Search results for: cancer detection

Authors: Chanya Jetsukontorn

Abstract:

Dengue hemorrhagic fever is the most important Mosquito-borne disease and the major public health problem in Thailand. The most important vector is Aedes aegypti. Environmental factors such as temperature, relative humidity, and biting rate affect dengue virus infection. The most effective measure for prevention is controlling of vector mosquitoes. In addition, surveillance of field-caught mosquitoes is imperative for determining the natural vector and can provide an early warning sign at risk of transmission in an area. In this study, Aedes aegypti mosquitoes were collected in Amphur Muang, Phetchabun Province, Thailand. The mosquitoes were collected in the rainy season and the dry season both indoor and outdoor. During mosquito’s collection, the data of environmental factors such as temperature, humidity and breeding sites were observed and recorded. After identified to species, mosquitoes were pooled according to genus/species, and sampling location. Pools consisted of a maximum of 10 Aedes mosquitoes. 70 pools of 675 Aedes aegypti were screened with RT-PCR for flaviviruses. To confirm individual infection for determining True infection rate, individual mosquitoes which gave positive results of flavivirus detection were tested for dengue virus by RT-PCR. The infection rate was 5.93% (4 positive individuals from 675 mosquitoes). The probability to detect dengue virus in mosquitoes at the neighbour’s houses was 1.25 times, especially where distances between neighboring houses and patient’s houses were less than 50 meters. The relative humidity in dengue-infected villages with dengue-infected mosquitoes was significantly higher than villages that free from dengue-infected mosquitoes. Indoor biting rate of Aedes aegypti was 14.87 times higher than outdoor, and biting times of 09.00-10.00, 10.00-11.00, 11.00-12.00 yielded 1.77, 1.46, 0.68mosquitoes/man-hour, respectively. These findings confirm environmental factors were related to Dengue infection in Thailand. Data obtained from this study will be useful for the prevention and control of the diseases.

Keywords: Aedes aegypti, Dengue virus, environmental factors, one health, PCR

Procedia PDF Downloads 144

Authors: Eric Dede, Marcus Tindall, John W. Cherrie, Steve Hankin, Christopher Collins

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Current exposure models used in contaminated land risk assessment are highly conservative. Use of these models may lead to over-estimation of actual exposures, possibly resulting in negative financial implications due to un-necessary remediation. Thus, we are carrying out a study seeking to improve our understanding of human exposure to selected toxic elements in soil: arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), and lead (Pb) resulting from allotment land-use. The study employs biomonitoring and physiologically-based pharmacokinetic (PBPK) modelling to quantify human exposure to these elements. We recruited 37 allotment users (adults > 18 years old) in Scotland, UK, to participate in the study. Concentrations of the elements (and their bioaccessibility) were measured in allotment samples (soil and allotment produce). Amount of produce consumed by the participants and participants’ biological samples (urine and blood) were collected for up to 12 consecutive months. Ethical approval was granted by the University of Reading Research Ethics Committee. PBPK models (coded in MATLAB) were used to estimate the distribution and accumulation of the elements in key body compartments, thus indicating the internal body burden. Simulating low element intake (based on estimated ‘doses’ from produce consumption records), predictive models suggested that detection of these elements in urine and blood was possible within a given period of time following exposure. This information was used in planning biomonitoring, and is currently being used in the interpretation of test results from biological samples. Evaluation of the models is being carried out using biomonitoring data, by comparing model predicted concentrations and measured biomarker concentrations. The PBPK models will be used to generate bioavailability values, which could be incorporated in contaminated land exposure models. Thus, the findings from this study will promote a more sustainable approach to contaminated land management.

Keywords: biomonitoring, exposure, PBPK modelling, toxic elements

Procedia PDF Downloads 319

Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

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The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

Procedia PDF Downloads 109

Authors: Fumihiro Ima, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know growth rate of brain tumors before surgery because it influences treatment planning including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without administration of contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients and WHO grade 4 in 2 patients), meningioma WHO grade1 in 2 patients and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW-signals than that in low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW-signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

Procedia PDF Downloads 137

Authors: Mohammed Seyam, Faridah Othman, Ahmed El-Shafie

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The early warning of high stream flow events (HSF) and floods is an important aspect in the management of surface water and rivers systems. This process can be performed using either process-based models or data driven-based models such as artificial intelligence (AI) techniques. The main goal of this study is to develop efficient AI-based model for predicting the real-time hourly stream flow (Q) and apply it as early warning tool of HSF and floods in the downstream area of the Selangor River basin, taken here as a paradigm of humid tropical rivers in Southeast Asia. The performance of AI-based models has been improved through the integration of the lag time (Lt) estimation in the modelling process. A total of 8753 patterns of Q, water level, and rainfall hourly records representing one-year period (2011) were utilized in the modelling process. Six hydrological scenarios have been arranged through hypothetical cases of input variables to investigate how the changes in RF intensity in upstream stations can lead formation of floods. The initial SF was changed for each scenario in order to include wide range of hydrological situations in this study. The performance evaluation of the developed AI-based model shows that high correlation coefficient (R) between the observed and predicted Q is achieved. The AI-based model has been successfully employed in early warning throughout the advance detection of the hydrological conditions that could lead to formations of floods and HSF, where represented by three levels of severity (i.e., alert, warning, and danger). Based on the results of the scenarios, reaching the danger level in the downstream area required high RF intensity in at least two upstream areas. According to results of applications, it can be concluded that AI-based models are beneficial tools to the local authorities for flood control and awareness.

Keywords: floods, stream flow, hydrological modelling, hydrology, artificial intelligence

Procedia PDF Downloads 247

Authors: Van Trieu, Shouhuai Xu, Yusheng Feng

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Tracking attack trajectories can be difficult, with limited information about the nature of the attack. Even more difficult as attack information is collected by Intrusion Detection Systems (IDSs) due to the current IDSs having some limitations in identifying malicious and anomalous traffic. Moreover, IDSs only point out the suspicious events but do not show how the events relate to each other or which event possibly cause the other event to happen. Because of this, it is important to investigate new methods capable of performing the tracking of attack trajectories task quickly with less attack information and dependency on IDSs, in order to prioritize actions during incident responses. This paper proposes a two-level graph causality framework for tracking attack trajectories in internet networks by leveraging observable malicious behaviors to detect what is the most probable attack events that can cause another event to occur in the system. Technically, given the time series of malicious events, the framework extracts events with useful features, such as attack time and port number, to apply to the conditional independent tests to detect the relationship between attack events. Using the academic datasets collected by IDSs, experimental results show that the framework can quickly detect the causal pairs that offer meaningful insights into the nature of the internet network, given only reasonable restrictions on network size and structure. Without the framework’s guidance, these insights would not be able to discover by the existing tools, such as IDSs. It would cost expert human analysts a significant time if possible. The computational results from the proposed two-level graph network model reveal the obvious pattern and trends. In fact, more than 85% of causal pairs have the average time difference between the causal and effect events in both computed and observed data within 5 minutes. This result can be used as a preventive measure against future attacks. Although the forecast may be short, from 0.24 seconds to 5 minutes, it is long enough to be used to design a prevention protocol to block those attacks.

Keywords: causality, multilevel graph, cyber-attacks, prediction

Procedia PDF Downloads 156

Authors: Barry D. Kyle, Jessica Boyd, Robin Pickersgill, Nicole Squires, Cynthia Balion

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Background-Aim: Fentanyl is a highly-potent synthetic μ-opioid receptor agonist used for exceptional pain management. Its main metabolite, norfentanyl, is typically present in urine at significantly high concentrations (i.e. ~20%) representing an effective targeting molecule for immunoassay detection. Here, we evaluated the NCS^TM One Step Fentanyl Test Device© and the BTNX Rapid Response^TM Single Drug Test Strip© point of care (POC) test strips targeting norfentanyl (20 ng/ml) and fentanyl (100 ng/ml) molecules for potential risperidone interference. Methods: POC tests calibrated against norfentanyl (20 ng/ml) used [immunochromatographic] lateral flow devices to provide qualitative results within five minutes of urine sample contact. Results were recorded as negative if lines appeared in the test and control regions according to manufacturer’s instructions. Positive results were recorded if no line appeared in the test region (i.e., control line only visible). Pooled patient urine (n=20), that screened negative for drugs of abuse (using NCS One Step Multi-Line Screen) and fentanyl (using BTNX Rapid Response Strip) was used for spiking studies. Urine was spiked with risperidone alone and with combinations of fentanyl, norfentanyl and/or risperidone to evaluate cross-reactivity in each test device. Results: A positive screen result was obtained when 8,000 ng/mL of risperidone was spiked into drug free urine using the NCS test device. Positive screen results were also obtained in spiked urine samples containing fentanyl and norfentanyl combinations below the cut-off concentrations when 4000 ng/mL risperidone was present using the NCS testing device. There were no screen positive test results using the BTNX test strip with up to 8,000 ng/mL alone or in combination with concentrations of fentanyl and norfentanyl below the cut-off. Both devices screened positive when either fentanyl or norfentanyl exceeded the cut-off threshold in the absence and presence of risperidone. Conclusion: We report that urine samples containing risperidone may give a false positive result using the NCS One Step Fentanyl Test Device.

Keywords: fentanyl, interferences, point of care test, Risperidone

Procedia PDF Downloads 274

Authors: Jeroen De Ceuster

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This study is the first empirical analysis of the link between corporate governance and European Union competition law. Although competition law enforcement is often studied through the lens of competition law, we offer an alternative perspective by looking at a number of corporate governance factor at the level of the board of directors. We find that undertakings where the Chief Executive Officer is also chairman of the board are twice as likely to violate European Union competition law. No significant relationship was found between European Union competition law infringements and gender diversity of the board, the size of the board, the percentage of directors appointed after the Chief Executive Officer, the percentage of independent directors, or the presence of corporate social responsibility (CSR) committee. This contribution is based on a 1-1 matched peer study. Our sample includes all ultimate parent companies with a board that have been sanctioned by the European Commission for either anticompetitive agreements or abuse of dominance for the period from 2004 to 2018. These companies were matched to a company with headquarters in the same country, belongs to the same industry group, is active in the European Economic Area, and is the nearest neighbor to the infringing company in terms of revenue. Our final sample includes 121 pairs. As is common with matched peer studies, we use CLR to analyze the differences within these pairs. The only statistically significant independent variable after controlling for size and performance is CEO/Chair duality. The results indicate that companies whose Chief Executive Officer also functions as chairman of the board are twice as likely to infringe European Union competition law. This is in line with the monitoring theory of the board of directors, which states that its primary function is to monitor top management. Since competition law infringements are mostly organized by management and hidden from board directors, the results suggest that a Chief Executive Officer who is also chairman is more likely to be either complicit in the infringement or less critical towards his day-to-day colleagues and thus impedes proper detection by the board of competition law infringements.

Keywords: corporate governance, competition law, board of directors, board independence, ender diversity, corporate social responisbility

Procedia PDF Downloads 138

Authors: Maftunakhon Latipova, Feruza Khaydarova

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Obesity is considered a chronic metabolic disease that occurs at any age. Regulation of body weight in the body is carried out through complex interaction of a complex of interrelated systems that control the body's energy system. Energy imbalance is the cause of obesity and overweight, in which the supply of energy from food exceeds the energy needs of the body. Obesity is closely related to impaired appetite regulation, and a hypothalamus is a key place for neural regulation of food consumption. The nucleus of the hypothalamus is connected and interdependent on receiving, integrating and sending hunger signals to regulate appetite. Purpose of the study: to identify markers of food behavior. Materials and methods: The screening was carried out to identify eating disorders in 200 men and women aged 18 to 35 years with overweight and obesity and to check the effects of Orexin A and Neuropeptide Y markers. A questionnaire and questionnaires were conducted with over 200 people aged 18 to 35 years. Questionnaires were for eating disorders and hidden depression (on the Zang scale). Anthropometry is measured by OT, OB, BMI, Weight, and Height. Based on the results of the collected data, 3 groups were divided: People with obesity, People with overweight, Control Group of Healthy People. Results: Of the 200 analysed persons, 86% had eating disorders. Of these, 60% of eating disorders were associated with childhood. According to the Zang test result: Normal condition was about 37%, mild depressive disorder 20%, moderate depressive disorder 25% and 18% of people suffered from severe depressive disorder without knowing it. One group of people with obesity had eating disorders and moderate and severe depressive disorder, and group 2 was overweight with mild depressive disorder. According to laboratory data, the first group had the lowest concentration of Orexin A and Neuropeptide U in blood serum. Conclusions: Being overweight and obese are the first signal of many diseases, and prevention and detection of these disorders will prevent various diseases, including type 2 diabetes. Obesity etiology is associated with eating disorders and signal transmission of the orexinorghetic system of the hypothalamus.

Keywords: obesity, endocrinology, hypothalamus, overweight

Procedia PDF Downloads 74

Authors: Innocent Uzougbo Onwuegbuzie

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Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

Procedia PDF Downloads 34

Authors: Tarek Duzan

Abstract:

Fractures are a fundamental property of most reservoirs. Despite their abundance, they remain difficult to detect and quantify. The most effective characterization of fractured reservoirs is accomplished by integrating geological, geophysical, and engineering data. Detection of fractures and defines their relative contribution is crucial in the early stages of exploration and later in the production of any field. Because fractures could completely change our thoughts, efforts, and planning to produce a specific field properly. From the structural point of view, all reservoirs are fractured to some point of extent. North Gialo field is thought to be a naturally fractured reservoir to some extent. Historically, natural fractured reservoirs are more complicated in terms of their exploration and production efforts, and most geologists tend to deny the presence of fractures as an effective variable. Our aim in this paper is to determine the degree of fracturing, and consequently, our evaluation and planning can be done properly and efficiently from day one. The challenging part in this field is that there is no enough data and straightforward well testing that can let us completely comfortable with the idea of fracturing; however, we cannot ignore the fractures completely. Logging images, available well testing, and limited core studies are our tools in this stage to evaluate, model, and predict possible fracture effects in this reservoir. The aims of this study are both fundamental and practical—to improve the prediction and diagnosis of natural-fracture attributes in N. Gialo hydrocarbon reservoirs and accurately simulate their influence on production. Moreover, the production of this field comes from 2-phase plan; a self depletion of oil and then gas injection period for pressure maintenance and increasing ultimate recovery factor. Therefore, well understanding of fracturing network is essential before proceeding with the targeted plan. New analytical methods will lead to more realistic characterization of fractured and faulted reservoir rocks. These methods will produce data that can enhance well test and seismic interpretations, and that can readily be used in reservoir simulators.

Keywords: natural fracture, sandstone reservoir, geological, geophysical, and engineering data

Procedia PDF Downloads 92

Authors: Sungho Kim, Jaechoul Shin, Yujin Baek, Nakseok Kim, Kyungnam Kim, Shinhaeng Jo

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The climate change and increase in heavy traffic have been accelerating damages that cause the problems such as pothole on asphalt pavement. Pothole causes traffic accidents, vehicle damages, road casualties and traffic congestion. A quick and efficient maintenance method is needed because pothole is caused by stripping and accelerates pavement distress. In this study, we propose a rapid and systematic pothole management by developing a pothole automated repairing equipment including a volume measurement system of pothole. Three kinds of cold mix asphalt mixture were investigated to select repair materials. The materials were evaluated for satisfaction with quality standard and applicability to automated equipment. The volume measurement system of potholes was composed of multi-sensor that are combined with laser sensor and ultrasonic sensor and installed in front and side of the automated repair equipment. An algorithm was proposed to calculate the amount of repair material according to the measured pothole volume, and the system for releasing the correct amount of material was developed. Field test results showed that the loss of repair material amount could be reduced from approximately 20% to 6% per one point of pothole. Pothole rapid automated repair equipment will contribute to improvement on quality and efficient and economical maintenance by not only reducing materials and resources but also calculating appropriate materials. Through field application, it is possible to improve the accuracy of pothole volume measurement, to correct the calculation of material amount, and to manage the pothole data of roads, thereby enabling more efficient pavement maintenance management. Acknowledgment: The author would like to thank the MOLIT(Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: automated equipment, management, multi-beam sensor, pothole

Procedia PDF Downloads 222

Authors: Fumihiro Imai, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

Abstract:

It is important to know the growth rate of brain tumors before surgery because it influences treatment planning, including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without the administration of a contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after a clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients, and WHO grade 4 in 2 patients), meningioma WHO grade 1 in 2 patients, and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW signals than that low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

Procedia PDF Downloads 84

Authors: Jelka Pleadin, Greta Krešić, Tina Lešić, Ana Vulić, Renata Barić, Tanja Bogdanović, Dražen Oraić, Ana Legac, Snježana Zrnčić

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Fish has been acknowledged as an integral component of a well-balanced diet, providing a healthy source of energy, high-quality proteins, vitamins, essential minerals and, especially, n-3 long-chain polyunsaturated fatty acids (n-3 LC PUFA), mainly eicosapentaenoic acid (20:5 n-3 EPA), and docosahexaenoicacid, (22:6 n-3 DHA), whose pleiotropic effects in terms of health promotion and disease prevention have been increasingly recognised. In this study, the fatty acids composition of three commercially important farmed fish species: sea bream (Sparus aurata), sea bass (Dicentrarchus labrax) and dentex (Dentex dentex) was investigated. In total, 60 fish samples were retrieved during 2015 (n = 30) and 2016 (n = 30) from different locations in the Adriatic Sea. Methyl esters of fatty acids were analysed using gas chromatography (GC) with flame ionization detection (FID). The results show that the most represented fatty acid in all three analysed species is oleic acid (C18:1n-9, OA), followed by linoleic acid (C18:2n-6, LA) and palmitic acid (C16:0, PA). Dentex was shown to have two to four times higher eicosapentaenoic (EPA) and docosahexaenoic (DHA) acid content as compared to sea bream and sea bass. The recommended n-6/n-3 ratio was determined in all fish species but obtained results pointed to statistically significant differences (p < 0.05) in fatty acid composition among the analysed fish species and their potential as a dietary source of valuable fatty acids. Sea bass and sea bream had a significantly higher proportion of n-6 fatty acids, while dentex had a significantly higher proportion of n-3 (C18:4n-3, C20:4n-3, EPA, DHA) fatty acids. A higher hypocholesterolaemic and hypercholesterolaemic fatty acids (HH) ratio was determined for sea bass and sea bream, which comes as the consequence of a lower share of SFA determined in these two species in comparison to dentex. Since the analysed fish species vary in their fatty acids composition consumption of diverse fish species would be advisable. Based on the established lipid quality indicators, dentex, a fish species underutilised by the aquaculture, seems to be a highly recommendable and important source of fatty acids recommended to be included into the human diet.

Keywords: dentex, fatty acids, farmed fish, sea bass, sea bream

Procedia PDF Downloads 390

Authors: Mohammad Nazri Abdul Bahari, Nurshafika Mohd Sakeh, Siti Nor Akmar Abdullah

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Basal stem rot (BSR) is the most devastating disease in oil palm. Among the oil palm pathogenic fungi, the most prevalent and virulent species associated with BSR is Ganoderma boninense. Early detection of G. boninense attack in oil palm wherein physical symptoms has not yet appeared can offer opportunities to prevent the spread of the necrotrophic fungus. However, poor understanding of molecular defense responses and roles of antifungal metabolites in oil palm against G. boninense has complicated the resolving measures. Hence, characterization of defense-related molecular responses and production of antifungal compounds during early interaction with G. boninense is of utmost important. Four month-old oil palm (Elaeis guineensis) seedlings were artificially infected with G. boninense-inoculated rubber wood block via sitting technique. RNA of samples were extracted from roots and leaves tissues at 0, 3, 7 and 11 days post inoculation (d.p.i) followed with sequencing using RNA-Seq method. Differentially-expressed genes (DEGs) of oil palm-G. boninense interaction were identified, while changes in metabolite profile will be scrutinized related to the DEGs. The RNA-Seq data generated a total of 113,829,376 and 313,293,229 paired-end clean reads from untreated (0 d.p.i) and treated (3, 7, 11 d.p.i) samples respectively, each with two biological replicates. The paired-end reads were mapped to Elaeis guineensis reference genome to screen out non-oil palm genes and subsequently generated 74,794 coding sequences. DEG analysis of phytohormone biosynthetic genes in oil palm roots revealed that at p-value ≤ 0.01, ethylene and jasmonic acid may act in antagonistic manner with salicylic acid to coordinate defense response at early interaction with G. boninense. Findings on metabolite profiling of G. boninense-infected oil palm roots and leaves are hoped to explain the defense-related compounds elicited by Elaeis guineensis in response to G. boninense colonization. The study aims to shed light on molecular defense response of oil palm at early interaction with G. boninense and promote prevention measures against Ganoderma infection.

Keywords: Ganoderma boninense, metabolites, phytohormones, RNA-Seq

Procedia PDF Downloads 264

Authors: Marisol Warthon-Medina, Jenny Plumb, Ayoub Aljawaldeh, Mark Roe, Ailsa Welch, Maria Glibetic, Paul M. Finglas

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Similar to Western Countries, the Eastern Mediterranean Region (EMR) also presents major public health issues associated with the increased consumption of sugar, fat, and salt. Therefore, one of the policies of the World Health Organization’s (WHO) EMR is to reduce the intake of salt, sugar, and fat (Saturated fatty acids, trans fatty acids) to address the risk of non-communicable diseases (i.e. diabetes, cardiovascular disease, cancer) and obesity. The project objective is to assess status and provide training and capacity development in the use of improved standardized methodologies for updated food composition data, dietary intake methods, use of suitable biomarkers of nutritional value and determine health outcomes in low and middle-income countries (LMIC). Training exchanges have been developed with clusters of countries created resulting from regional needs including Sudan, Egypt and Jordan; Tunisia, Morocco, and Mauritania; and other Middle Eastern countries. This capacity building will lead to the development and sustainability of up-to-date national and regional food composition databases in LMIC for use in dietary monitoring assessment in food and nutrient intakes. Workshops were organized to provide training and capacity development in the use of improved standardized methodologies for food composition and food intake. Training needs identified and short-term scientific missions organized for LMIC researchers including (1) training and knowledge exchange workshops, (2) short-term exchange of researchers, (3) development and application of protocols and (4) development of strategies to reduce sugar and fat intake. An initial training workshop, Morocco 2018 was attended by 25 participants from 10 EMR countries to review status and support development of regional food composition. 4 training exchanges are in progress. The use of improved standardized methodologies for food composition and dietary intake will produce robust measurements that will reinforce dietary monitoring and policy in LMIC. The capacity building from this project will lead to the development and sustainability of up-to-date national and regional food composition databases in EMR countries. Supported by the UK Medical Research Council, Global Challenges Research Fund, (MR/R019576/1), and the World Health Organization’s Eastern Mediterranean Region.

Keywords: dietary intake, food composition, low and middle-income countries, status.

Procedia PDF Downloads 160

Authors: Yanghui Xu, Qin Ou, Xintu Wang, Feng Hou, Peng Li, Jan Peter van der Hoek, Gang Liu

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The level and removal of microplastics (MPs) in wastewater treatment plants (WWTPs) has been well evaluated by the particle number, while the mass concentration of MPs and especially nanoplastics (NPs) remains unclear. In this study, microfiltration, ultrafiltration and hydrogen peroxide digestion were used to extract MPs and NPs with different size ranges (0.01−1, 1−50, and 50−1000 μm) across the whole treatment schemes in two WWTPs. By identifying specific pyrolysis products, pyrolysis gas chromatography−mass spectrometry were used to quantify their mass concentrations of selected six types of polymers (i.e., polymethyl methacrylate (PMMA), polypropylene (PP), polystyrene (PS), polyethylene (PE), polyethylene terephthalate (PET), and polyamide (PA)). The mass concentrations of total MPs and NPs decreased from 26.23 and 11.28 μg/L in the influent to 1.75 and 0.71 μg/L in the effluent, with removal rates of 93.3 and 93.7% in plants A and B, respectively. Among them, PP, PET and PE were the dominant polymer types in wastewater, while PMMA, PS and PA only accounted for a small part. The mass concentrations of NPs (0.01−1 μm) were much lower than those of MPs (>1 μm), accounting for 12.0−17.9 and 5.6− 19.5% of the total MPs and NPs, respectively. Notably, the removal efficiency differed with the polymer type and size range. The low-density MPs (e.g., PP and PE) had lower removal efficiency than high-density PET in both plants. Since particles with smaller size could pass the tertiary sand filter or membrane filter more easily, the removal efficiency of NPs was lower than that of MPs with larger particle size. Based on annual wastewater effluent discharge, it is estimated that about 0.321 and 0.052 tons of MPs and NPs were released into the river each year. Overall, this study investigated the mass concentration of MPs and NPs with a wide size range of 0.01−1000 μm in wastewater, which provided valuable information regarding the pollution level and distribution characteristics of MPs, especially NPs, in WWTPs. However, there are limitations and uncertainties in the current study, especially regarding the sample collection and MP/NP detection. The used plastic items (e.g., sampling buckets, ultrafiltration membranes, centrifugal tubes, and pipette tips) may introduce potential contamination. Additionally, the proposed method caused loss of MPs, especially NPs, which can lead to underestimation of MPs/NPs. Further studies are recommended to address these challenges about MPs/NPs in wastewater.

Keywords: microplastics, nanoplastics, mass concentration, WWTPs, Py-GC/MS

Procedia PDF Downloads 278

Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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Authors: Benlaifa Meriem, Berredjem Hajira, Bouasla Radia, Berredjem Malika, Djebar Med Reda

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Toxoplasmosis is a cosmopolitan infection due to Toxoplasma gondii (T.gondii). It is a significant cause of congenital disease and an important opportunistic pathogen which has become a worldwide increasing problem due to the AIDS epidemic. Current available drugs do not give satisfactory results and often have only a static and several adverse side effects as it is the case of pyrimethamine. So, the need to develop and evaluate new drugs is critical. The purpose of this study is to investigate the in vitro and in vivo effects of the new chiral N-acylsulfonamide bis-oxazolidin-2-ones on T.gondii. In this study, anti-T.gondii RH strain activities, of two new chiral N-acylsulfonamide bis-oxazolidin-2-ones were evaluated in vitro, using a MRC-5 fibroblast tissue cultures to determine the concentration that inhibit parasite multiplication by 50% (IC50) of each drug and in vivo, by PCR detection of the tachyzoites in mice ascites after new molecules treatment, using the 35-fold repetitive B1 gene of T.gondii. The in vitro results demonstrated that the treatment with the tested molecules decreased the amount of tachyzoites in cell culture in a dose-dependent manner. The inhibition was complete for concentrations over 4 mg/ml. The IC50 of Mol 1 and Mol 2 were 1.5 and 3 mg/ml, respectively, and were quite similar to the control one (2 mg/ml). The Mol 1 was highly active against T.gondii in cell cultures than Mol 2; these results were similar to those of sulfadiazine-treated group (p < 0.05). Toxoplasma-specific DNA was demonstrated in all ascites samples from infected mice of the different tested groups. Mol 1 showed better effect than Mol 2, but it did not completely inhibit the parasite proliferation. The intensity of amplification products increased when the treatment started late after infection. These findings suggest continuous parasite replication despite the treatment. In conclusion, our results showed a promising treatment effect of the tested molecules and suggest that in vitro, the Mol 1, and Mol 2 have a dose-dependent effect and a high cytotoxicity on the studied cells. The present study revealed that concentration and duration of tested molecules treatment are major factors that influence the course of Toxoplasma infection in infected mice.

Keywords: cytotoxicity, PCR, sulfonamide, Toxoplasma gondii

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Authors: T. Abbas, J. McEvoy, E. Khan

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Pesticide contamination in water supply is a common environmental problem in rural agricultural communities. Advanced water treatment processes such as membrane filtration and adsorption on activated carbon only remove pesticides from water without degrading them into less toxic/easily degradable compounds leaving behind contaminated brine and activated carbon that need to be managed. Rural communities which normally cannot afford expensive water treatment technologies need an economical and sustainable filter which not only treats pesticides from water but also degrades them into benign products. In this study, iron turning waste experimented as potential point-of-use filtration media for the removal/degradation of a mixture of six chlorinated pesticides (lindane, heptachlor, endosulfan, dieldrin, endrin, and DDT) in water. As a common and traditional medium for water filtration, sand was also tested along with iron turning waste. Iron turning waste was characterized using scanning electron microscopy and energy dispersive X-Ray analyzer. Four glass columns with different filter media layer configurations were set up: (1) only sand, (2) only iron turning, (3) sand and iron turning (two separate layers), and (4) sand, iron turning and sand (three separate layers). The initial pesticide concentration and flow rate were 2 μg/L and 10 mL/min. Results indicate that sand filtration was effective only for the removal of DDT (100%) and endosulfan (94-96%). Iron turning filtration column effectively removed endosulfan, endrin, and dieldrin (85-95%) whereas the lindane and DDT removal were 79-85% and 39-56%, respectively. The removal efficiencies for heptachlor, endosulfan, endrin, dieldrin, and DDT were 90-100% when sand and iron turning waste (two separate layers) were used. However, better removal efficiencies (93-100%) for five out of six pesticides were achieved, when sand, iron turning and sand (three separate layers) were used as filtration media. Moreover, the effects of water pH, amounts of media, and minerals present in water such as magnesium, sodium, calcium, and nitrate on the removal of pesticides were examined. Results demonstrate that iron turning waste efficiently removed all the pesticides under studied parameters. Also, it completely de-chlorinated all the pesticides studied and based on the detection of by-products, the degradation mechanisms for all six pesticides were proposed.

Keywords: pesticide contamination, rural communities, iron turning waste, filtration

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Authors: Bahram Besharti, Hossein Navid, Hadi Karimi, Hossein Behfar, Iraj Eskandari

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Multiple or miss sowing by seed drills is a common problem on the farm. This problem causes overuse of seeds, wasting energy, rising crop treatment cost and reducing crop yield in harvesting. To be informed of mentioned faults and monitoring the performance of seed drills during sowing, developing a seed sensor for detecting seed mass flow rate and monitoring in a delivery tube is essential. In this research, an infrared seed sensor was developed to estimate seed mass flow rate in seed drills. The developed sensor comprised of a pair of spaced apart circuits one acting as an IR transmitter and the other acting as an IR receiver. Optical coverage in the sensing section was obtained by setting IR LEDs and photo-diodes directly on opposite sides. Passing seeds made interruption in radiation beams to the photo-diode which caused output voltages to change. The voltage difference of sensing units summed by a microcontroller and were converted to an analog value by DAC chip. The sensor was tested by using a roller seed metering device with three types of seeds consist of chickpea, wheat, and alfalfa (representing large, medium and fine seed, respectively). The results revealed a good fitting between voltage received from seed sensor and mass flow of seeds in the delivery tube. A linear trend line was set for three seeds collected data as a model of the mass flow of seeds. A final mass flow model was developed for various size seeds based on receiving voltages from the seed sensor, thousand seed weight and equivalent diameter of seeds. The developed infrared seed sensor, besides monitoring mass flow of seeds in field operations, can be used for the assessment of mechanical planter seed metering unit performance in the laboratory and provide an easy calibrating method for seed drills before planting in the field.

Keywords: seed flow, infrared, seed sensor, seed drills

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Authors: Goksen Arik, Mihriban Korukluoglu

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Lactic acid bacteria (LAB) and some yeast species are common microorganisms found in dairy products and most of them are responsible for the fermentation of foods. Such cultures are isolated and used as a starter culture in the food industry because of providing standardisation of the final product during the food processing. Choice of starter culture is the most important step for the production of fermented food. Isolated LAB and yeast cultures which have the ability to create a biofilm layer can be preferred as a starter in the food industry. The biofilm formation could be beneficial to extend the period of usage time of microorganisms as a starter. On the other hand, it is an undesirable property in pathogens, since biofilm structure allows a microorganism become more resistant to stress conditions such as antibiotic presence. It is thought that the resistance mechanism could be turned into an advantage by promoting the effective microorganisms which are used in the food industry as starter culture and also which have potential to stimulate the gastrointestinal system. Development of the biofilm layer is observed in some LAB and yeast strains. The resistance could make LAB and yeast strains dominant microflora in the human gastrointestinal system; thus, competition against pathogen microorganisms can be provided more easily. Based on this circumstance, in the study, 10 LAB and 10 yeast strains were isolated from various dairy products, such as cheese, yoghurt, kefir, and cream. Samples were obtained from farmer markets and bazaars in Bursa, Turkey. As a part of this research, all isolated strains were identified and their ability of biofilm formation was detected with two different methods and compared with each other. The first goal of this research was to determine whether isolates have the potential for biofilm production, and the second was to compare the validity of two different methods, which are known as “Tube method” and “96-well plate-based method”. This study may offer an insight into developing a point of view about biofilm formation and its beneficial properties in LAB and yeast cultures used as a starter in the food industry.

Keywords: biofilm, dairy products, lactic acid bacteria, yeast

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Authors: Graziella Ziino, Filippo Giarratana, Stefania Maria Marotta, Alessandro Giuffrida, Antonio Panebianco

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In Europe, North America and Japan, campylobacteriosis is one of the leading food-borne bacterial illnesses, often related to the consumption of poultry meats and/or by-products. The aim of this study was the evaluation of Campylobacter contamination of poultry meats marketed in Sicily (Italy) using both traditional methods and Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS). MALDI-TOF MS is considered a promising rapid (less than 1 hour) identification method for food borne pathogens bacteria. One hundred chicken and turkey meat preparations (no. 68 hamburgers, no. 21 raw sausages, no. 4 meatballs and no. 7 meat rolls) were taken from different butcher’s shops and large scale retailers and submitted to detection/enumeration of Campylobacter spp. according to EN ISO 10272-1:2006 and EN ISO 10272-2:2006. Campylobacter spp. was detected with general low counts in 44 samples (44%), of which 30 from large scale retailers and 14 from butcher’s shops. Chicken meats were significantly more contaminated than turkey meats. Among the preparations, Campylobacter spp. was found in 85.71% of meat rolls, 50% of meatballs, 44.12% of hamburgers and 28.57% of raw sausages. A total of 100 strains, 2-3 from each positive samples, were isolated for the identification by phenotypic, biomolecular and MALDI-TOF MS methods. C. jejuni was the predominant strains (63%), followed by C. coli (33%) and C. lari (4%). MALDI-TOF MS correctly identified 98% of the strains at the species level, only 1% of the tested strains were not identified. In the last 1%, a mixture of two different species was mixed in the same sample and MALDI-TOF MS correctly identified at least one of the strains. Considering the importance of rapid identification of pathogens in the food matrix, this method is highly recommended for the identification of suspected colonies of Campylobacteria.

Keywords: campylobacter spp., Food Microbiology, matrix-assisted laser desorption ionization-time of flight mass spectrometry, rapid microbial identification

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Authors: Ruchi B. Semwal, Deepak K. Semwal, Thobile A. N. Nkosi, Alvaro M. Viljoen

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The use of Lawsonia inermis L. (Lythraeae), commonly known as henna, has many medicinal benefits and is used as a remedy for the treatment of diarrhoea, cancer, inflammation, headache, jaundice and skin diseases in folk medicine. Although widely used for hair dyeing and temporary tattooing, henna body art has popularized over the last 15 years and changed from being a traditional bridal and festival adornment to an exotic fashion accessory. The naphthoquinone, lawsone, is one of the main constituents of the plant and responsible for its dyeing property. Henna leaves typically contain 1.8–1.9% lawsone, which is used as a marker compound for the quality control of henna products. Adulteration of henna with various toxic chemicals such as p-phenylenediamine, p-methylaminophenol, p-aminobenzene and p-toluenodiamine to produce a variety of colours, is very common and has resulted in serious health problems, including allergic reactions. This study aims to assess the quality of henna products collected from different parts of the world by determining the lawsone content, as well as the concentrations of any adulterants present. Ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to determine the lawsone concentrations in 172 henna products. Separation of the chemical constituents was achieved on an Acquity UPLC BEH C18 column using gradient elution (0.1% formic acid and acetonitrile). The results from UPLC-MS revealed that of 172 henna products, 11 contained 1.0-1.8% lawsone, 110 contained 0.1-0.9% lawsone, whereas 51 samples did not contain detectable levels of lawsone. High performance thin layer chromatography was investigated as a cheaper, more rapid technique for the quality control of henna in relation to the lawsone content. The samples were applied using an automatic TLC Sampler 4 (CAMAG) to pre-coated silica plates, which were subsequently developed with acetic acid, acetone and toluene (0.5: 1.0: 8.5 v/v). A Reprostar 3 digital system allowed the images to be captured. The results obtained corresponded to those from UPLC-MS analysis. Vibrational spectroscopy analysis (MIR or NIR) of the powdered henna, followed by chemometric modelling of the data, indicates that this technique shows promise as an alternative quality control method. Principal component analysis (PCA) was used to investigate the data by observing clustering and identifying outliers. Partial least squares (PLS) multivariate calibration models were constructed for the quantification of lawsone. In conclusion, only a few of the samples analysed contain lawsone in high concentrations, indicating that they are of poor quality. Currently, the presence of adulterants that may have been added to enhance the dyeing properties of the products, is being investigated.

Keywords: Lawsonia inermis, paraphenylenediamine, temporary tattooing, lawsone

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

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Authors: Vijay Sodhi, Charanjit Singh, Neelam Sodhi, Puneet P. S. Cheema, Reena Sharma, Mithilesh K. Jha

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The management and secure disposal of the biosludge generated from widely commercialized conventional activated sludge (CAS) treatments become a potential environmental issue. Thus, a sustainable technological upgradation to the CAS for sludge yield minimization has recently been gained serious attention of the scientific community. A number of recently reported studies effectively addressed the remedial technological advancements that in monopoly limited to the municipal wastewater. Moreover, the critical review of the literature signifies side-stream sludge minimization as a complex task to maintain. In this work, therefore, a hybrid moving bed biofilm reactor (MBBR) configuration (named as AMOMOX process) for in-situ minimization of the excess biosludge generated from high organic strength tannery wastewater has been demonstrated. The AMOMOX collectively stands for anoxic MBBR (as AM), aerobic MBBR (OM) and an oxic CAS (OX). The AMOMOX configuration involved a combined arrangement of an anoxic MBBR and oxic MBBR coupled with the aerobic CAS. The AMOMOX system was run in parallel with an identical CAS reactor. Both system configurations were fed with same influent to judge the real-time operational changes. For the AMOMOX process, the strict maintenance of operational strategies resulted about 95% removal of NH4-N and SCOD from tannery wastewater. Here, the nourishment of filamentous microbiota and purposeful promotion of cell-lysis effectively sustained sludge yield (Yobs) lowering upto 0.51 kgVSS/kgCOD. As a result, the volatile sludge scarcity apparent in the AMOMOX system succeeded upto 47% reduction of the excess biosludge. The corroborated was further supported by FE-SEM imaging and thermogravimetric analysis. However, the detection of microbial strains habitat underlying extended SRT (23-26 days) of the AMOMOX system would be the matter of further research.

Keywords: tannery wastewater, moving bed biofilm reactor, sludhe yield, sludge minimization, solids retention time

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Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Gehan Hussein, Hala Agha, Rasha Abdelraof, Marina George, Antoine Fakhri

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Background: β-Thalassemia major (TM) and sickle cell disease (SCD) are inherited hemoglobin disorders resulting in chronic hemolytic anemia. Cardiovascular involvement is an important cause of morbidity and mortality in these groups of patients. The narrow border is between overt myocardial dysfunction and clinically silent left ventricular (LV) and / or right ventricular (RV) dysfunction in those patients. 3 D Speckle tracking echocardiography (3D STE) is a novel method for the detection of subclinical myocardial involvement. We aimed to study myocardial affection in SCD and TM using 3D STE, comparing it with conventional echocardiography, correlate it with serum ferritin level and lactate dehydrogenase (LDH). Methodology: Thirty SCD and thirty β TM patients, age range 4-18 years, were compared to 30 healthy age and sex matched control group. Cases were subjected to clinical examination, laboratory measurement of hemoglobin level, serum ferritin, and LDH. Transthoracic color Doppler echocardiography, 3D STE, tissue Doppler echocardiography, and aortic speckle tracking were performed. Results: significant reduction in global longitudinal strain (GLS), global circumferential strain (GCS), and global area strain (GAS) in SCD and TM than control (P value <0.001) there was significantly lower aortic speckle tracking in patients with TM and SCD than control (P value< 0.001). LDH was significantly higher in SCD than both TM and control and it correlated significantly positive mitral inflow E, (p value:0.022 and 0.072. r: 0.416 and -0.333 respectively) lateral E/E’ (p value.<0.001and 0.818. r. 0.618 and -0. 044.respectively) and septal E/E’ (p value 0.007 and 0.753& r value 0.485 and -0.060 respectively) in SCD but not TM and significant negative correlation between LDH and aortic root speckle tracking (value 0.681& r. -0.078.). The potential diagnostic accuracy of LDH in predicting vascular dysfunction as represented by aortic root GCS with a sensitivity 74% and aortic root GCS was predictive of LV dysfunction in SCD patients with sensitivity 100% Conclusion: 3D STE LV and RV systolic dysfunction in spite of their normal values by conventional echocardiography. SCD showed significantly lower right ventricular dysfunction and aortic root GCS than TM and control. LDH can be used to screen patients for cardiac dysfunction in SCD, not in TM

Keywords: thalassemia major, sickle cell disease, 3d speckle tracking echocardiography, LDH

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