Search results for: signal classification

Authors: Austin Jiang, Richard M. Salmon, Nicholas W. Morrell, Wei Li

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BMP10 is highly expressed in the developing heart and plays essential roles in cardiogenesis. BMP10 deletion in mice results in embryonic lethality due to impaired cardiac development. In adults, BMP10 expression is restricted to the right atrium, though ventricular hypertrophy is accompanied by increased BMP10 expression in a rat hypertension model. However, reports of BMP10 activity in the circulation are inconclusive. In particular it is not known whether in vivo secreted BMP10 is active or whether additional factors are required to achieve its bioactivity. It has been shown that high-affinity binding of the BMP10 prodomain to the mature ligand inhibits BMP10 signaling activity in C2C12 cells, and it was proposed that prodomain-bound BMP10 (pBMP10) complex is latent. In this study, we demonstrated that the BMP10 prodomain did not inhibit BMP10 signaling activity in multiple endothelial cells, and that recombinant human pBMP10 complex, expressed in mammalian cells and purified under native conditions, was fully active. In addition, both BMP10 in human plasma and BMP10 secreted from the mouse right atrium were fully active. Finally, we confirmed that active BMP10 secreted from mouse right atrium was in the prodomain-bound form. Our data suggest that circulating BMP10 in adults is fully active and that the reported vascular quiescence function of BMP10 in vivo is due to the direct activity of pBMP10 and does not require an additional activation step. Moreover, being an active ligand, recombinant pBMP10 may have therapeutic potential as an endothelial-selective BMP ligand, in conditions characterized by loss of BMP9/10 signaling.

Keywords: bone morphogenetic protein 10 (BMP10), endothelial cell, signal transduction, transforming growth factor beta (TGF-B)

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Authors: Sara Alhabli, Eman Elashiry, Osama Felemban, Abdullah Almushayt, Faisal Dardeer, Ahmed Mohammad, Fajr Orri, Nada Bamashmous

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Background: In December of 2019, the coronavirus (SARS-CoV-2) first appeared and quickly spread to become a worldwide pandemic. This study aimed to evaluate the prevalence and types of pediatric dental emergencies during the COVID-19 lockdown in Jeddah, Saudi Arabia, at the University Dental Hospital (UDH) of King Abdulaziz University (KAU) and identified the management provided for these dental emergency visits. Materials and Methods: Data collection was done retrospectively from electronic dental records for children aged 0-18 that attended the UDH emergency clinic during the period from March 1st, 2020, to September 30th, 2020. An electronic form formulated specifically for this study was used to collect the required data from electronic patient records, including demographic data, emergency classification, management, and referrals. Results: A total of 3146 patients were seen at the emergency clinics during this period, of which 661 were children (21%). Types of emergency conditions included 0.8% emergency cases, 34% urgent, and 65.2% non-urgent conditions. Severe dental pain (73.1%) and abscesses (20%) were the most common urgent dental conditions. Most non-urgent conditions presented for initial or periodic visits, recalls, or routine radiographs (74%). Treatments rarely involved restorations, with 8% among urgent conditions and 5.4% among non-urgent conditions. Antibiotics were only prescribed to 6.9% of urgent conditions. Conclusions: The largest group of children presenting at the emergency dental clinics were found to be children with non-urgent conditions. Tele dentistry can be a solution to avoid large numbers of non-urgent patients presenting to emergency clinics. Additionally, dental care for non-urgent conditions during the pandemic should focus more on procedures with less aerosol generation.

Keywords: COVID-19 pandemic, dental emergencies, oral health, pediatric dentistry, children

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Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

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In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

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Authors: Okechukwu B. C. Nwankwo

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The surge of social protests sweeping through the globe is a contemporary phenomenon. Yet the phenomenon in itself is not new. Thus, various scholars have over the years developed conceptual frameworks for evaluating it. Adopting and adapting some of these frameworks this paper begins from a purely theoretical perspective exploring the concept and content of social protest within the specific context of Nigeria. It proceeds to build a typology of the phenomenon in terms of form, actors, origin, character, organisation, goal, dynamics, outcome and a whole lot of other variables that are context relevant for evaluating it in an operationally useful manner. The centrality of the context in which protest evolves is demonstrated. Adopting Easton’s systems theory, the paper builds on the assumption that protests emerge whenever and wherever political institutions and structures prove unable or unwilling to transform inputs in form of basic demands into outputs in form of responsive policies. It argues that protests in Nigeria are simply the crystallisation of opposition in the streets. Protests are thus extra-institutional politics. This is usually the case, as elsewhere, where there is no functional institutionalised opposition. Noting that protest, disruptive or otherwise, is an influence strategy, it argues that every single protest is a new opportunity for reform, for reorganisation of state capacities, for modifying rights and obligation of citizens and government to each other. Each reform outcome is, however, only a temporal antecedent. Its extensity gives signal for the next similar protest event. Through providing evidence on how protests in Nigeria create opportunity for reform, for more accountable, more effective governance, the paper shows the positive impact of protests and its importance even in the consolidation effort for the nation’s nascent democracy. Data on protest events will be based on media reports, especially print media.

Keywords: democracy, dialectics, social protest, reform

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Authors: Riccardo Patriarca, Giulio Di Gravio, Francesco Costantino, Massimo Tronci

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An accurate inventory management policy acquires a crucial role in the several high-availability sectors. In these sectors, due to the high-cost of spares and backorders, an (S-1, S) replenishment policy is necessary for high-availability items. The policy enables the shipment of a substitute efficient item anytime the inventory size decreases by one. This policy can be modelled following the Multi-Echelon Technique for Recoverable Item Control (METRIC). The METRIC is a system-based technique that allows defining the optimum stock level in a multi-echelon network, adopting measures in line with the decision-maker’s perspective. The METRIC defines an availability-cost function with inventory costs and required service levels, using as inputs data about the demand trend, the supplying and maintenance characteristics of the network and the budget/availability constraints. The traditional METRIC relies on the hypothesis that a Poisson distribution well represents the demand distribution in case of items with a low failure rate. However, in this research, we will explore the effects of using a Poisson distribution to model the demand of low failure rate items characterized by an irregular demand trend. This characteristic of a demand is not included in the traditional METRIC formulation leading to the need of revising its traditional formulation. Using the CV (Coefficient of Variation) and ADI (Average inter-Demand Interval) classification, we will define the inherent flaws of Poisson-based METRIC for irregular demand items, defining an innovative ad hoc distribution which can better fit the irregular demands. This distribution will allow defining proper stock levels to reduce stocking and backorder costs due to the high irregularities in the demand trend. A case study in the aviation domain will clarify the benefits of this innovative METRIC approach.

Keywords: METRIC, inventory management, irregular demand, spare parts

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

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Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Mohammad H. Yarmohammadian, Mehdi Nasr Isfahani, Elham Anbari

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Introduction: The awareness of using chemical, biological, and nuclear agents in everyday industrial and non-industrial incidents has increased recently; release of these materials can be accidental or intentional. Since hospitals are the forefronts of confronting Chemical, Biological, Radiological and Nuclear( CBRN) incidents, the goal of the present research was to provide a generic protocol for CBRN incidents through a comparative review of CBRN protocols and guidelines of different countries and reviewing various books, handbooks and papers. Method: The integrative approach or research synthesis was adopted in this study. First a simple narrative review of programs, books, handbooks, and papers about response to CBRN incidents in different countries was carried out. Then the most important and functional information was discussed in the form of a generic protocol in focus group sessions and subsequently confirmed. Results: Findings indicated that most of the countries had various protocols, guidelines, and handbooks for hazardous materials or CBRN incidents. The final outcome of the research synthesis was a 50 page generic protocol whose main topics included introduction, definition and classification of CBRN agents, four major phases of incident and disaster management cycle, hospital response management plan, equipment, and recommended supplies and antidotes for decontamination (radiological/nuclear, chemical, biological); each of these also had subtopics. Conclusion: In the majority of international protocols, guidelines, handbooks and also international and Iranian books and papers, there is an emphasis on the importance of incident command system, determining the safety degree of decontamination zones, maps of decontamination zones, decontamination process, triage classifications, personal protective equipment, and supplies and antidotes for decontamination; these are the least requirements for such incidents and also consistent with the provided generic protocol.

Keywords: hospital, CBRN, decontamination, generic protocol, CBRN Incidents

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Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

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Authors: Xiaoyang Zhao, Kaiying Wang

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The choice of stocking density in poultry farming is a potential way for determining welfare level of poultry. However, it is difficult to measure stocking densities in poultry farming because of a lot of variables such as species, age and weight, feeding way, house structure and geographical location in different broiler houses. A method was proposed in this paper to measure the differences of young broilers reared under different stocking densities by sound analysis. Vocalisations of broilers were recorded and analysed under different stocking densities to identify the relationship between sounds and stocking densities. Recordings were made continuously for three-week-old chickens in order to evaluate the variation of sounds emitted by the animals at the beginning. The experimental trial was carried out in an indoor reared broiler farm; the audio recording procedures lasted for 5 days. Broilers were divided into 5 groups, stocking density treatments were 8/m², 10/m², 12/m² (96birds/pen), 14/m² and 16/m², all conditions including ventilation and feed conditions were kept same except from stocking densities in every group. The recordings and analysis of sounds of chickens were made noninvasively. Sound recordings were manually analysed and labelled using sound analysis software: GoldWave Digital Audio Editor. After sound acquisition process, the Mel Frequency Cepstrum Coefficients (MFCC) was extracted from sound data, and the Support Vector Machine (SVM) was used as an early detector and classifier. This preliminary study, conducted in an indoor reared broiler farm shows that this method can be used to classify sounds of chickens under different densities economically (only a cheap microphone and recorder can be used), the classification accuracy is 85.7%. This method can predict the optimum stocking density of broilers with the complement of animal welfare indicators, animal productive indicators and so on.

Keywords: broiler, stocking density, poultry farming, sound monitoring, Mel Frequency Cepstrum Coefficients (MFCC), Support Vector Machine (SVM)

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Authors: Hediyeh Talebi, Shokoofeh Ghiam, Changiz Eslahchi

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Traditionally, Alzheimer’s disease research has focused on genes with significant fold changes, potentially neglecting subtle but biologically important alterations. Our study introduces an integrative approach that highlights genes crucial to underlying biological processes, regardless of their fold change magnitude. Alzheimer's Single-cell RNA-seq data related to the peripheral blood mononuclear cells (PBMC) was extracted from the Gene Expression Omnibus (GEO). After quality control, normalization, scaling, batch effect correction, and clustering, differentially expressed genes (DEGs) were identified with adjusted p-values less than 0.05. These DEGs were categorized based on cell-type, resulting in four datasets, each corresponding to a distinct cell type. To distinguish between cells from healthy individuals and those with Alzheimer's, an adversarial autoencoder with a classifier was employed. This allowed for the separation of healthy and diseased samples. To identify the most influential genes in this classification, the weight matrices in the network, which includes the encoder and classifier components, were multiplied, and focused on the top 20 genes. The analysis revealed that while some of these genes exhibit a high fold change, others do not. These genes, which may be overlooked by previous methods due to their low fold change, were shown to be significant in our study. The findings highlight the critical role of genes with subtle alterations in diagnosing Alzheimer's disease, a facet frequently overlooked by conventional methods. These genes demonstrate remarkable discriminatory power, underscoring the need to integrate biological relevance with statistical measures in gene prioritization. This integrative approach enhances our understanding of the molecular mechanisms in Alzheimer’s disease and provides a promising direction for identifying potential therapeutic targets.

Keywords: alzheimer's disease, single-cell RNA-seq, neural networks, blood biomarkers

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Authors: Abu Salim Mustafa

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Brucellosis is a zoonotic disease endemic in Kuwait. Human brucellosis can be caused by several Brucella species with Brucella melitensis causing the most severe and Brucella abortus the least severe disease. Furthermore, relapses are common after successful chemotherapy of patients. The classical biochemical methods of culture and serology for identification of Brucellae provide information about the species and serotypes only. However, to differentiate between relapse and reinfection/epidemiological investigations, the identification of genotypes using molecular methods is essential. In this study, four molecular methods [16S rRNA gene sequencing, real-time PCR, enterobacterial repetitive intergenic consensus (ERIC)-PCR and multilocus variable-number tandem-repeat analysis (MLVA)-16] were evaluated for the identification and typing of 75 strains of Brucella isolated in Kuwait. The 16S rRNA gene sequencing suggested that all the strains were B. melitensis and real-time PCR confirmed their species identity as B. melitensis. The ERIC-PCR band profiles produced a dendrogram of 75 branches suggesting each strain to be of a unique type. The cluster classification, based on ~ 80% similarity, divided all the ERIC genotypes into two clusters, A and B. Cluster A consisted of 9 ERIC genotypes (A1-A9) corresponding to 9 individual strains. Cluster B comprised of 13 ERIC genotypes (B1-B13) with B5 forming the largest cluster of 51 strains. MLVA-16 identified all isolates as B. melitensis and divided them into 71 MLVA-types. The cluster analysis of MLVA-16-types suggested that most of the strains in Kuwait originated from the East Mediterranean Region, a few from the African group and one new genotype closely matched with the West Mediterranean region. In conclusion, this work demonstrates that B. melitensis, the most pathogenic species of Brucella, is prevalent in Kuwait. Furthermore, MLVA-16 is the best molecular method, which can identify the Brucella species and genotypes as well as determine their origin in the global context. Supported by Kuwait University Research Sector grants MI04/15 and SRUL02/13.

Keywords: Brucella, ERIC-PCR, MLVA-16, RT-PCR, 16S rRNA gene sequencing

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Authors: H. Dakhlaoui, D. Ruelland, Y. Tramblay, Z. Bargaoui

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To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that are able to be fairly reliable under changing climate conditions. This study aims at assessing the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in Northern Tunisia under long-term climate variability. Their robustness was evaluated according to a differential split sample test based on a climate classification of the observation period regarding simultaneously precipitation and temperature conditions. The studied catchments are situated in a region where climate change is likely to have significant impacts on runoff and they already suffer from scarcity of water resources. They cover the main hydrographical basins of Northern Tunisia (High Medjerda, Zouaraâ, Ichkeul and Cap bon), which produce the majority of surface water resources in Tunisia. The streamflow regime of the basins can be considered as natural since these basins are located upstream from storage-dams and in areas where withdrawals are negligible. A 30-year common period (1970‒2000) was considered to capture a large spread of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while the evaluation of model transferability is performed according to the Nash-Suttfliff efficiency criterion and volume error. The three hydrological models were shown to have similar behaviour under climate variability. Models prove a better ability to simulate the runoff pattern when transferred toward wetter periods compared to the case when transferred to drier periods. The limits of transferability are beyond -20% of precipitation and +1.5 °C of temperature in comparison with the calibration period. The deterioration of model robustness could in part be explained by the climate dependency of some parameters.

Keywords: rainfall-runoff modelling, hydro-climate variability, model robustness, uncertainty, Tunisia

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Authors: Victor Ananth Paramananth, Rashid Muniginin, Mahaya Abd Rahman, Siti Afifah Ismail

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Safety issues, scene protection, and appropriate evidence collection must be handled in any bio crime scene. There will be a scene or multi-scene to be cordoned for investigation in any bio-incident or bio crime event. Evidence collection is critical in determining the type of microbial or toxin, its lethality, and its source. As a consequence, from the start of the investigation, a proper sampling method is required. The most significant challenges for the crime scene officer would be deciding where to obtain samples, the best sampling method, and the sample sizes needed. Since there could be evidence in liquid, viscous, or powder shape at a crime scene, crime scene officers have difficulty determining which tools to use for sampling. To maximize sample collection, the appropriate tools for sampling methods are necessary. This study aims to assist the crime scene officer in collecting liquid, viscous, and powder biological samples in sufficient quantity while preserving sample quality. Observational tests on sample collection using liquid, viscous, and powder samples for adequate quantity and sample quality were performed using UV light in this research. The density of the light emission varies upon the method of collection and sample types. The best tools for collecting sufficient amounts of liquid, viscous, and powdered samples can be identified by observing UV light. Instead of active microorganisms, the invisible powder is used to assess sufficient sample collection during a crime scene investigation using various collection tools. The liquid, powdered and viscous samples collected using different tools were analyzed using Fourier transform infrared - attenuate total reflection (FTIR-ATR). FTIR spectroscopy is commonly used for rapid discrimination, classification, and identification of intact microbial cells. The liquid, viscous and powdered samples collected using various tools have been successfully observed using UV light. Furthermore, FTIR-ATR analysis showed that collected samples are sufficient in quantity while preserving their quality.

Keywords: biological sample, crime scene, collection tool, UV light, forensic

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Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

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Authors: Nureni Amoo, Sunday Aroge, Oluranti Akintola, Hakeem Olujide, Ibrahim Alabi

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This study investigated the optimum landfill site in Osogbo so as to identify suitable solid waste dumpsite for proper waste management in the capital city. Despite an increase in alternative techniques for disposing of waste, landfilling remains the primary means of waste disposal. These changes in attitudes in many parts of the world have been supported by changes in laws and policies regarding the environment and waste disposal. Selecting the most suitable site for landfill can avoid any ecological and socio-economic effects. The increase in industrial and economic development, along with the increase of population growth in Osogbo town, generates a tremendous amount of solid waste within the region. Factors such as the scarcity of land, the lifespan of the landfill, and environmental considerations warrant that the scientific and fundamental studies are carried out in determining the suitability of a landfill site. The analysis of spatial data and consideration of regulations and accepted criteria are part of the important elements in the site selection. This paper presents a multi-criteria decision-making method using geographic information system (GIS) with the integration of the fuzzy logic multi-criteria decision making (FMCDM) technique for landfill suitability site evaluation. By using the fuzzy logic method (classification of suitable areas in the range of 0 to 1 scale), the superposing of the information layers related to drainage, soil, land use/land cover, slope, land use, and geology maps were performed in the study. Based on the result obtained in this study, five (5) potential sites are suitable for the construction of a landfill are proposed, two of which belong to the most suitable zone, and the existing waste disposal site belonged to the unsuitable zone.

Keywords: fuzzy logic multi-criteria decision making, geographic information system, landfill, suitable site, waste disposal

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau, Dong Hun Kwak, Nicolae-Alexandru Colceriu

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Background: Stress management (SM) is a topic of great academic interest and equally a task to accomplish. In addition, it is recognized the beneficial role of unconventional therapies (UCT) in stress modulation. Aims: The aim was to evaluate medical (MS) versus non-medical students’ (NMS) opinions about academic stress management (ASM) using UCT. Methods: MS (n=103, third year males and females) and NMS (n=112, males and females, from humanities faculties, different years of study), out of their academic program, voluntarily answered to a questionnaire concerning: a) Classification of the four most important academic stress factors; b) The extent to which their daily life influences academic stress; c) The most important SM methods they know; d) Which of these methods they are applying; e) the UCT they know or about which they have heard; f) Which of these they know to have stress modulation effects; g) Which of these UCT, participants are using or would like to use for modulating stress; and if participants use UTC for their own choose or following a specialist consultation in those therapies (SCT); h) If they heard about the following UCT and what opinion they have (using visual analogue scale) about their use (following CST) for the ASM: Phytotherapy (PT), apitherapy (AT), homeopathy (H), ayurvedic medicine (AM), traditional Chinese medicine (TCM), music therapy (MT), color therapy (CT), forest therapy (FT). Results: Among the four most important academic stress factors, for MS more than for NMS, are: busy schedule, large amount of information taught; high level of performance required, reduced time for relaxing. The most important methods for SM that MS and NMS know, hierarchically are: listen to music, meeting friends, playing sport, hiking, sleep, regularly breaks, seeing positive side, faith; of which, NMS more than MS, are partially applying to themselves. UCT about which MS and less NMS have heard, are phytotherapy, apitherapy, acupuncture, reiki. Of these UTC, participants know to have stress modulation effects: some plants, bee’s products and music; they use or would like to use for ASM (the majority without SCT) certain teas, honey and music. Most of MS and only some NMS heard about PT, AT, TCM, MT and much less about H, AM, CT, TT. NMS more than MS, would use these UCT, following CST. Conclusions: 1) Academic stress is similarly reflected in MS and NMS opinions. 2) MS and NMS apply similar but very few UCT for stress modulation. 3) Information that MS and NMS have about UCT and their ASM application is reduced. 4) It is remarkable that MS and especially NMS, are open to UCT use for ASM, following an SCT.

Keywords: academic stress, stress management, stress modulation, medical students, non-medical students, unconventional therapies

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Authors: Ivan Potapov

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Background: The aim of this paper is to investigate poly code texts in the communication of youth antisocial groups. Nowadays, the notion of a text has numerous interpretations. Besides all the approaches to defining a text, we must take into account semiotic and cultural-semiotic ones. Rapidly developing IT, world globalization, and new ways of coding of information increase the role of the cultural-semiotic approach. However, the development of computer technologies leads also to changes in the text itself. Polycode texts play a more and more important role in the everyday communication of the younger generation. Therefore, the research of functional and pragmatic aspects of both verbal and non-verbal content is actually quite important. Methods and Material: For this survey, we applied the combination of four methods of text investigation: not only intention and content analysis but also semantic and syntactic analysis. Using these methods provided us with information on general text properties, the content of transmitted messages, and each communicants’ intentions. Besides, during our research, we figured out the social background; therefore, we could distinguish intertextual connections between certain types of polycode texts. As the sources of the research material, we used 20 public channels in the popular messenger Telegram and data extracted from smartphones, which belonged to arrested members of antisocial groups. Findings: This investigation let us assert that polycode texts can be characterized as highly intertextual language unit. Moreover, we could outline the classification of these texts based on communicants’ intentions. The most common types of antisocial polycode texts are a call to illegal actions and agitation. What is more, each type has its own semantic core: it depends on the sphere of communication. However, syntactic structure is universal for most of the polycode texts. Conclusion: Polycode texts play important role in online communication. The results of this investigation demonstrate that in some social groups using these texts has a destructive influence on the younger generation and obviously needs further researches.

Keywords: text, polycode text, internet linguistics, text analysis, context, semiotics, sociolinguistics

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Authors: Eman Merza, Stephen Pearson, Glen Lichtwark, Peter Malliaras

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The Achilles tendon (AT) exhibits volume changes related to fluid flow under acute load which may be linked to changes in stiffness. Fluid flow provides a mechanical signal for cellular activity and may be one mechanism that facilitates tendon adaptation. This study aimed to investigate whether isometric intervention involving a high level of load duration and intensity could maximize the immediate reduction in AT volume and stiffness compared to interventions involving a lower level of load duration and intensity. Sixteen healthy participants (12 males, 4 females; age= 24.4 ± 9.4 years; body mass= 70.9 ± 16.1 kg; height= 1.7 ± 0.1 m) performed three isometric interventions of varying levels of load duration (2 s and 8 s) and intensity (35% and 75% maximal voluntary isometric contraction) over a 3 week period. Freehand 3D ultrasound was used to measure free AT volume (at rest) and length (at 35%, 55%, and 75% of maximum plantarflexion force) pre- and post-interventions. The slope of the force-elongation curve over these force levels represented individual stiffness (N/mm). Large reductions in free AT volume and stiffness resulted in response to long-duration high-intensity loading whilst less reduction was produced with a lower load intensity. In contrast, no change in free AT volume and a small increase in AT stiffness occurred with lower load duration. These findings suggest that the applied load on the AT must be heavy and sustained for a long duration to maximize immediate volume reduction, which might be an acute response that enables optimal long-term tendon adaptation via mechanotransduction pathways.

Keywords: Achilles tendon, volume, stiffness, free tendon, 3d ultrasound

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Authors: AbdelRahman A. Faragalla, Mohamed H. Alqhtani, Mohamed M. M.Ahmed

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Saudi Arabia has currently been beset by a barrage of bizarre assemblages of subterranean termite fauna, inflicting heavy catastrophic havocs on human valued properties in various homes, storage facilities, warehouses, agricultural and horticultural crops including okra, sweet pepper, tomatoes, sorghum, date palm trees, citruses and many forest domains and green lush desert oases. The most pressing urgent priority is to use modern technologies to alleviate the painstaking obstacle of taxonomic identification of these injurious noxious pests that might lead to effective pest control in both infested agricultural commodities and field crops. Our study has indicated the use of DNA fingerprinting technologies, in order to generate basic information of the genetic similarity between 3 predominant families containing the most destructive termite species. The methodologies included extraction and DNA isolation from members of the major families and the use of randomly selected primers and PCR amplifications with the nucleotide sequences. GC content and annealing temperatures for all primers, PCR amplifications and agarose gel electrophoresis were also conducted in addition to the scoring and analysis of Random Amplification Polymorphic DNA-PCR (RAPDs). A phylogenetic analysis for different species using statistical computer program on the basis of RAPD-DNA results, represented as a dendrogram based on the average of band sharing ratio between different species. Our study aims to shed more light on this intriguing subject, which may lead to an expedited display of the kinship and relatedness of species in an ambitious undertaking to arrive at correct taxonomic classification of termite species, discover sibling species, so that a logistic rational pest management strategy could be delineated.

Keywords: DNA fingerprinting, Western Saudi Arabia, DNA primers, RAPD

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Authors: Hyun Lim, Dong Sook Min, Han Eul Yun, Kil Tae Kim, Ya Nan Sun, Young Ho Kim, Hyun Pyo Kim

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Matrix metalloproteinase (MMP)-13 has an important role for degrading cartilage materials under inflammatory conditions such as arthritis. Since the 70% ethanol extract of Acanthopanax koreanum inhibited MMP-13 expression in IL-1β-treated human chondrocyte cell line, SW1353, two major constituents including acanthoic acid and impressic acid were initially isolated from the same plant materials and their MMP-13 down-regulating capacity was examined. In IL-1β-treated SW1353 cells, acanthoic acid and impressic acid significantly and concentration-dependently inhibited MMP-13 expression at 10 – 100 μM and 0.5 – 10 μM, respectively. The potent one, impressic acid, was found to inhibit MMP-13 expression by blocking the phosphorylation of signal transducer and activator of transcription-1/-2 (STAT-1/-2) and activation of c-Jun and c-Fos among cellular signaling pathway involved, but did not affect the activation of mitogen-activated protein kinases (MAPKs) and nuclear transcription factor-κB (NF-κB). Further, impressic acid was also found to inhibit the expression of MMP-13 mRNA (47.7% inhibition at 10 μM), the glycosaminoglycan release (42.2% reduction at 10 μM) and proteoglycan loss in IL-1-treated rabbit cartilage explants culture. For a further study, 21 impressic acid derivatives were isolated from the same plant materials and their suppressive activities against MMP-13 expression were examined. Among the derivatives, 3α-hydroxy-lup-20(29)-en-23-oxo,28-oic acid, (20R)-3α-hydroxy-29-dimethoxylupan-23,28-dioic acid, acankoreoside F and acantrifoside A clearly down-regulated MMP-13 expression, but impressic acid being most potent. All these results suggest that impressic acid, 3α-hydroxy-lup-20(29)-en-23-oxo,28-oic acid, (20R)-3α-hydroxy-29-dimethoxylupan-23,28-dioic acid, acankoreoside F, acantrifoside A and A. koreanum may have a potential for therapeutic agents to prevent cartilage degradation possibly by inhibiting matrix protein degradation.

Keywords: acanthoic acid, Acanthopanax koreanum, cartilage, impressic acid, matrix metalloproteinase

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Authors: Khatuna Buskivadze

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The aim of the present study is to investigate the sociolinguistic and classroom functions and frequency of Teacher’s Code Switching (CS) in the Content and Language Integrated (CLIL) Lesson. Nowadays, Georgian society struggles to become the part of the European world, the English language itself plays a role in forming new generations with European values. Based on our research conducted in 2019, out of all 114 private schools in Tbilisi, full- programs of CLIL are taught in 7 schools, while only some subjects using CLIL are conducted in 3 schools. The goal of the former research was to define the features of Content and Language Integrated learning (CLIL) methodology within the process of teaching English on the Example of Georgian private high schools. Taking the Georgian reality and cultural features into account, the modified version of the questionnaire, based on the classification of using CS in ESL Classroom proposed By Ferguson (2009) was used. The qualitative research revealed students’ and teacher’s attitudes towards teacher’s code-switching in CLIL lesson. Both qualitative and quantitative research were conducted: the observations of the teacher’s lessons (Recording of T’s online lessons), interview and the questionnaire among Math’s T’s 20 high school students. We came to the several conclusions, some of them are given here: Math’s teacher’s CS behavior mostly serves (1) the conversational function of interjection; (2) the classroom functions of introducing unfamiliar materials and topics, explaining difficult concepts, maintaining classroom discipline and the structure of the lesson; The teacher and 13 students have negative attitudes towards using only Georgian in teaching Math. The higher level of English is the more negative is attitude towards using Georgian in the classroom. Although all the students were Georgian, their competence in English is higher than in Georgian, therefore they consider English as an inseparable part of their identities. The overall results of the case study of teaching Math (Educational discourse) in one of the private schools in Tbilisi will be presented at the conference.

Keywords: attitudes, bilingualism, code-switching, CLIL, conversation analysis, interactional sociolinguistics.

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Authors: Ticijana Prijon, Branko Ermenc

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Background: Blunt aortic trauma (BAT) includes various morphological changes that occur during deceleration, acceleration and/or body compression in traffic accidents. The various forms of BAT, from limited laceration of the intima to complete transection of the aorta, depends on the force acting on the vessel wall and the tolerance of the aorta to injury. The force depends on the change in velocity, the dynamics of the accident and of the seating position in the car. Tolerance to aortic injury depends on the anatomy, histological structure and pathomorphological alterations due to aging or disease of the aortic wall.An overview of the literature and medical documentation reveals that different terms are used to describe certain forms of BAT, which can lead to misinterpretation of findings or diagnoses. We therefore, propose a classification that would enable uniform systematic screening of all forms of BAT. We have classified BAT into three morphologycal types: TYPE I (intramural), TYPE II (transmural) and TYPE III (multiple) aortic ruptures with appropriate subtypes. Methods: All car accident casualties examined at the Institute of Forensic Medicine from 2001 to 2009 were included in this retrospective study. Autopsy reports were used to determine the occurrence of each morphological type of BAT in deceased drivers, front seat passengers and other passengers in cars and to define the morphology of BAT in relation to the accident dynamics and the age of the fatalities. Results: A total of 391 fatalities in car accidents were included in the study. TYPE I, TYPE II and TYPE III BAT were observed in 10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in drivers, front seat and other passengers was 36,7%, 43,1% and 28,6%, respectively. In frontal collisions, the incidence of BAT was 32,7%, in lateral collisions 54,2%, and in other traffic accidents 29,3%. The average age of fatalities with BAT was 42,8 years and of those without BAT 39,1 years. Conclusion: Identification and early recognition of the risk factors of BAT following a traffic accident is crucial for successful treatment of patients with BAT. Front seat passengers over 50 years of age who have been injured in a lateral collision are the most at risk of BAT.

Keywords: aorta, blunt trauma, car accidents, morphology, risk factors

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Authors: Nijole Savickiene, Antonella Di Sotto, Gabriela Mazzanti, Rasa Starselskyte, Silvia Di Giacomo, Annabella Vitalone

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Plant lectins are non-enzymic and non-immune origin proteins that specifically recognize and bind to various sugar structures and possess the activity to agglutinate cells and/or precipitate polysaccharides and glycoconjugates. The emerging evidences showed that plant lectins contribute not only to tumour cell recognition but also to cell adhesion and localization, to signal transduction, to mitogenic cytotoxicity and apoptosis. Among chitin-binding lectins, the Urtica dioica agglutinin (UDA), which is a complex of different isoforms, has been poorly studied for its biological activity. In this context and according to the increasing interest for lectins as novel antitumor drugs, present paper aimed at evaluating the potential antimutagenic activity of a lectin-like glycoprotein-enriched fraction from aerial part of Urtica dioica L. Aim: to evaluate the potential chemopreventive properties of a protein - lectin fraction from the aerial part of Urtica dioica. Materials and methods: Protein – lectin fraction has been tested for the antimutagenic activity in bacteria (50–800 mg/plate; Ames test by the preincubation method) and for the cytotoxicity on human hepatoma HepG2 cells (0.06–2 mg/mL; 24 and 48 h incubation). Results: Protein – lectin fraction from stinging nettle was not cytotoxic on HepG2 cells up to 2 mg/mL; conversely, it exhibited a strong antimutagenic activity against the mutagen 2-aminoanthracene (2AA) in all strains tested (maximum inhibition of 56.78 and 61% in TA98, TA100, and WP2uvrA strains, respectively, at 800 mg/plate). Discussion and conclusions: Protein – lectin fraction from Urtica dioica L. possesses antimutagenic and radical scavenging properties. Being 2AA a pro-carcinogenic agent, we hypothesize that the antimutagenicity of it can be due to the inhibition of CYP450-isoenzymes, involved in the mutagen bioactivation.

Keywords: lectins, antimutagenicity, chemoprevention, Urtica dioica

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Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

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Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

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Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

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In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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Authors: Nikhil A. Gavhane, Sachin Shah, Ishant S. Mahajan, Pawan D. Bahekar

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Introduction: Millions of people are affected with dengue fever every year, which drives up healthcare expenses in many low-income countries. Organ failure and other serious symptoms may result. Another worldwide public health problem is sickle cell anaemia, which is most prevalent in Africa, the Caribbean, and Europe. Dengue epidemics have reportedly occurred in locations with a high frequency of sickle cell disease, compounding the health problems in these areas. Aims and Objectives: This study examines dengue infection in sickle cell disease-afflicted pre-schoolers. Method:This Retrospective cohort study examined paediatric patients. Young people with sickle cell disease (SCD), dengue infection, and a control group without SCD or dengue were studied. Data on demographics, SCD consequences, medical treatments, and laboratory findings were gathered to analyse the influence of SCD on dengue severity and clinical outcomes, classified as severe or non-severe by the 2009 WHO classification. Using fever or admission symptoms, the research estimated acute illness duration. Result: Table 1 compares haemoglobin genotype-based dengue episode features in SS, SC, and controls. Table 2 shows that severe dengue cases are older, have longer admission delays, and have particular symptoms. Table 3's multivariate analysis indicates SS genotype's high connection with severe dengue, multiorgan failure, and acute pulmonary problems. Table 4 relates severe dengue to greater white blood cell counts, anaemia, liver enzymes, and reduced lactate dehydrogenase. Conclusion: This study is valuable but confined to hospitalised dengue patients with sickle cell illness. Small cohorts limit comparisons. Further study is needed since findings contradict predictions.

Keywords: dengue, chills, headache, severe myalgia, vomiting, nausea, prostration

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