Search results for: human detection and identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13474

Search results for: human detection and identification

11374 Bluetooth Piconet System for Child Care Applications

Authors: Ching-Sung Wang, Teng-Wei Wang, Zhen-Ting Zheng

Abstract:

This study mainly concerns a safety device designed for child care. When children are out of sight or the caregivers cannot always pay attention to the situation, through the functions of this device, caregivers can immediately be informed to make sure that the children do not get lost or hurt, and thus, ensure their safety. Starting from this concept, a device is produced based on the relatively low-cost Bluetooth piconet system and a three-axis gyroscope sensor. This device can transmit data to a mobile phone app through Bluetooth, in order that the user can learn the situation at any time. By simply clipping the device in a pocket or on the waist, after switching on/starting the device, it will send data to the phone to detect the child’s fall and distance. Once the child is beyond the angle or distance set by the app, it will issue a warning to inform the phone owner.

Keywords: children care, piconet system, three-axis gyroscope, distance detection, falls detection

Procedia PDF Downloads 597
11373 Pulmonary Disease Identification Using Machine Learning and Deep Learning Techniques

Authors: Chandu Rathnayake, Isuri Anuradha

Abstract:

Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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11372 Real-Time Kinetic Analysis of Labor-Intensive Repetitive Tasks Using Depth-Sensing Camera

Authors: Sudip Subedi, Nipesh Pradhananga

Abstract:

The musculoskeletal disorders, also known as MSDs, are common in construction workers. MSDs include lower back injuries, knee injuries, spinal injuries, and joint injuries, among others. Since most construction tasks are still manual, construction workers often need to perform repetitive, labor-intensive tasks. And they need to stay in the same or an awkward posture for an extended time while performing such tasks. It induces significant stress to the joints and spines, increasing the risk of getting into MSDs. Manual monitoring of such tasks is virtually impossible with the handful of safety managers in a construction site. This paper proposes a methodology for performing kinetic analysis of the working postures while performing such tasks in real-time. Skeletal of different workers will be tracked using a depth-sensing camera while performing the task to create training data for identifying the best posture. For this, the kinetic analysis will be performed using a human musculoskeletal model in an open-source software system (OpenSim) to visualize the stress induced by essential joints. The “safe posture” inducing lowest stress on essential joints will be computed for different actions involved in the task. The identified “safe posture” will serve as a basis for real-time monitoring and identification of awkward and unsafe postural behaviors of construction workers. Besides, the temporal simulation will be carried out to find the associated long-term effect of repetitive exposure to such observed postures. This will help to create awareness in workers about potential future health hazards and encourage them to work safely. Furthermore, the collected individual data can then be used to provide need-based personalized training to the construction workers.

Keywords: construction workers’ safety, depth sensing camera, human body kinetics, musculoskeletal disorders, real time monitoring, repetitive labor-intensive tasks

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11371 Stability-Indicating High-Performance Thin-Layer Chromatography Method for Estimation of Naftopidil

Authors: P. S. Jain, K. D. Bobade, S. J. Surana

Abstract:

A simple, selective, precise and Stability-indicating High-performance thin-layer chromatographic method for analysis of Naftopidil both in a bulk and in pharmaceutical formulation has been developed and validated. The method employed, HPTLC aluminium plates precoated with silica gel as the stationary phase. The solvent system consisted of hexane: ethyl acetate: glacial acetic acid (4:4:2 v/v). The system was found to give compact spot for Naftopidil (Rf value of 0.43±0.02). Densitometric analysis of Naftopidil was carried out in the absorbance mode at 253 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.999±0.0001 with respect to peak area in the concentration range 200-1200 ng per spot. The method was validated for precision, recovery and robustness. The limits of detection and quantification were 20.35 and 61.68 ng per spot, respectively. Naftopidil was subjected to acid and alkali hydrolysis, oxidation and thermal degradation. The drug undergoes degradation under acidic, basic, oxidation and thermal conditions. This indicates that the drug is susceptible to acid, base, oxidation and thermal conditions. The degraded product was well resolved from the pure drug with significantly different Rf value. Statistical analysis proves that the method is repeatable, selective and accurate for the estimation of investigated drug. The proposed developed HPTLC method can be applied for identification and quantitative determination of Naftopidil in bulk drug and pharmaceutical formulation.

Keywords: naftopidil, HPTLC, validation, stability, degradation

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11370 Offender Rehabilitation: The Middle Way of Maimonides to Mental and Social Health

Authors: Liron Hoch

Abstract:

Traditional religious and spiritual texts offer a surprising wealth of relevant theoretical and practical knowledge about human behavior. This wellspring may contribute significantly to expanding our current body of knowledge in the social sciences and criminology in particular. In Jewish religious texts, specifically by Maimonides, we can find profound analyses of human traits and guidelines for a normative way of life. Among other things, modern criminological literature attempts to link certain character traits and divergent behaviors. Using the hermeneutic phenomenological approach, we analyzed the writings of Maimonides, mainly Laws of Human Dispositions, in order to understand Moses ben Maimon's (1138–1204) view of character traits. The analysis yielded four themes: (1) Human personality between nature and nurture; (2) The complexity of human personality, imbalance and criminality; (3) Extremism as a way to achieve balance; and (4) The Middle Way, flexibility and common sense. These themes can serve therapeutic purposes, as well as inform a rehabilitation model. Grounded in a theoretical rationale about the nature of humans, this model is designed to direct individuals to balance their traits by self-reflection and constant practice of the Middle Way. The proposal we will present is that implementing this model may promote normative behavior and thus contribute to rehabilitating offenders.

Keywords: rehabilitation, traits, offenders, maimonides, middle way

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11369 Identification and Differentiation of Fagonia Arabica and Fagonia Indica by Using DNA Barcode Region Matk

Authors: Noshaba Dilbar, Aisha Tahir, Amer Jamil

Abstract:

During the last decade, DNA barcoding proved to be an authentic tool for discovery and identification of plants. In the present study, DNA barcoding of two species, Fagonia arabica and Fagonia indica was done for differentiation by using matK region. matK gene is considered as a universal barcode because of its easy alignment and high discrimination ability. In this study, matK yielded 100% sequencing results. The sequences from both plants were aligned at clustal W and observed that there is no nucleotide variation and polymorphism among both sequences. This was further analysed by BLAST which showed the similar sequences from different plants belonging to same family but didn’t find sequence of both species. Considering this, the resulted sequence was submitted by the name of Fagonia arabica with accession number KM276890. In the end, we analysed the results from BOLD which gave us the final conclusion that both plants are same as their matK sequences are 100% identical. In literature, both Fagonia indica and Fagonia arabica names are used for this plant but there is no clear differentiation has been observed in these plants. Results evaluate that Fagonia indica and Fagonia arabica are the alternative names of same plant.

Keywords: DNA barcoding, Fagonia arabica, Fagonia indica, matK

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11368 A Model Based Metaheuristic for Hybrid Hierarchical Community Structure in Social Networks

Authors: Radhia Toujani, Jalel Akaichi

Abstract:

In recent years, the study of community detection in social networks has received great attention. The hierarchical structure of the network leads to the emergence of the convergence to a locally optimal community structure. In this paper, we aim to avoid this local optimum in the introduced hybrid hierarchical method. To achieve this purpose, we present an objective function where we incorporate the value of structural and semantic similarity based modularity and a metaheuristic namely bees colonies algorithm to optimize our objective function on both hierarchical level divisive and agglomerative. In order to assess the efficiency and the accuracy of the introduced hybrid bee colony model, we perform an extensive experimental evaluation on both synthetic and real networks.

Keywords: social network, community detection, agglomerative hierarchical clustering, divisive hierarchical clustering, similarity, modularity, metaheuristic, bee colony

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11367 Modular Robotics and Terrain Detection Using Inertial Measurement Unit Sensor

Authors: Shubhakar Gupta, Dhruv Prakash, Apoorv Mehta

Abstract:

In this project, we design a modular robot capable of using and switching between multiple methods of propulsion and classifying terrain, based on an Inertial Measurement Unit (IMU) input. We wanted to make a robot that is not only intelligent in its functioning but also versatile in its physical design. The advantage of a modular robot is that it can be designed to hold several movement-apparatuses, such as wheels, legs for a hexapod or a quadpod setup, propellers for underwater locomotion, and any other solution that may be needed. The robot takes roughness input from a gyroscope and an accelerometer in the IMU, and based on the terrain classification from an artificial neural network; it decides which method of propulsion would best optimize its movement. This provides the bot with adaptability over a set of terrains, which means it can optimize its locomotion on a terrain based on its roughness. A feature like this would be a great asset to have in autonomous exploration or research drones.

Keywords: modular robotics, terrain detection, terrain classification, neural network

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11366 Detection of Antibiotic Resistance Genes and Antibiotic Residues in Plant-based Products

Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

Abstract:

Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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11365 High Frequency of Chlamydophila Pneumoniae in Children with Asthma Exacerbations

Authors: Katherine Madero Valencia, Carlos Jaramillo, Elida Dueñas, Carlos Torres, María Del Pilar Delgado

Abstract:

Asthma, described as a chronic inflammatory condition of the airways, courses accompanied by episodes known as exacerbations, characterized by a worsening of symptoms. Among the triggers, some allergen-irritative and infectious agents are found, including Chlamydophila pneumoniae which seems to play an increasingly important role. In this paper a PCR was used to detect C. pneumoniae in order to estimate the frequency of infections caused by this agent in pediatric patients with asthma exacerbations. C. pneumoniae distribution throughout the study period was also evaluated. 175 nasopharyngeal aspirates from children with asthma exacerbations were analyzed by PCR and sequencing. A global prevalence of C. pneumoniae of 53.71% was obtained. This study highlights a high circulation of C. pneumoniae during the study period, in children of all ages and especially in children under 5 years old. Molecular tests applied permit a rapid detection and improved our knowledge about these infections in children with asthma.

Keywords: Chlamydophila pneumoniae, detection, molecular techniques, pediatric asthma

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11364 Human Rights in the United States: Challenges and Lessons from the Period 1948-2018

Authors: Mary Carmen Peloche Barrera

Abstract:

Since its early years as an independent nation, the United States has been one of the main promoters regarding the recognition, legislation, and protection of human rights. In the matter of freedom, the founding father Thomas Jefferson envisioned the role of the U.S. as a defender of freedom and equality throughout the world. This founding ideal shaped America’s domestic and foreign policy in the 19th and the 20th century and became an aspiration of the ideals of the country to expand its values and institutions. The history of the emergence of human rights cannot be studied without making reference to leaders such as Woodrow Wilson, Franklin, and Eleanor Roosevelt, as well as Martin Luther King. Throughout its history, this country has proclaimed that the protection of the freedoms of men, both inside and outside its borders, is practically the reason for its existence. Although the United States was one of the first countries to recognize the existence of inalienable rights for individuals, as well as the main promoter of the Universal Declaration of Human Rights of 1948, the country has gone through critical moments that had led to questioning its commitment to the issue. Racial segregation, international military interventions, national security strategy, as well as national legislation on immigration, are some of the most controversial issues related to decisions and actions driven by the United States, which at the same time mismatched with its role as an advocate of human rights, both in the Americas and in the rest of the world. The aim of this paper is to study the swinging of the efforts and commitments of the United States towards human rights. The paper will analyze the history and evolution of human rights in the United States, to study the greatest challenges for the country in this matter. The paper will focus on both the domestic policy (related to demographic issues) and foreign policy (about its role in a post-war world). Currently, more countries are joining the multilateral efforts for the promotion and protection of human rights. At the same time, the United States is one of the least committed countries in this respect, having ratified only 5 of the 18 treaties emanating from the United Nations. The last ratification was carried out in 2002 and, since then, the country has been losing ground, in an increasingly vertiginous way, in its credibility and, even worse, in its role as leader of 'the free world'. With or without the United States, the protection of human rights should remain the main goal of the international community.

Keywords: United States, human rights, foreign policy, domestic policy

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11363 Design and Development of an Autonomous Underwater Vehicle for Irrigation Canal Monitoring

Authors: Mamoon Masud, Suleman Mazhar

Abstract:

Indus river basin’s irrigation system in Pakistan is extremely complex, spanning over 50,000 km. Maintenance and monitoring of this demands enormous resources. This paper describes the development of a streamlined and low-cost autonomous underwater vehicle (AUV) for the monitoring of irrigation canals including water quality monitoring and water theft detection. The vehicle is a hovering-type AUV, designed mainly for monitoring irrigation canals, with fully documented design and open source code. It has a length of 17 inches, and a radius of 3.5 inches with a depth rating of 5m. Multiple sensors are present onboard the AUV for monitoring water quality parameters including pH, turbidity, total dissolved solids (TDS) and dissolved oxygen. A 9-DOF Inertial Measurement Unit (IMU), GY-85, is used, which incorporates an Accelerometer (ADXL345), a Gyroscope (ITG-3200) and a Magnetometer (HMC5883L). The readings from these sensors are fused together using directional cosine matrix (DCM) algorithm, providing the AUV with the heading angle, while a pressure sensor gives the depth of the AUV. 2 sonar-based range sensors are used for obstacle detection, enabling the vehicle to align itself with the irrigation canals edges. 4 thrusters control the vehicle’s surge, heading and heave, providing 3 DOF. The thrusters are controlled using a proportional-integral-derivative (PID) feedback control system, with heading angle and depth being the controller’s input and the thruster motor speed as the output. A flow sensor has been incorporated to monitor canal water level to detect water-theft event in the irrigation system. In addition to water theft detection, the vehicle also provides information on water quality, providing us with the ability to identify the source(s) of water contamination. Detection of such events can provide useful policy inputs for improving irrigation efficiency and reducing water contamination. The AUV being low cost, small sized and suitable for autonomous maneuvering, water level and quality monitoring in the irrigation canals, can be used for irrigation network monitoring at a large scale.

Keywords: the autonomous underwater vehicle, irrigation canal monitoring, water quality monitoring, underwater line tracking

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11362 Simultaneous Analysis of 25 Trace Elements in Micro Volume of Human Serum by Inductively Coupled Plasma–Mass Spectrometry

Authors: Azmawati Mohammed Nawi, Siok-Fong Chin, Shamsul Azhar Shah, Rahman Jamal

Abstract:

In recent years, trace elements have gained importance as biomarkers in many chronic diseases. Unfortunately, the requirement for sample volume increases according to the extent of investigation for diagnosis or elucidating the mechanism of the disease. Here, we describe the method development and validation for simultaneous determination of 25 trace elements (lithium (Li), beryllium (Be), magnesium (Mg), aluminium (Al), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), gallium (Ga), arsenic (As), selenium (Se), rubidium (Rb), strontium (Sr), silver (Ag), cadmium (Cd), caesium (Cs), barium (Ba), mercury (Hg), thallium (Tl), lead (Pb), uranium (U)) using just 20 µL of human serum. Serum samples were digested with nitric acid and hydrochloric acid (ratio 1:1, v/v) and analysed using inductively coupled plasma–mass spectrometry (ICP-MS). Seronorm®, a human-derived serum control material was used as quality control samples. The intra-day and inter-day precisions were consistently < 15% for all elements. The validated method was later applied to 30 human serum samples to evaluate its suitability. In conclusion, we have successfully developed and validated a precise and accurate analytical method for determining 25 trace elements requiring very low volume of human serum.

Keywords: acid digestion, ICP-MS, trace element, serum

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11361 Packaging in the Design Synthesis of Novel Aircraft Configuration

Authors: Paul Okonkwo, Howard Smith

Abstract:

A study to estimate the size of the cabin and major aircraft components as well as detect and avoid interference between internally placed components and the external surface, during the conceptual design synthesis and optimisation to explore the design space of a BWB, was conducted. Sizing of components follows the Bradley cabin sizing and rubber engine scaling procedures to size the cabin and engine respectively. The interference detection and avoidance algorithm relies on the ability of the Class Shape Transform parameterisation technique to generate polynomial functions of the surfaces of a BWB aircraft configuration from the sizes of the cabin and internal objects using few variables. Interference detection is essential in packaging of non-conventional configuration like the BWB because of the non-uniform airfoil-shaped sections and resultant varying internal space. The unique configuration increases the need for a methodology to prevent objects from being placed in locations that do not sufficiently enclose them within the geometry.

Keywords: packaging, optimisation, BWB, parameterisation, aircraft conceptual design

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11360 Identification and Characterization of Oil-Degrading Bacteria from Crude Oil-Contaminated Desert Soil in Northeastern Jordan

Authors: Mohammad Aladwan, Adelia Skripova

Abstract:

Bioremediation aspects of crude oil-polluted fields can be achieved by isolation and identification of bacterial species from oil-contaminated soil in order to choose the most active isolates and increase the strength of others. In this study, oil-degrading bacteria were isolated and identified from oil-contaminated soil samples in northeastern Jordan. The bacterial growth count (CFU/g) was between 1.06×10⁵ and 0.75×10⁹. Eighty-two bacterial isolates were characterized by their morphology and biochemical tests. The identified bacterial genera included: Klebsiella, Staphylococcus, Citrobacter, Lactobacillus, Alcaligenes, Pseudomonas, Hafnia, Micrococcus, Rhodococcus, Serratia, Enterobacter, Bacillus, Salmonella, Mycobacterium, Corynebacterium, and Acetobacter. Molecular identification of a universal primer 16S rDNA gene was used to identify four bacterial isolates: Microbacterium esteraromaticum strain L20, Pseudomonas stutzeri strain 13636M, Klebsilla pneumoniae, and uncultured Klebsilla sp., known as new strains. Our results indicate that their specific oil-degrading bacteria isolates might have a high strength of oil degradation from oil-contaminated sites. Staphylococcus intermedius (75%), Corynebacterium xerosis (75%), and Pseudomonas fluorescens (50%) showed a high growth rate on different types of hydrocarbons, such as crude oil, toluene, naphthalene, and hexane. In addition, monooxygenase and catechol 2,3-dioxygenase were detected in 17 bacterial isolates, indicating their superior hydrocarbon degradation potential. Total petroleum hydrocarbons were analyzed using gas chromatography for soil samples. Soil samples M5, M7, and M8 showed the highest levels (43,645, 47,805, and 45,991 ppm, respectively), and M4 had the lowest level (7,514 ppm). All soil samples were analyzed for heavy metal contamination (Cu, Cd, Mn, Zn, and Pb). Site M7 contains the highest levels of Cu, Mn, and Pb, while Site M8 contains the highest levels of Mn and Zn. In the future, these isolates of bacteria can be used for the cleanup of oil-contaminated soil.

Keywords: bioremediation, 16S rDNA gene, oil-degrading bacteria, hydrocarbons

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11359 Enterpreneurship as a Strategic Tool for Higher Productivity in Nigerian Universities System

Authors: Yahaya Salihu Emeje, Amuchie Austine Anthony

Abstract:

The topic examined the prospects of entrepreneurship as an emerging dynamic and strategic tool in the upliftment of human and non-human resources in the Nigerian university system, with a view of showcasing the abundant positive impact, on the Nigerian University system in particular and Nigerian economy at large. It is end at bringing out the benefits of entrepreneurship in the university system which includes, namely cultivating the culture of enterprise in University system; improvement in the quality and quantity of both human and non-human resources; innovative and creative methods of production; new employment strategies in the University system; improved sources of internal generated revenue; entrepreneurship as the culture of sustainability within and outside the university system. Secondary data was used in analyzing entrepreneurship as a productivity tool in the Nigeria University system. From the findings, the university system could be enriched through innovative ideas and technical revenue and employment generation; sustainable financial and economic base; university autonomy and improved international ranking of Nigerian Universities system; therefore, recommended that entrepreneurship is necessary therapy for reviving the ailing, Nigerian universities system.

Keywords: entrepreneurship, strategic, productivity, universities

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11358 Biological Significance of Long Intergenic Noncoding RNA LINC00273 in Lung Cancer Cell Metastasis

Authors: Ipsita Biswas, Arnab Sarkar, Ashikur Rahaman, Gopeswar Mukherjee, Subhrangsu Chatterjee, Shamee Bhattacharjee, Deba Prasad Mandal

Abstract:

One of the major reasons for the high mortality rate of lung cancer is the substantial delays in disease detection at late metastatic stages. It is of utmost importance to understand the detailed molecular signaling and detect the molecular markers that can be used for the early diagnosis of cancer. Several studies explored the emerging roles of long noncoding RNAs (lncRNAs) in various cancers as well as lung cancer. A long non-coding RNA LINC00273 was recently discovered to promote cancer cell migration and invasion, and its positive correlation with the pathological stages of metastasis may prove it to be a potential target for inhibiting cancer cell metastasis. Comparing real-time expression of LINC00273 in various human clinical cancer tissue samples with normal tissue samples revealed significantly higher expression in cancer tissues. This long intergenic noncoding RNA was found to be highly expressed in human liver tumor-initiating cells, human gastric adenocarcinoma AGS cell line, as well as human non-small cell lung cancer A549 cell line. SiRNA and shRNA-induced knockdown of LINC00273 in both in vitro and in vivo nude mice significantly subsided AGS and A549 cancer cell migration and invasion. LINC00273 knockdown also reduced TGF-β induced SNAIL, SLUG, VIMENTIN, ZEB1 expression, and metastasis in A549 cells. Plenty of reports have suggested the role of microRNAs of the miR200 family in reversing epithelial to mesenchymal transition (EMT) by inhibiting ZEB transcription factors. In this study, hsa-miR-200a-3p was predicted via IntaRNA-Freiburg RNA tools to be a potential target of LINC00273 with a negative free binding energy of −8.793 kcal/mol, and this interaction was verified as a confirmed target of LINC00273 by RNA pulldown, real-time PCR and luciferase assay. Mechanistically, LINC00273 accelerated TGF-β induced EMT by sponging hsa-miR-200a-3p which in turn liberated ZEB1 and promoted prometastatic functions in A549 cells in vitro as verified by real-time PCR and western blotting. The similar expression patterns of these EMT regulatory pathway molecules, viz. LINC00273, hsa-miR-200a-3p, ZEB1 and TGF-β, were also detected in various clinical samples like breast cancer tissues, oral cancer tissues, lung cancer tissues, etc. Overall, this LINC00273 mediated EMT regulatory signaling can serve as a potential therapeutic target for the prevention of lung cancer metastasis.

Keywords: epithelial to mesenchymal transition, long noncoding RNA, microRNA, non-small-cell lung carcinoma

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11357 Detection of Voltage Sag and Voltage Swell in Power Quality Using Wavelet Transforms

Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

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11356 Application of Infrared Thermal Imaging, Eye Tracking and Behavioral Analysis for Deception Detection

Authors: Petra Hypšová, Martin Seitl

Abstract:

One of the challenges of forensic psychology is to detect deception during a face-to-face interview. In addition to the classical approaches of monitoring the utterance and its components, detection is also sought by observing behavioral and physiological changes that occur as a result of the increased emotional and cognitive load caused by the production of distorted information. Typical are changes in facial temperature, eye movements and their fixation, pupil dilation, emotional micro-expression, heart rate and its variability. Expanding technological capabilities have opened the space to detect these psychophysiological changes and behavioral manifestations through non-contact technologies that do not interfere with face-to-face interaction. Non-contact deception detection methodology is still in development, and there is a lack of studies that combine multiple non-contact technologies to investigate their accuracy, as well as studies that show how different types of lies produced by different interviewers affect physiological and behavioral changes. The main objective of this study is to apply a specific non-contact technology for deception detection. The next objective is to investigate scenarios in which non-contact deception detection is possible. A series of psychophysiological experiments using infrared thermal imaging, eye tracking and behavioral analysis with FaceReader 9.0 software was used to achieve our goals. In the laboratory experiment, 16 adults (12 women, 4 men) between 18 and 35 years of age (SD = 4.42) were instructed to produce alternating prepared and spontaneous truths and lies. The baseline of each proband was also measured, and its results were compared to the experimental conditions. Because the personality of the examiner (particularly gender and facial appearance) to whom the subject is lying can influence physiological and behavioral changes, the experiment included four different interviewers. The interviewer was represented by a photograph of a face that met the required parameters in terms of gender and facial appearance (i.e., interviewer likability/antipathy) to follow standardized procedures. The subject provided all information to the simulated interviewer. During follow-up analyzes, facial temperature (main ROIs: forehead, cheeks, the tip of the nose, chin, and corners of the eyes), heart rate, emotional expression, intensity and fixation of eye movements and pupil dilation were observed. The results showed that the variables studied varied with respect to the production of prepared truths and lies versus the production of spontaneous truths and lies, as well as the variability of the simulated interviewer. The results also supported the assumption of variability in physiological and behavioural values during the subject's resting state, the so-called baseline, and the production of prepared and spontaneous truths and lies. A series of psychophysiological experiments provided evidence of variability in the areas of interest in the production of truths and lies to different interviewers. The combination of technologies used also led to a comprehensive assessment of the physiological and behavioral changes associated with false and true statements. The study presented here opens the space for further research in the field of lie detection with non-contact technologies.

Keywords: emotional expression decoding, eye-tracking, functional infrared thermal imaging, non-contact deception detection, psychophysiological experiment

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11355 Machine Learning Facing Behavioral Noise Problem in an Imbalanced Data Using One Side Behavioral Noise Reduction: Application to a Fraud Detection

Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

Abstract:

With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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11354 Parking Space Detection and Trajectory Tracking Control for Vehicle Auto-Parking

Authors: Shiuh-Jer Huang, Yu-Sheng Hsu

Abstract:

On-board available parking space detecting system, parking trajectory planning and tracking control mechanism are the key components of vehicle backward auto-parking system. Firstly, pair of ultrasonic sensors is installed on each side of vehicle body surface to detect the relative distance between ego-car and surrounding obstacle. The dimension of a found empty space can be calculated based on vehicle speed and the time history of ultrasonic sensor detecting information. This result can be used for constructing the 2D vehicle environmental map and available parking type judgment. Finally, the auto-parking controller executes the on-line optimal parking trajectory planning based on this 2D environmental map, and monitors the real-time vehicle parking trajectory tracking control. This low cost auto-parking system was tested on a model car.

Keywords: vehicle auto-parking, parking space detection, parking path tracking control, intelligent fuzzy controller

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11353 Protecting Human Health under International Investment Law

Authors: Qiang Ren

Abstract:

In the past 20 years, under the high standard of international investment protection, there have been numerous cases of investors ignoring the host country's measures to protect human health. Examples include investment disputes triggered by the Argentine government's measures related to human health, quality, and price of drinking water under the North American Free Trade Agreement. Examples also include Philip Morris v. Australia, in which case the Australian government announced the passing of the Plain Packing of Cigarettes Act to address the threat of smoking to public health in 2010. In order to take advantage of the investment treaty protection between Hong Kong and Australia, Philip Morris Asia acquired Philip Morris Australia in February 2011 and initiated investment arbitration under the treaty before the passage of the Act in July 2011. Philip Morris claimed the Act constitutes indirect expropriation and violation of fair and equitable treatment and claimed 4.16 billion US dollars compensation. Fortunately, the case ended at the admissibility decision stage and did not enter the substantive stage. Generally, even if the host country raises a human health defense, most arbitral tribunals will rule that the host country revoke the corresponding policy and make huge compensation in accordance with the clauses in the bilateral investment treaty to protect the rights of investors. The significant imbalance in the rights and obligations of host states and investors in international investment treaties undermines the ability of host states to act in pursuit of human health and social interests beyond economic interests. This squeeze on the nation's public policy space and disregard for the human health costs of investors' activities raises the need to include human health in investment rulemaking. The current international investment law system that emphasizes investor protection fails to fully reflect the requirements of the host country for the healthy development of human beings and even often brings negative impacts to human health. At a critical moment in the reform of the international investment law system, in order to achieve mutual enhancement of investment returns and human health development, human health should play a greater role in influencing and shaping international investment rules. International investment agreements should not be limited to investment protection tools but should also be part of national development strategies to serve sustainable development and human health. In order to meet the requirements of the new sustainable development goals of the United Nations, human health should be emphasized in the formulation of international investment rules, and efforts should be made to shape a new generation of international investment rules that meet the requirements of human health and sustainable development.

Keywords: human health, international investment law, Philip Morris v. Australia, investor protection

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11352 Democracy and Human Rights in Nigeria's Fourth Republic: An Assessment

Authors: Kayode Julius Oni

Abstract:

Without mincing words, democracy is by far the most popular form of government in the world today. No matter how we look at it, and regardless of the variant, most leaders in the world today wish to be seen or labeled as Democrats. Perhaps, its attractions in terms of freedom of allocation, accountability, smooth successions of leadership and a lot more, account for its appeal to the ordinary people. The governance style in Nigeria since 1999 cannot be said to be different from the military. Elections are manipulated, judicial processes abused, and the ordinary people do not have access to the dividends of democracy. The paper seeks to address the existing failures experienced under democratic rule in Nigeria which have to transcend into violation of human rights in the conduct of government business. The paper employs the primary and secondary sources of data collection, and it is highly descriptive and critical.

Keywords: democracy, human rights, Nigeria, politics, republic

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11351 A Physiological Approach for Early Detection of Hemorrhage

Authors: Rabie Fadil, Parshuram Aarotale, Shubha Majumder, Bijay Guargain

Abstract:

Hemorrhage is the loss of blood from the circulatory system and leading cause of battlefield and postpartum related deaths. Early detection of hemorrhage remains the most effective strategy to reduce mortality rate caused by traumatic injuries. In this study, we investigated the physiological changes via non-invasive cardiac signals at rest and under different hemorrhage conditions simulated through graded lower-body negative pressure (LBNP). Simultaneous electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure (BP), impedance cardiogram (ICG), and phonocardiogram (PCG) were acquired from 10 participants (age:28 ± 6 year, weight:73 ± 11 kg, height:172 ± 8 cm). The LBNP protocol consisted of applying -20, -30, -40, -50, and -60 mmHg pressure to the lower half of the body. Beat-to-beat heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean aerial pressure (MAP) were extracted from ECG and blood pressure. Systolic amplitude (SA), systolic time (ST), diastolic time (DT), and left ventricle Ejection time (LVET) were extracted from PPG during each stage. Preliminary results showed that the application of -40 mmHg i.e. moderate stage simulated hemorrhage resulted significant changes in HR (85±4 bpm vs 68 ± 5bpm, p < 0.01), ST (191 ± 10 ms vs 253 ± 31 ms, p < 0.05), LVET (350 ± 14 ms vs 479 ± 47 ms, p < 0.05) and DT (551 ± 22 ms vs 683 ± 59 ms, p < 0.05) compared to rest, while no change was observed in SA (p > 0.05) as a consequence of LBNP application. These findings demonstrated the potential of cardiac signals in detecting moderate hemorrhage. In future, we will analyze all the LBNP stages and investigate the feasibility of other physiological signals to develop a predictive machine learning model for early detection of hemorrhage.

Keywords: blood pressure, hemorrhage, lower-body negative pressure, LBNP, machine learning

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11350 Enhanced Near-Infrared Upconversion Emission Based Lateral Flow Immunoassay for Background-Free Detection of Avian Influenza Viruses

Authors: Jaeyoung Kim, Heeju Lee, Huijin Jung, Heesoo Pyo, Seungki Kim, Joonseok Lee

Abstract:

Avian influenza viruses (AIV) are the primary cause of highly contagious respiratory diseases caused by type A influenza viruses of the Orthomyxoviridae family. AIV are categorized on the basis of types of surface glycoproteins such as hemagglutinin and neuraminidase. Certain H5 and H7 subtypes of AIV have evolved to the high pathogenic avian influenza (HPAI) virus, which has caused considerable economic loss to the poultry industry and led to severe public health crisis. Several commercial kits have been developed for on-site detection of AIV. However, the sensitivity of these methods is too low to detect low virus concentrations in clinical samples and opaque stool samples. Here, we introduced a background-free near-infrared (NIR)-to-NIR upconversion nanoparticle-based lateral flow immunoassay (NNLFA) platform to yield a sensor that detects AIV within 20 minutes. Ca²⁺ ion in the shell was used to enhance the NIR-to-NIR upconversion photoluminescence (PL) emission as a heterogeneous dopant without inducing significant changes in the morphology and size of the UCNPs. In a mixture of opaque stool samples and gold nanoparticles (GNPs), which are components of commercial AIV LFA, the background signal of the stool samples mask the absorption peak of GNPs. However, UCNPs dispersed in the stool samples still show strong emission centered at 800 nm when excited at 980 nm, which enables the NNLFA platform to detect 10-times lower viral load than a commercial GNP-based AIV LFA. The detection limit of NNLFA for low pathogenic avian influenza (LPAI) H5N2 and HPAI H5N6 viruses was 10² EID₅₀/mL and 10³.⁵ EID₅₀/mL, respectively. Moreover, when opaque brown-colored samples were used as the target analytes, strong NIR emission signal from the test line in NNLFA confirmed the presence of AIV, whereas commercial AIV LFA detected AIV with difficulty. Therefore, we propose that this rapid and background-free NNLFA platform has the potential of detecting AIV in the field, which could effectively prevent the spread of these viruses at an early stage.

Keywords: avian influenza viruses, lateral flow immunoassay on-site detection, upconversion nanoparticles

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11349 Environmental Impacts Assessment of Power Generation via Biomass Gasification Systems: Life Cycle Analysis (LCA) Approach for Tars Release

Authors: Grâce Chidikofan, François Pinta, A. Benoist, G. Volle, J. Valette

Abstract:

Statement of the Problem: biomass gasification systems may be relevant for decentralized power generation from recoverable agricultural and wood residues available in rural areas. In recent years, many systems have been implemented in all over the world as especially in Cambodgia, India. Although they have many positive effects, these systems can also affect the environment and human health. Indeed, during the process of biomass gasification, black wastewater containing tars are produced and generally discharged in the local environment either into the rivers or on soil. However, in most environmental assessment studies of biomass gasification systems, the impact of these releases are underestimated, due to the difficulty of identification of their chemical substances. This work deal with the analysis of the environmental impacts of tars from wood gasification in terms of human toxicity cancer effect, human toxicity non-cancer effect, and freshwater ecotoxicity. Methodology: A Life Cycle Assessment (LCA) approach was adopted. The inventory of tars chemicals substances was based on experimental data from a downdraft gasification system. The composition of six samples from two batches of raw materials: one batch made of tree wood species (oak+ plane tree +pine) at 25 % moisture content and the second batch made of oak at 11% moisture content. The tests were carried out for different gasifier load rates, respectively in the range 50-75% and 50-100%. To choose the environmental impacts assessment method, we compared the methods available in SIMAPRO tool (8.2.0) which are taking into account most of the chemical substances. The environmental impacts for 1kg of tars discharged were characterized by ILCD 2011+ method (V.1.08). Findings Experimental results revealed 38 important chemical substances in varying proportion from one test to another. Only 30 are characterized by ILCD 2011+ method, which is one of the best performing methods. The results show that wood species or moisture content have no significant impact on human toxicity noncancer effect (HTNCE) and freshwater ecotoxicity (FWE) for water release. For human toxicity cancer effect (HTCE), a small gap is observed between impact factors of the two batches, either 3.08E-7 CTUh/kg against 6.58E-7 CTUh/kg. On the other hand, it was found that the risk of negative effects is higher in case of tar release into water than on soil for all impact categories. Indeed, considering the set of samples, the average impact factor obtained for HTNCE varies respectively from 1.64 E-7 to 1.60E-8 CTUh/kg. For HTCE, the impact factor varies between 4.83E-07 CTUh/kg and 2.43E-08 CTUh/kg. The variability of those impact factors is relatively low for these two impact categories. Concerning FWE, the variability of impact factor is very high. It is 1.3E+03 CTUe/kg for tars release into water against 2.01E+01 CTUe/kg for tars release on soil. Statement concluding: The results of this study show that the environmental impacts of tars emission of biomass gasification systems can be consequent and it is important to investigate the ways to reduce them. For environmental research, these results represent an important step of a global environmental assessment of the studied systems. It could be used to better manage the wastewater containing tars to reduce as possible the impacts of numerous still running systems all over the world.

Keywords: biomass gasification, life cycle analysis, LCA, environmental impact, tars

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11348 Human Resource Utilization Models for Graceful Ageing

Authors: Chuang-Chun Chiou

Abstract:

In this study, a systematic framework of graceful ageing has been used to explore the possible human resource utilization models for graceful ageing purpose. This framework is based on the Chinese culture. We call ‘Nine-old’ target. They are ageing gracefully with feeding, accomplishment, usefulness, learning, entertainment, care, protection, dignity, and termination. This study is focused on two areas: accomplishment and usefulness. We exam the current practices of initiatives and laws of promoting labor participation. That is to focus on how to increase Labor Force Participation Rate of the middle aged as well as the elderly and try to promote the elderly to achieve graceful ageing. Then we present the possible models that support graceful ageing.

Keywords: human resource utilization model, labor participation, graceful ageing, employment

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11347 Kinematic Hardening Parameters Identification with Respect to Objective Function

Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

Abstract:

Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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11346 Identification of Flooding Attack (Zero Day Attack) at Application Layer Using Mathematical Model and Detection Using Correlations

Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

Abstract:

Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

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11345 Evaluation of Microbiological Quality and Safety of Two Types of Salads Prepared at Libyan Airline Catering Center in Tripoli

Authors: Elham A. Kwildi, Yahia S. Abugnah, Nuri S. Madi

Abstract:

This study was designed to evaluate the microbiological quality and safety of two types of salads prepared at a catering center affiliated with Libyan Airlines in Tripoli, Libya. Two hundred and twenty-one (221) samples (132 economy-class and 89 first- class) were used in this project which lasted for ten months. Biweekly, microbiological tests were performed which included total plate count (TPC) and total coliforms (TCF), in addition to enumeration and/or detection of some pathogenic bacteria mainly Escherichia coli, Staphylococcus aureus, Bacillus cereus, Salmonella sp, Listeria sp and Vibrio parahaemolyticus parahaemolyticus, By using conventional as well as compact dry methods. Results indicated that TPC of type 1 salad ranged between (<10 – 62 x 103 cfu/gm) and (<10 to 36 x103 cfu/g), while TCF were (<10 – 41 x 103 cfu/gm) and (< 10 to 66 x102 cfu/g) using both methods of detection respectively. On the other hand, TPC of type 2 salad were: (1 × 10 – 52 x 103) and (<10 – 55 x 103 cfu/gm) and in the range of (1 x10 to 45x103 cfu/g), and the (TCF) counts were between (< 10 to 55x103 cfu/g) and (< 10 to 34 x103 cfu/g) using the 1st and the 2nd methods of detection respectively. Also, the pathogens mentioned above were detected in both types of salads, but their levels varied according to the type of salad and the method of detection. The level of Staphylococcus aureus, for instance, was 17.4% using conventional method versus 14.4% using the compact dry method. Similarly, E. coli was 7.6% and 9.8%, while Salmonella sp. recorded the least percentage i.e. 3% and 3.8% with the two mentioned methods respectively. First class salads were also found to contain the same pathogens, but the level of E. coli was relatively higher in this case (14.6% and 16.9%) using conventional and compact dry methods respectively. The second rank came Staphylococcus aureus (13.5%) and (11.2%), followed by Salmonella (6.74%) and 6.70%). The least percentage was for Vibrio parahaemolyticus (4.9%) which was detected in the first class salads only. The other two pathogens Bacillus cereus and Listeria sp. were not detected in either one of the salads. Finally, it is worth mentioning that there was a significant decline in TPC and TCF counts in addition to the disappearance of pathogenic bacteria after the 6-7th month of the study which coincided with the first trial of the HACCP system at the center. The ups and downs in the counts along the early stages of the study reveal that there is a need for some important correction measures including more emphasis on training of the personnel in applying the HACCP system effectively.

Keywords: air travel, vegetable salads, foodborne outbreaks, Libya

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