can spread from corpses to workers by the airborne route, by direct contact, or from needle and sharp object injuries. Objective: Knowledge about the prevalence of these infections among autopsies is prudent to appreciate any risk of transmission and to further enforce safety measures. Method: A total of 242 autopsies were tested. Age ranged from 3 days to 94 years (median 75.5 years, mean 45.3 (21.9 ± SD)). There were 172 (71%) males. Results: The cause of death was considered natural in 137 (56.6%) cases, accidental in 89 (36.8%), homicidal in 9 (3.7%), suicidal in 4 (1.7%), and unknown in 3 (1.2%). Hepatitis B surface antigen was positive in 5 (2.1%) cases. Hepatitis C virus antibody was detected in 5 (2.1%) cases and the hepatitis C virus polymerase chain reaction was positive in 2 of them (0.8%). HIV antibody was not detected in any of the cases. Conclusions: Autopsies can be associated with exposure to blood borne viruses. Autopsies performed during the study period were tested for hepatitis B surface antigen, hepatitis C virus antibody, and human immunodeficiency virus antibody. Positive tests were subsequently confirmed by polymerase chain reaction. There is low prevalence of infections with these viruses in our autopsy cases. However, the risk of transmission remains a threat. Healthcare workers in the forensic departments should adhere to standard precautions.

Keywords: autopsy, hepatitis B virus, hepatitis C virus, human immunodeficiency virus, Jordan

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