Search results for: real geometry of bronchial tree

Authors: Aya Effat, Ossama A. Hosny, Elkhayam M. Dorra

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Estimating costs is a crucial step in construction management and should be completed at the beginning of every project to establish the project's budget. The precision of the cost estimate plays a significant role in the success of construction projects as it allows project managers to effectively manage the project's costs. Site overhead costs constitute a significant portion of construction project budgets, necessitating accurate prediction and management. These costs are influenced by a multitude of factors, requiring a thorough examination and analysis to understand their relative importance and impact. Thus, the main aim of this research is to enhance the contractor’s ability to predict and manage site overheads by identifying and analyzing the main factors influencing the site overheads costs in the Egyptian construction industry. Through a comprehensive literature review, key factors were first identified and subsequently validated using a thorough comparative analysis of data from 55 real-life construction projects. Through this comparative analysis, the relationship between each factor and site overheads percentage as well as each site overheads subcategory and each project construction phase was identified and examined. Furthermore, correlation analysis was done to check for multicollinearity and identify factors with the highest impact. The findings of this research offer valuable insights into the key drivers of site overhead costs in the Egyptian construction industry. By understanding these factors, construction professionals can make informed decisions regarding the estimation and management of site overhead costs.

Keywords: comparative analysis, cost estimation, construction management, site overheads

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Authors: AliAkbar Hafezi, Jahanbakhsh Asadi, Majid Shahbazi, Alijan Tabarraei, Nader Mansour Samaei, Hamed Sheibak, Roghaye Gharaei

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Background: Breast cancer is the most common cancer in women. In most cancer cells, apoptosis is blocked. As for the importance of apoptosis in cancer cell death and the role of different genes in its induction or inhibition, the search for compounds that can begin the process of apoptosis in tumor cells is discussed as a new strategy in anticancer drug discovery. The aim of this study was to investigate the effect of Naringenin (NGEN) on the apoptosis in the T47D cell line of breast cancer. Materials and Methods: In this experimental study in vitro, the T47D cell line of breast cancer was selected as a sample. The cells at 24, 48, and 72 hours were treated with doses of 20, 200, and 1000 µm of Naringenin. Then, the transcription levels of the genes involved in apoptosis, including Bcl-2, Bax, Caspase 3, Caspase 8, Caspase 9, P53, PARP-1, and FAS, were assessed using Real Time-PCR. The collected data were analyzed using IBM SPSS Statistics 24.0. Results: The results showed that Naringenin at doses of 20, 200, and 1000 µm in all three times of 24, 48, and 72 hours increased the expression of Caspase 3, P53, PARP-1 and FAS and reduced the expression of Bcl-2 and increased the Bax/Bcl-2 ratio, nevertheless in none of the studied doses and times, had not a significant effect on the expression of Bax, Caspase 8 and Caspase 9. Conclusion: This study indicates that Naringenin can reduce the growth of some cancer cells and cause their deaths through increased apoptosis and decreased anti-apoptotic Bcl-2 gene expression and, resulting in the induction of apoptosis via both internal and external pathways.

Keywords: apoptosis, breast cancer, naringenin, T47D cell line

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: S. Aswath, Chinmaya Krishna Tilak, Amal Suresh, Ganesh Udupa

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There are technologies to control a humanoid robot in many ways. But the use of Electromyogram (EMG) electrodes has its own importance in setting up the control system. The EMG based control system helps to control robotic devices with more fidelity and precision. In this paper, development of an electromyogram based interface for human gesture recognition for the control of a humanoid robot is presented. To recognize control signs in the gestures, a single channel EMG sensor is positioned on the muscles of the human body. Instead of using a remote control unit, the humanoid robot is controlled by various gestures performed by the human. The EMG electrodes attached to the muscles generates an analog signal due to the effect of nerve impulses generated on moving muscles of the human being. The analog signals taken up from the muscles are supplied to a differential muscle sensor that processes the given signal to generate a signal suitable for the microcontroller to get the control over a humanoid robot. The signal from the differential muscle sensor is converted to a digital form using the ADC of the microcontroller and outputs its decision to the CM-530 humanoid robot controller through a Zigbee wireless interface. The output decision of the CM-530 processor is sent to a motor driver in order to control the servo motors in required direction for human like actions. This method for gaining control of a humanoid robot could be used for performing actions with more accuracy and ease. In addition, a study has been conducted to investigate the controllability and ease of use of the interface and the employed gestures.

Keywords: electromyogram, gesture, muscle sensor, humanoid robot, microcontroller, Zigbee

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Authors: Pukhtoon Yar

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Peshawar City is experiencing a rapid spatial urban growth primarily as a result of high rate of urbanization along with economic development. This paper was designed to understand the impacts of urbanization on agriculture land use change by particularly focusing on land use change trajectories from the past (1991-2014). We used Landsat imageries (30 meters) for1991along with Spot images (2.5 meters) for year 2014. . The ground truthing of the satellite data was performed by collecting information from Peshawar Development Authority, revenue department, real estate agents and interviews with the officials of city administration. The temporal satellite images were processed by applying supervised maximum likelihood classification technique in ArcGIS 9.3. The procedure resulted into five main classes of land use i.e. built-up area, farmland, barren land, cultivable-wasteland and water bodies. The analysis revealed that, in Peshawar City the built-up environment has been doubled from 8.1 percent in 1991 to over 18.2 percent in 2014 by predominantly encroaching land producing food. Furthermore, the CA-Markov Model predicted that the area under impervious surfaces would continue to flourish during the next three decades. This rapid increase in built-up area is accredited to the lack of proper land use planning and management, which has caused chaotic urban sprawl with detrimental social and environmental consequences.

Keywords: Urban Expansion, Land use, GIS, Remote Sensing, Markov Model, Peshawar City

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Authors: Shalini Menon, K. Girish Kumar

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Norepinephrine (NE) is one of the naturally occurring catecholamines which act both as a neurotransmitter and a hormone. Catecholamine levels are used for the diagnosis and regulation of phaeochromocytoma, a neuroendocrine tumor of the adrenal medulla. The development of simple, rapid and cost-effective sensors for NE still remains a great challenge. Herein, a dual-channel sensor has been developed for the determination of NE. A mixture of AgNO₃, NaOH, NH₃.H₂O and cetrimonium bromide in appropriate concentrations was taken as the working solution. To the thoroughly vortexed mixture, an appropriate volume of NE solution was added. After a particular time, the fluorescence and absorbance were measured. Fluorescence measurements were made by exciting at a wavelength of 400 nm. A dual-channel optical sensor has been developed for the colorimetric as well as the fluorimetric determination of NE. Metal enhanced fluorescence property of nanoparticles forms the basis of the fluorimetric detection of this assay, whereas the appearance of brown color in the presence of NE leads to colorimetric detection. Wide linear ranges and sub-micromolar detection limits were obtained using both the techniques. Moreover, the colorimetric approach was applied for the determination of NE in synthetic blood serum and the results obtained were compared with the classic high-performance liquid chromatography (HPLC) method. Recoveries between 97% and 104% were obtained using the proposed method. Based on five replicate measurements, relative standard deviation (RSD) for NE determination in the examined synthetic blood serum was found to be 2.3%. This indicates the reliability of the proposed sensor for real sample analysis.

Keywords: norepinephrine, colorimetry, fluorescence, silver nanoparticles

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Authors: A. Shoiynbek, K. Kozhakhmet, P. Menezes, D. Kuanyshbay, D. Bayazitov

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Speech emotion recognition has received increasing research interest all through current years. There was used emotional speech that was collected under controlled conditions in most research work. Actors imitating and artificially producing emotions in front of a microphone noted those records. There are four issues related to that approach, namely, (1) emotions are not natural, and it means that machines are learning to recognize fake emotions. (2) Emotions are very limited by quantity and poor in their variety of speaking. (3) There is language dependency on SER. (4) Consequently, each time when researchers want to start work with SER, they need to find a good emotional database on their language. In this paper, we propose the approach to create an automatic tool for speech emotion extraction based on facial emotion recognition and describe the sequence of actions of the proposed approach. One of the first objectives of the sequence of actions is a speech detection issue. The paper gives a detailed description of the speech detection model based on a fully connected deep neural network for Kazakh and Russian languages. Despite the high results in speech detection for Kazakh and Russian, the described process is suitable for any language. To illustrate the working capacity of the developed model, we have performed an analysis of speech detection and extraction from real tasks.

Keywords: deep neural networks, speech detection, speech emotion recognition, Mel-frequency cepstrum coefficients, collecting speech emotion corpus, collecting speech emotion dataset, Kazakh speech dataset

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Authors: Deepanwita Deka, Dhruva Kumar Jha

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Endophytes are the microbes that colonize living, internal tissues of plants without causing any immediate, overt negative effects. Endophytes are rich source of therapeutic substances like antimicrobial, anticancerous, herbicidal, insecticidal, immunomodulatory compounds. Brucea mollis, commonly known as Quinine in Assam, belonging to the family Simaroubaceae, is a shrub or small tree, recorded as endangered species in North East India by CAMP survey in 2003. It is traditionally being used as antimalarial and antimicrobial agent and has antiplasmodial, cytotoxic, anticancer, diuretic, cardiovascular effect etc. Being endangered and medicinal; this plant may host certain noble endophytes which need to be studied in depth. The aim of the present study was isolation and identification of potent endophytic fungi from Brucea mollis, an endangered medicinal plant, to protect it from extinction due to over use for medicinal purposes. Aseptically collected leaves, barks and roots samples of healthy plants were washed and cut into a total of 648 segments of about 2 cm long and 0.5 cm broad with sterile knife, comprising 216 segments each from leaves, barks and roots. These segments were surface sterilized using ethanol, mercuric chloride (HgCl2) and aqueous solution of sodium hypochlorite (NaClO). Different media viz., Czapeck-Dox-Agar (CDA, Himedia), Potato-Dextrose-Agar (PDA, Himedia), Malt Extract Agar (MEA, Himedia), Sabourad Dextrose Agar (SDA, Himedia), V8 juice agar, nutrient agar and water agar media and media amended with plant extracts were used separately for the isolation of the endophytic fungi. A total of 11 fungal species were recovered from leaf, bark and root tissues of B. mollis. The isolates were screened for antimicrobial, antioxidant and enzymatic activities using certain protocols. Cochliobolus geniculatus was identified as the most dominant species. The mycelia sterilia (creamy white) showing highest inhibitory activity against Candida albicans (MTCC 183) was induced to sporulate using modified PDA media. The isolate was identified as Geosmithia pallida. The internal transcribed spacer of rDNA was sequenced for confirmation of the taxonomic identity of the sterile mycelia (creamy white). The internal transcribed spacer r-DNA sequence was submitted to the NCBI (KU693285) for the first time from India. G. pallida and Penicillium showed highest antioxidant activity among all the isolates. The antioxidant activity of G. pallida and Penicillium didn’t show statistically significant difference (P˃0.05). G. pallida, Cochliobolus geniculatus and P. purpurogenum respectively showed highest cellulase, amylase and protease activities. Thus, endopytic fungal isolates may be used as potential natural resource of pharmaceutical importance. The endophytic fungi, Geosmithia pallida, may be used for synthesis of pharmaceutically important natural products and consequently can replace plants hitherto used for the same purpose. This study suggests that endophytes should be investigated more aggressively to better understand the endophyte biology of B. mollis.

Keywords: Antimicrobial activity, antioxidant activity, Brucea mollis, endophytic fungi, enzyme activity, Geosmithia pallida

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Ailin Agaahi, Nafise Daneshvar Hoseini, Shahnaz Tamizi, Mehrdad Sabet

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Music education has been recognized as a valuable therapeutic and educational intervention for children with Autism Spectrum Disorder (ASD). This study explores the experiences and perceptions of parents whose children with ASD have participated in music lessons at the Tehran Conservatory. The aim is to understand the impacts and barriers of this educational approach, providing insights into the real-world experiences of families integrating music into the lives of their children. Qualitative research was conducted through in-depth interviews with parents of children with ASD enrolled in the Tehran Conservatory's music program. The interviews examined parental motivations, observations of their child's progress, and evaluations of the program's effectiveness. Preliminary findings suggest that the music program positively impacts social interaction, emotional regulation, and communication. Parents highlighted the program's adaptability to meet the unique needs of children with ASD and the supportive environment fostered by specialized instructors. However, several barriers were identified, including the need for greater awareness and acceptance of music education for children with ASD and the limited availability of similar programs in the region. This research contributes valuable insights from parents and caregivers, emphasizing the importance of inclusive and effective music programs to support the needs of children with ASD and their families.

Keywords: autism spectrum disorder, music education, therapeutic intervention, parental perspectives

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Authors: Hayder H. Kareem

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Groundwater recharge is a crucial parameter for any groundwater management system. The variability of the recharge rates and the difficulty in estimating this factor in many processes by direct observation leads to the complexity of estimating the recharge value. Various methods are existing to estimate the groundwater recharge, with some limitations for each method to be able for application. This paper focuses particularly on a real study area, Al-Najaf City, Iraq. In this city, there are few groundwater aquifers, but the aquifer which is considered in this study is the closest one to the ground surface, the Dibdibba aquifer. According to the Aridity Index, which is estimated in the paper, Al-Najaf City is classified as a region located in an arid climate, and this identified that the most appropriate method to estimate the groundwater recharge is Thornthwaite's formula or Thornthwaite's method. From the calculations, the estimated average groundwater recharge over the period 1980-2014 for Al-Najaf City is 40.32 mm/year. Groundwater recharge is completely affected the groundwater table level (groundwater head). Therefore, to make sure that this value of recharge is true, the MODFLOW program has been used to apply this value through finding the relationship between the calculated and observed heads where a groundwater model for the Al-Najaf City study area has been built by MODFLOW to simulate this area for different purposes, one of these purposes is to simulate the groundwater recharge. MODFLOW results show that this value of groundwater recharge is extremely high and needs to be reduced. Therefore, a further sensitivity test has been carried out for the Al-Najaf City study area by the MODFLOW program through changing the recharge value and found that the best estimation of groundwater recharge value for this city is 16.5 mm/year where this value gives the best fitting between the calculated and observed heads with minimum values of RMSE % (13.175) and RSS m² (1454).

Keywords: Al-Najaf City, groundwater modelling, recharge estimation, visual MODFLOW

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Authors: Kalyan Koganti

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Background: In India, platelet transfusions are given to large no. of patients suffering from dengue due to the fear of bleeding especially when the platelet counts are low. Though many patients do not bleed when the platelet count falls to less than 20,000, certain patients bleed even if the platelet counts are more than 20,000 without any comorbid condition (like gastrointestinal ulcer) in the past. This fear has led to huge amounts of unnecessary platelet transfusions which cause significant economic burden to low and middle-income countries like India and also sometimes these transfusions end with transfusion-related adverse reactions. Objective: To identify the role of Activated Partial Thromboplastin Time (APTT) in comparison with thrombocytoenia as an indicator to assess the real need of platelet transfusions. Method: A prospective study was conducted at a hospital in South India which included 176 admitted cases of dengue confirmed by immunochromatography. APTT was performed in all these patients along with platelet count. Cut off values of > 60 seconds for APTT and < 20,000 for platelet count were considered to assess the bleeding manifestations. Results: Among the total 176 patients, 56 patients had bleeding manifestations like malena, hematuria, bleeding gums etc. APTT > 60 seconds had a sensitivity and specificity of 93% and 90% respectively in identifying bleeding manifestations where as platelet count of < 20,000 had a sensitivity and specificity of 64% and 73% respectively. Conclusion: Elevated APTT levels can be considered as an indicator to assess the need of platelet transfusion in dengue. As there is a significant variation among patients who bleed with respect to platelet count, APTT can be considered to avoid unnecessary transfusions.

Keywords: activated partial thromboplastin time, dengue, platelet transfusion, thrombocytopenia

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Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

Abstract:

Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

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Authors: Abu Salim Mustafa

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Water plays a major role in maintaining life on earth, but it can also serve as a matrix for pathogenic organisms, posing substantial health threats to humans. Although, outbreaks of diseases attributable to drinking water may not be common in industrialized countries, they still occur and can lead to serious acute, chronic, or sometimes fatal health consequences. The analysis of drinking water samples from different regions of Kuwait was performed in this study for bacterial and viral contaminations. Drinking tap water samples were collected from 15 different locations of the six Kuwait governorates. All samples were analyzed by confocal microscopy for the presence of bacteria. The samples were cultured in vitro to detect cultivable organisms. DNA was isolated from the cultured organisms and the identity of the bacteria was determined by sequencing the bacterial 16S rRNA genes, followed by BLAST analysis in the database of NCBI, USA. RNA was extracted from water samples and analyzed by real-time PCR for the detection of viruses with potential health risks, i.e. Astrovirus, Enterovirus, Norovirus, Rotavirus, and Hepatitis A. Confocal microscopy showed the presence of bacteria in some water samples. The 16S rRNA gene sequencing of culture grown organisms, followed by BLAST analysis, identified the presence of several non-pathogenic bacterial species. However, one sample had Acinetobacter baumannii, which often causes opportunistic infections in immunocompromised people, but none of the studied viruses could be detected in the drinking water samples analyzed. The results indicate that drinking water samples analyzed from various locations in Kuwait are relatively safe for drinking and do not contain many harmful pathogens.

Keywords: drinking water, microbial contaminant, 16S rDNA, Kuwait

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Authors: Sumia Fatima, Tayyaba Idrees

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Cardiac Arrest and Heart Failures are an important causes of mortality in developed and developing countries and even a second spent without Cardiopulmonary Resuscitation (CPR) increases the risk of mortality. Youngs doctors are expected to partake in CPR from the first day and if they are not taught basic life support (BLS) skills during their studies. They have next to no opportunity to learn them in clinical settings. To determine the exact level of knowledge of Basic Life Support among medical students. To compare the degree of knowledge among 1st and 2nd year medical students of RMU (Rawalpindi Medical University), using self-structured questionnaires. A cross sectional, qualitative primary study was conducted in March 2020 in order to analyse theoretical and practical knowledge of Basic Life Support among Medical Students of 1st and 2nd year MBBS. Self-Structured Questionnaires were distributed among 300 students, 150 from 1st year and 150 from 2nd year. Data was analysed using SPSS v 22. Chi Square test was employed. The results showed that only 13 (4%) students had received formal BLS training.129 (42%) students had encountered accidents in real life but had not known how to react. Majority responded that Basic Life Support should be made part of medical college curriculum (189 students), 194 participants (64%) had moderate knowledge of both theoretical and practical aspects of BLS. 75-80% students of both 1st and 2nd year had only moderate knowledge, which must be improved for them to be better healthcare providers in future. It was also found that male students had more practical knowledge than females, but both had almost the same proficiency in theoretical knowledge. The study concluded that the level of knowledge of BLS among the students was not up to the mark, and there is a dire need to include BLS training in the medical colleges’ curriculum.

Keywords: basic cardiac life support, cardiac arrest, awareness, medical students

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Authors: Raju Ranjha, Surbhi Aggarwal

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Background: Inflammation plays an important role in infectious and non-infectious diseases. MiRNA is also reported to play role in inflammation and associated cancers. Chemokine CXCL12 is also known to play role in inflammation and various cancers. CXCL12/CXCR4 chemokine axis was involved in pathogenesis of IBD specially UC. Supplementation of CXCL12 induces homing of dendritic cells to spleen and enhances control of plasmodium parasite in BALB/c mice. We looked at the regulation of CXCL12β by miRNA in UC colitis. Prolonged inflammation of colon in UC patient increases the risk of developing colorectal cancer. We looked at the expression differences of CXCl12β and its targeting miRNA in cancer susceptible area of colon of UC patients. Aim: Aim of this study was to find out the expression regulation of CXCL12β by miRNA in inflammation. Materials and Methods: Biopsy samples and blood samples were collected from UC patients and non-IBD controls. mRNA expression was analyzed using microarray and real-time PCR. CXCL12β targeting miRNA were looked by using online target prediction tools. Expression of CXCL12β in blood samples and cell line supernatant was analyzed using ELISA. miRNA target was validated using dual luciferase assay. Results and conclusion: We found miR-200a regulate the expression of CXCL12β in UC. Expression of CXCL12β was increased in cancer susceptible part of colon and expression of its targeting miRNA was decreased in the same part of colon. miR-200a regulate CXCL12β expression in inflammation and may be an important therapeutic target in inflammation associated cancer.

Keywords: inflammation, miRNA, regulation, CXCL12

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Authors: Castells Pau, Poetsch Christophe

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The effect of gust and turbulence encounters on aircraft is a wide field of study which allows different approaches, from high-fidelity multidisciplinary simulations to more simplified models adapted to industrial applications. The typical main goal is to predict the gust loads on the aircraft in order to ensure a safe design and achieve certification. Another topic widely studied is the gust loads reduction through an active control law. The impact of gusts on aircraft handling qualities is of interest as well in the analysis of in-service events so as to evaluate the aircraft response and the performance of the flight control laws. Traditionally, gust loads and handling qualities are addressed separately with different models adapted to the specific needs of each discipline. In this paper, an assessment of the differences between both models is presented and a strategy to better account for the physics of gust encounters in a typical flight dynamics model is proposed based on the model used for gust loads analysis. The applied corrections aim to capture the gust unsteady aerodynamics and propagation as well as the effect of dynamic flexibility at low frequencies. Results from the gust loads model at different flight conditions and measures from real events are used for validation. An assessment of a possible extension of steady aerodynamic nonlinearities to low frequency range is also addressed. The proposed corrections provide meaningful means to evaluate the performance and possible adjustments of the flight control laws.

Keywords: flight dynamics, gust loads, handling qualities, unsteady aerodynamics

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Oluwole Durodolu

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The rationale for this study is to explore the adaptive strategy that librarians adopt in performing night shifts in a mega-city like Lagos state. Maslach Burnout Theory would be used to measure the three proportions of burnout in understanding emotional exhaustion, depersonalisation, and individual accomplishment to scrutinise job-related burnout syndrome allied with longstanding, unsolved stress. The qualitative methodology guided by a phenomenological research paradigm, which is an approach that focuses on the commonality of real-life experience in a particular group, would be used, focus group discussion adopted as a method of data collection from library staff who are involved in night-shift. The participant for the focus group discussion would be selected using a convenience sampling technique in which staff at the cataloguing unit would be included in the sample because of the representative characteristics of the unit. This would be done to enable readers to understand phenomena as it is reasonable than from a remote perspective. The exploratory interviews which will be in focus group method to shed light on issues relating to security, housing, transportation, budgeting, energy supply, employee duties, time management, information access, and sustaining professional levels of service and how all these variables affect the productivity of all the 149 library staff and their work-life balance.

Keywords: nightshift, work-life balance, mega-city, academic library, Maslach Burnout Theory, Lagos State, University of Lagos

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: cold-start learning, expectation propagation, multi-armed bandits, Thompson Sampling, variational inference

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Authors: Keerthana E., Lohithya S., Harshavardhini K. S., Saranya G., Suganthi S.

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In an epoch of expanding human-machine interaction, the development of innovative interfaces that bridge the gap between physical gestures and digital control has gained significant momentum. This study introduces a distinct solution that leverages a combination of MEMS (Micro-Electro-Mechanical Systems) sensors, an Arduino Mega microcontroller, and a PC to create a hand gesture interface for PC control and SMS notification. The core of the system is an ADXL335 MEMS accelerometer sensor integrated with an Arduino Mega, which communicates with a PC via a USB cable. The ADXL335 provides real-time acceleration data, which is processed by the Arduino to detect specific hand gestures. These gestures, such as left, right, up, down, or custom patterns, are interpreted by the Arduino, and corresponding actions are triggered. In the context of SMS notifications, when a gesture indicative of a new SMS is recognized, the Arduino relays this information to the PC through the serial connection. The PC application, designed to monitor the Arduino's serial port, displays these SMS notifications in the serial monitor. This study offers an engaging and interactive means of interfacing with a PC by translating hand gestures into meaningful actions, opening up opportunities for intuitive computer control. Furthermore, the integration of SMS notifications adds a practical dimension to the system, notifying users of incoming messages as they interact with their computers. The use of MEMS sensors, Arduino, and serial communication serves as a promising foundation for expanding the capabilities of gesture-based control systems.

Keywords: hand gestures, multiple cables, serial communication, sms notification

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Authors: Hossein Edrisi

Abstract:

To study the impact of the amount and volume of power of isolation transformer on the lamps in airfield Ground Lighting Systems. A test was conducted in Persian Gulf International Airport, This airport is situated in the south of Iran and it is one of the most cutting-edge airports, the same one that owns modern devices. Iran uses materials and auxiliary equipment which are made by ADB Company from Belgium. Airfield ground lighting (AGL) systems are responsible for providing visual issue to aircrafts and helicopters in the runways. In an AGL system a great deal of lamps are connected in serial circuits to each other and each ring has its individual constant current regulators (CCR), which through that provide energy to the lamps. Control of lamps is crucial for maintenance and operation in the AGL systems. Thanks to the Programmable Logic Controller (PLC) that is a cutting-edge technology can help the system to connect the elements from substations and ATC (TOWER). For this purpose, a test in real conditions of the airport done for all element that used in the airport such as isolation transformer in different power capacity and different consuming power and brightness of the lamps. The data were analyzed with Lux meter and Multimeter. The results had shown that the increase in the power of transformer caused a significant increase in brightness. According to the Ohm’s law and voltage division, without changing the characteristics of the light bulb, it is not possible to change the voltage, just need to change the amount of transformer with which it connects to the lamps. When the voltage is increased, the current through the bulb has to increase as well, because of Ohm's law: I=V/R and I=V/R which means that if V increases, so do I increase. The output voltage on the constant current regulator emerges between the lamps and the transformers.

Keywords: AGL, CCR, lamps, transformer, Ohm’s law

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Authors: Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Tsegahun Manyazewal, Francesco Marinucci, Getachew Belay, Abraham Tesfaye, Gonfa Ayana, Amaha Kebede, Yewondwossen Tadesse, Susan Lehman, Zelalem Temesgen

Abstract:

In-service health trainings in Sub-Saharan Africa are mostly content-centered with higher disconnection with the real practice in the facility. This study intended to evaluate in-service training approach aimed to strengthen health care human resources. A combined web-based and face-to-face training was designed and piloted in Ethiopia with the diagnosis of tuberculosis. During the first part, which lasted 43 days, trainees accessed web-based material and read without leaving their work; while the second part comprised a one-day hands-on evaluation. Trainee’s competency was measured using multiple-choice questions, written-assignments, exercises and hands-on evaluation. Of 108 participants invited, 81 (75%) attended the course and 71 (88%) of them successfully completed. Of those completed, 73 (90%) scored a grade from A to C. The approach was effective to transfer knowledge and turn it into practical skills. In-service health training should transform from a passive one-time-event to a continuous behavioral change of participants and improvements on their actual work.

Keywords: Ethiopia, health care, Mycobacterium tuberculosis, training

Procedia PDF Downloads 499

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

Abstract:

The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

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Authors: Shilpa Khobragade, Carlos Da Silva Granja, Niklas Sandström, Igor Efimov, Victor P. Ostanin, Wouter van der Wijngaart, David Klenerman, Sourav K. Ghosh

Abstract:

Rapid, label-free and direct detection of pathogenic bacteria is critical for the prevention of disease outbreaks. This paper for the first time attempts to probe the nonlinear acoustic response of quartz crystal resonator (QCR) functionalized with specific DNA aptamers for direct detection and quantification of viable E. coli KCTC 2571 bacteria. DNA aptamers were immobilized through biotin and streptavidin conjugation, onto the gold surface of QCR to capture the target bacteria and the detection was accomplished by shift in amplitude of the peak 3f signal (3 times the drive frequency) upon binding, when driven near fundamental resonance frequency. The developed nonlinear acoustic aptasensor system demonstrated better reliability than conventional resonance frequency shift and energy dissipation monitoring that were recorded simultaneously. This sensing system could directly detect 10⁽⁵⁾ cells/mL target bacteria within 30 min or less and had high specificity towards E. coli KCTC 2571 bacteria as compared to the same concentration of S.typhi bacteria. Aptasensor response was observed for the bacterial suspensions ranging from 10⁽⁵⁾-10⁽⁸⁾ cells/mL. Conclusively, this nonlinear acoustic aptasensor is simple to use, gives real-time output, cost-effective and has the potential for rapid, specific, label-free direction detection of bacteria.

Keywords: acoustic, aptasensor, detection, nonlinear

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Authors: Sukhwinder K. Bhullar, M. B. G. Jun

Abstract:

The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

Procedia PDF Downloads 457

Authors: Prathiksha Kamath, Pratibha Jamkhandi, Prateek Ghanti, Priyanshu Gupta, M. Lakshmi Neelima

Abstract:

Combining Image Captioning and Visual Question Answering (VQA) tasks have emerged as a new and exciting research area. The image captioning task involves generating a textual description that summarizes the content of the image. VQA aims to answer a natural language question about the image. Both these tasks include computer vision and natural language processing (NLP) and require a deep understanding of the content of the image and semantic relationship within the image and the ability to generate a response in natural language. There has been remarkable growth in both these tasks with rapid advancement in deep learning. In this paper, we present a comprehensive review of recent progress in combining image captioning and visual question-answering (VQA) tasks. We first discuss both image captioning and VQA tasks individually and then the various ways in which both these tasks can be integrated. We also analyze the challenges associated with these tasks and ways to overcome them. We finally discuss the various datasets and evaluation metrics used in these tasks. This paper concludes with the need for generating captions based on the context and captions that are able to answer the most likely asked questions about the image so as to aid the VQA task. Overall, this review highlights the significant progress made in combining image captioning and VQA, as well as the ongoing challenges and opportunities for further research in this exciting and rapidly evolving field, which has the potential to improve the performance of real-world applications such as autonomous vehicles, robotics, and image search.

Keywords: image captioning, visual question answering, deep learning, natural language processing

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Authors: Maxime Alex Junior Kuitche, Ruxandra Mihaela Botez, Jean-Chirstophe Maunand

Abstract:

The evolution of aircraft is closely linked to the study and improvement of propulsion systems. Determining the propulsion performance is a real challenge in aircraft modeling and design. In addition to theoretical methodologies, experimental procedures are used to obtain a good estimation of the propulsion performances. For piston-propeller propulsion, the propeller needs several experimental tests which could be extremely demanding in terms of time and money. This paper presents a new procedure to estimate the performance of a propeller from a numerical approach using computational fluid dynamic analysis. The propeller was initially scanned, and then, its 3D model was represented using CATIA. A structured meshing and Shear Stress Transition k-ω turbulence model were applied to describe accurately the flow pattern around the propeller. Thus, the Partial Differential Equations were solved using ANSYS FLUENT software. The method was applied on the UAS-S45’s propeller designed and manufactured by Hydra Technologies in Mexico. An extensive investigation was performed for several flight conditions in terms of altitudes and airspeeds with the aim to determine thrust coefficients, power coefficients and efficiency of the propeller. The Computational Fluid Dynamics results were compared with experimental data acquired from wind tunnel tests performed at the LARCASE Price-Paidoussis wind tunnel. The results of this comparison have demonstrated that our approach was highly accurate.

Keywords: CFD analysis, propeller performance, unmanned aerial system propeller, UAS-S45

Procedia PDF Downloads 349

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

Abstract:

Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Adesoji Tunbosun Jaiyeola, Josiah Adeyemo

Abstract:

Sediment yield can be considered to be the total sediment load that leaves a drainage basin. The knowledge of the quantity of sediments present in a river at a particular time can lead to better flood capacity in reservoirs and consequently help to control over-bane flooding. Furthermore, as sediment accumulates in the reservoir, it gradually loses its ability to store water for the purposes for which it was built. The development of hydrological models to forecast the quantity of sediment present in a reservoir helps planners and managers of water resources systems, to understand the system better in terms of its problems and alternative ways to address them. The application of artificial intelligence models and technique to such real-life situations have proven to be an effective approach of solving complex problems. This paper makes an extensive review of literature relevant to the theories and applications of evolutionary algorithms, and most especially genetic programming. The successful applications of genetic programming as a soft computing technique were reviewed in sediment modelling and other branches of knowledge. Some fundamental issues such as benchmark, generalization ability, bloat and over-fitting and other open issues relating to the working principles of GP, which needs to be addressed by the GP community were also highlighted. This review aim to give GP theoreticians, researchers and the general community of GP enough research direction, valuable guide and also keep all stakeholders abreast of the issues which need attention during the next decade for the advancement of GP.

Keywords: benchmark, bloat, generalization, genetic programming, over-fitting, sediment yield

Procedia PDF Downloads 442