Search results for: real time pest tracking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21491

Search results for: real time pest tracking

17231 Development of a Humanized Anti-CEA Antibody for the Near Infrared Optical Imaging of Cancer

Authors: Paul J Yazaki, Michael Bouvet, John Shively

Abstract:

Surgery for solid gastrointestinal (GI) cancers such as pancreatic, colorectal, and gastric adenocarcinoma remains the mainstay of curative therapy. Complete resection of the primary tumor with negative margins (R0 resection), its draining lymph nodes, and distant metastases offers the optimal surgical benefit. Real-time fluorescence guided surgery (FGS) promises to improve GI cancer outcomes and is rapidly advancing with tumor-specific antibody conjugated fluorophores that can be imaged using near infrared (NIR) technology. Carcinoembryonic Antigen (CEA) is a non-internalizing tumor antigen validated as a surface tumor marker expressed in >95% of colorectal, 80% of gastric, and 60% of pancreatic adenocarcinomas. Our humanized anti-CEA hT84.66-M5A (M5A) monoclonal antibody (mAb)was conjugated with the NHS-IRDye800CW fluorophore and shown it can rapidly and effectively NIRoptical imageorthotopically implanted human colon and pancreatic cancer in mouse models. A limitation observed is that these NIR-800 dye conjugated mAbs have a rapid clearance from the blood, leading to a narrow timeframe for FGS and requiring high doses for effective optical imaging. We developed a novel antibody-fluorophore conjugate by incorporating a PEGylated sidearm linker to shield or mask the IR800 dye’s hydrophobicity which effectively extended the agent’s blood circulation half-life leading to increased tumor sensitivity and lowered normal hepatic uptake. We hypothesized that our unique anti-CEA linked to the fluorophore, IR800 by PEGylated sidewinder, M5A-SW-IR800 will become the next generation optical imaging agent, safe, effective, and widely applicable for intraoperative image guided surgery in CEA expressing GI cancers.

Keywords: optical imaging, anti-CEA, cancer, fluorescence-guided surgery

Procedia PDF Downloads 147
17230 Robotics Technology Supported Pedagogic Models in Science, Technology, Engineering, Arts and Mathematics Education

Authors: Sereen Itani

Abstract:

As the world aspires for technological innovation, Innovative Robotics Technology-Supported Pedagogic Models in STEAM Education (Science, Technology, Engineering, Arts, and Mathematics) are critical in our global education system to build and enhance the next generation 21st century skills. Thus, diverse international schools endeavor in attempts to construct an integrated robotics and technology enhanced curriculum based on interdisciplinary subjects. Accordingly, it is vital that the globe remains resilient in STEAM fields by equipping the future learners and educators with Innovative Technology Experiences through robotics to support such fields. A variety of advanced teaching methods is employed to learn about Robotics Technology-integrated pedagogic models. Therefore, it is only when STEAM and innovations in Robotic Technology becomes integrated with real-world applications that transformational learning can occur. Robotics STEAM education implementation faces major challenges globally. Moreover, STEAM skills and concepts are communicated in separation from the real world. Instilling the passion for robotics and STEAM subjects and educators’ preparation could lead to the students’ majoring in such fields by acquiring enough knowledge to make vital contributions to the global STEAM industries. Thus, this necessitates the establishment of Pedagogic models such as Innovative Robotics Technologies to enhance STEAM education and develop students’ 21st-century skills. Moreover, an ICT innovative supported robotics classroom will help educators empower and assess students academically. Globally, the Robotics Design System and platforms are developing in schools and university labs creating a suitable environment for the robotics cross-discipline STEAM learning. Accordingly, the research aims at raising awareness about the importance of robotics design systems and methodologies of effective employment of robotics innovative technology-supported pedagogic models to enhance and develop (STEAM) education globally and enhance the next generation 21st century skills.

Keywords: education, robotics, STEAM (Science, Technology, Engineering, Arts and Mathematics Education), challenges

Procedia PDF Downloads 384
17229 AI-Driven Solutions for Optimizing Master Data Management

Authors: Srinivas Vangari

Abstract:

In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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17228 Numerical Simulation of a Three-Dimensional Framework under the Action of Two-Dimensional Moving Loads

Authors: Jia-Jang Wu

Abstract:

The objective of this research is to develop a general technique so that one may predict the dynamic behaviour of a three-dimensional scale crane model subjected to time-dependent moving point forces by means of conventional finite element computer packages. To this end, the whole scale crane model is divided into two parts: the stationary framework and the moving substructure. In such a case, the dynamic responses of a scale crane model can be predicted from the forced vibration responses of the stationary framework due to actions of the four time-dependent moving point forces induced by the moving substructure. Since the magnitudes and positions of the moving point forces are dependent on the relative positions between the trolley, moving substructure and the stationary framework, it can be found from the numerical results that the time histories for the moving speeds of the moving substructure and the trolley are the key factors affecting the dynamic responses of the scale crane model.

Keywords: moving load, moving substructure, dynamic responses, forced vibration responses

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17227 The Effects of the GAA15 (Gaelic Athletic Association 15) on Lower Extremity Injury Incidence and Neuromuscular Functional Outcomes in Collegiate Gaelic Games: A 2 Year Prospective Study

Authors: Brenagh E. Schlingermann, Clare Lodge, Paula Rankin

Abstract:

Background: Gaelic football, hurling and camogie are highly popular field games in Ireland. Research into the epidemiology of injury in Gaelic games revealed that approximately three quarters of the injuries in the games occur in the lower extremity. These injuries can have player, team and institutional impacts due to multiple factors including financial burden and time loss from competition. Research has shown it is possible to record injury data consistently with the GAA through a closed online recording system known as the GAA injury surveillance database. It has been established that determining the incidence of injury is the first step of injury prevention. The goals of this study were to create a dynamic GAA15 injury prevention programme which addressed five key components/goals; avoid positions associated with a high risk of injury, enhance flexibility, enhance strength, optimize plyometrics and address sports specific agilities. These key components are internationally recognized through the Prevent Injury, Enhance performance (PEP) programme which has proven reductions in ACL injuries by 74%. In national Gaelic games the programme is known as the GAA15 which has been devised from the principles of the PEP. No such injury prevention strategies have been published on this cohort in Gaelic games to date. This study will investigate the effects of the GAA15 on injury incidence and neuromuscular function in Gaelic games. Methods: A total of 154 players (mean age 20.32 ± 2.84) were recruited from the GAA teams within the Institute of Technology Carlow (ITC). Preseason and post season testing involved two objective screening tests; Y balance test and Three Hop Test. Practical workshops, with ongoing liaison, were provided to the coaches on the implementation of the GAA15. The programme was performed before every training session and game and the existing GAA injury surveillance database was accessed to monitor player’s injuries by the college sports rehabilitation athletic therapist. Retrospective analysis of the ITC clinic records were performed in conjunction with the database analysis as a means of tracking injuries that may have been missed. The effects of the programme were analysed by comparing the intervention groups Y balance and three hop test scores to an age/gender matched control group. Results: Year 1 results revealed significant increases in neuromuscular function as a result of the GAA15. Y Balance test scores for the intervention group increased in both the posterolateral (p=.005 and p=.001) and posteromedial reach directions (p= .001 and p=.001). A decrease in performance was determined for the three hop test (p=.039). Overall twenty-five injuries were reported during the season resulting in an injury rate of 3.00 injuries/1000hrs of participation; 1.25 injuries/1000hrs training and 4.25 injuries/1000hrs match play. Non-contact injuries accounted for 40% of the injuries sustained. Year 2 results are pending and expected April 2016. Conclusion: It is envisaged that implementation of the GAA15 will continue to reduce the risk of injury and improve neuromuscular function in collegiate Gaelic games athletes.

Keywords: GAA15, Gaelic games, injury prevention, neuromuscular training

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17226 Breast Cancer: The Potential of miRNA for Diagnosis and Treatment

Authors: Abbas Pourreza

Abstract:

MicroRNAs (miRNAs) are small single-stranded non-coding RNAs. They are almost 18-25 nucleotides long and very conservative through evolution. They are involved in adjusting the expression of numerous genes due to the existence of a complementary region, generally in the 3' untranslated regions (UTR) of target genes, against particular mRNAs in the cell. Also, miRNAs have been proven to be involved in cell development, differentiation, proliferation, and apoptosis. More than 2000 miRNAs have been recognized in human cells, and these miRNAs adjust approximately one-third of all genes in human cells. Dysregulation of miRNA originated from abnormal DNA methylation patterns of the locus, cause to down-regulated or overexpression of miRNAs, and it may affect tumor formation or development of it. Breast cancer (BC) is the most commonly identified cancer, the most prevalent cancer (23%), and the second-leading (14%) mortality in all types of cancer in females. BC can be classified based on the status (+/−) of the hormone receptors, including estrogen receptor (ER), progesterone receptor (PR), and the Receptor tyrosine-protein kinase erbB-2 (ERBB2 or HER2). Currently, there are four main molecular subtypes of BC: luminal A, approximately 50–60 % of BCs; luminal B, 10–20 %; HER2 positive, 15–20 %, and 10–20 % considered Basal (triple-negative breast cancer (TNBC)) subtype. Aberrant expression of miR-145, miR-21, miR-10b, miR-125a, and miR-206 was detected by Stem-loop real-time RT-PCR in BC cases. Breast tumor formation and development may result from down-regulation of a tumor suppressor miRNA such as miR-145, miR-125a, and miR-206 and/or overexpression of an oncogenic miRNA such as miR-21 and miR-10b. MiR-125a, miR-206, miR-145, miR-21, and miR-10b are hugely predicted to be new tumor markers for the diagnosis and prognosis of BC. MiR-21 and miR-125a could play a part in the treatment of HER-2-positive breast cancer cells, while miR-145 and miR-206 could speed up the evolution of cure techniques for TNBC. To conclude, miRNAs will be presented as hopeful molecules to be used in the primary diagnosis, prognosis, and treatment of BC and battle as opposed to its developed drug resistance.

Keywords: breast cancer, HER2 positive, miRNA, TNBC

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17225 Determining a Suitable Time and Temperature Combination for Electricial Conductivity Test in Sorghum

Authors: Mehmet Demir Kaya, Onur İleri, Süleyman Avcı

Abstract:

This study was conducted to determine a suitable time and temperature combination for the electrical conductivity test to be used in sorghum seeds. Fifty seeds known initial seed moisture content and weight of fresh and dead seeds (105°C for 6h) of seven sorghum cultivars were used as material. The electrical conductivities of soak water were measured using EC meter at 20, 25 and 30°C for 4, 8, 12 and 24 h using 50 mL deionized water. The experimental design was three factors factorial (7 × 3 × 4) arranged in a completely randomized design; with four replications and 50 seeds per replicate. The results showed that increased time and temperature caused a remarkable increase in EC values of all of the cultivars. Temperature significantly affected the electrical conductivity values and the best results were obtained at 25°C. The cultivars having the lowest germination percentage gave the highest electrical conductivity value. Dead seeds always gave higher electrical conductivity at 25°C for all periods. It was concluded that the temperature of 25°C and higher period than 12 h was the optimum combination for the electrical conductivity test in sorghum.

Keywords: Sorghum bicolor, seed vigor, cultivar, temperature

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17224 Plant Mediated RNAi Approach to Knock Down Ecdysone Receptor Gene of Colorado Potato Beetle

Authors: Tahira Hussain, Ilhom Rahamkulov, Muhammad Aasim, Ugur Pirlak, Emre Aksoy, Mehmet Emin Caliskan, Allah Bakhsh

Abstract:

RNA interference (RNAi) has proved its usefulness in functional genomic research on insects recently and is considered potential strategy in crop improvement for the control of insect pests. The different insect pests incur significant losses to potato yield worldwide, Colorado Potato Beetle (CPB) being most notorious one. The present study focuses to knock down highly specific 20-hydroxyecdysone hormone-receptor complex interaction by using RNAi approach to silence Ecdysone receptor (EcR) gene of CPB in transgenic potato plants expressing dsRNA of EcR gene. The partial cDNA of Ecdysone receptor gene of CPB was amplified using specific primers in sense and anti-sense orientation and cloned in pRNAi-GG vector flanked by an intronic sequence (pdk). Leaf and internodal explants of Lady Olympia, Agria and Granola cultivars of potato were infected with Agrobacterium strain LBA4404 harboring plasmid pRNAi-CPB, pRNAi-GFP (used as control). Neomycin phosphotransferase (nptII) gene was used as a plant selectable marker at a concentration of 100 mg L⁻¹. The primary transformants obtained have shown proper integration of T-DNA in plant genome by standard molecular analysis like polymerase chain reaction (PCR), real-time PCR, Sothern blot. The transgenic plants developed out of these cultivars are being evaluated for their efficacy against larvae as well adults of CPB. The transgenic lines are expected to inhibit expression of EcR protein gene, hindering their molting process, hence leading to increased potato yield.

Keywords: plant mediated RNAi, molecular strategy, ecdysone receptor, insect metamorphosis

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17223 Effect of Deer Antler Extract on Osteogenic Gene Expression and Longitudinal Bone Growth of Adolescent Male Rats

Authors: Kang-Hyun Leem, Myung-Gyou Kim, Hye Kyung Kim

Abstract:

Deer antler, traditionally used as a tonic and valuable drug in oriental medicine, has been considered to possess bone-strengthening activity. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study was performed to examine the effects of different parts of deer antler extract (DH) on osteogenic gene expressions in MG-63 cells and longitudinal bone growth in adolescent male rats. The expressions of osteogenic genes, collagen, alkaline phosphatase, osteocalcin, and osteopontin, were measured by quantitative real-time PCR. Longitudinal bone growth was measured in 3-week-old male Sprague-Dawley rats using fluorescence microscopy. To examine the effects on the growth plate metabolism, the total height of growth plate and bone morphogenetic protein-2 (BMP-2) were measured. Collagen and osteocalcin mRNA expressions were increased by all three parts of the DH treatment while osteopontin gene expression was not affected by any of the DH treatment. Alkaline phosphatase gene expression was increased by upper and mid part of DH while base part of DH fails to affect alkaline phosphatase gene expression. The upper and mid parts of the DH treatment enhanced longitudinal bone growth and total height of growth plate. The induction of BMP-2 protein expression in growth plate assessed by immunostaining was also promoted by upper and mid parts of the DH treatment. These results suggest that DH, especially upper and mid parts, stimulate osteogenic gene expressions and have the effect on bone growth in adolescent rats and might be used for the growth delayed adolescent and inherent growth failure patient.

Keywords: bone morphogenetic protein-2, deer antler, longitudinal bone growth, osteogenic genes

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17222 Design and Implementation of Control System in Underwater Glider of Ganeshblue

Authors: Imam Taufiqurrahman, Anugrah Adiwilaga, Egi Hidayat, Bambang Riyanto Trilaksono

Abstract:

Autonomous Underwater Vehicle glider is one of the renewal of underwater vehicles. This vehicle is one of the autonomous underwater vehicles that are being developed in Indonesia. Glide ability is obtained by controlling the buoyancy and attitude of the vehicle using the movers within the vehicle. The glider motion mechanism is expected to provide energy resistance from autonomous underwater vehicles so as to increase the cruising range of rides while performing missions. The control system on the vehicle consists of three parts: controlling the attitude of the pitch, the buoyancy engine controller and the yaw controller. The buoyancy and pitch controls on the vehicle are sequentially referring to the finite state machine with pitch angle and depth of diving inputs to obtain a gliding cycle. While the yaw control is done through the rudder for the needs of the guide system. This research is focused on design and implementation of control system of Autonomous Underwater Vehicle glider based on PID anti-windup. The control system is implemented on an ARM TS-7250-V2 device along with a mathematical model of the vehicle in MATLAB using the hardware-in-the-loop simulation (HILS) method. The TS-7250-V2 is chosen because it complies industry standards, has high computing capability, minimal power consumption. The results show that the control system in HILS process can form glide cycle with depth and angle of operation as desired. In the implementation using half control and full control mode, from the experiment can be concluded in full control mode more precision when tracking the reference. While half control mode is considered more efficient in carrying out the mission.

Keywords: control system, PID, underwater glider, marine robotics

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17221 Optimizing Energy Efficiency: Leveraging Big Data Analytics and AWS Services for Buildings and Industries

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 64
17220 Application of Dissolved Air Flotation for Removal of Oil from Wastewater

Authors: Talat Ghomashchi, Zahra Akbari, Shirin Malekpour, Marjan Alimirzaee

Abstract:

Mixing the waste water of industries with natural water has caused environmental pollution. So researcher try to obtain methods and optimum conditions for waste water treatment. One of important stage in waste water treatment is dissolved air flotation. DAF is used for the removal of suspended solids and oils from waste water. In this paper, the effect of several parameters on flotation efficiency with Cationic polyacrylamide as flocculant, was examined, namely, (a) concentration of cationic flocculants, (b) pH (c) fast mixing time, (d) fast mixing speed,(e) slow mixing time,(f) retention time and temperature. After design of experiment, in each trial turbidity of waste water was measured by spectrophotometer. Results show that contribution of pH and concentration of flocculant on flotation efficiency are 75% and 9% respectively. Cationic polyacrylamide led to a significant increase in the settling speed and effect of temperature is negligible. In the optimum condition, the outcome of the DAF unit is increased and amount of suspended solid and oil in waste water is decreased effectively.

Keywords: dissolved air flotation, oil industry, waste water, treatment

Procedia PDF Downloads 530
17219 Clinical Relevance of TMPRSS2-ERG Fusion Marker for Prostate Cancer

Authors: Shalu Jain, Anju Bansal, Anup Kumar, Sunita Saxena

Abstract:

Objectives: The novel TMPRSS2:ERG gene fusion is a common somatic event in prostate cancer that in some studies is linked with a more aggressive disease phenotype. Thus, this study aims to determine whether clinical variables are associated with the presence of TMPRSS2:ERG-fusion gene transcript in Indian patients of prostate cancer. Methods: We evaluated the clinical variables with presence and absence of TMPRSS2:ERG gene fusion in prostate cancer and BPH association of clinical patients. Patients referred for prostate biopsy because of abnormal DRE or/and elevated sPSA were enrolled for this prospective clinical study. TMPRSS2:ERG mRNA copies in samples were quantified using a Taqman chemistry by real time PCR assay in prostate biopsy samples (N=42). The T2:ERG assay detects the gene fusion mRNA isoform TMPRSS2 exon1 to ERG exon4. Results: Histopathology report has confirmed 25 cases as prostate cancer adenocarcinoma (PCa) and 17 patients as benign prostate hyperplasia (BPH). Out of 25 PCa cases, 16 (64%) were T2: ERG fusion positive. All 17 BPH controls were fusion negative. The T2:ERG fusion transcript was exclusively specific for prostate cancer as no case of BPH was detected having T2:ERG fusion, showing 100% specificity. The positive predictive value of fusion marker for prostate cancer is thus 100% and the negative predictive value is 65.3%. The T2:ERG fusion marker is significantly associated with clinical variables like no. of positive cores in prostate biopsy, Gleason score, serum PSA, perineural invasion, perivascular invasion and periprostatic fat involvement. Conclusions: Prostate cancer is a heterogeneous disease that may be defined by molecular subtypes such as the TMPRSS2:ERG fusion. In the present prospective study, the T2:ERG quantitative assay demonstrated high specificity for predicting biopsy outcome; sensitivity was similar to the prevalence of T2:ERG gene fusions in prostate tumors. These data suggest that further improvement in diagnostic accuracy could be achieved using a nomogram that combines T2:ERG with other markers and risk factors for prostate cancer.

Keywords: prostate cancer, genetic rearrangement, TMPRSS2:ERG fusion, clinical variables

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17218 TNFRSF11B Gene Polymorphisms A163G and G11811C in Prediction of Osteoporosis Risk

Authors: I. Boroňová, J.Bernasovská, J. Kľoc, Z. Tomková, E. Petrejčíková, D. Gabriková, S. Mačeková

Abstract:

Osteoporosis is a complex health disease characterized by low bone mineral density, which is determined by an interaction of genetics with metabolic and environmental factors. Current research in genetics of osteoporosis is focused on identification of responsible genes and polymorphisms. TNFRSF11B gene plays a key role in bone remodeling. The aim of this study was to investigate the genotype and allele distribution of A163G (rs3102735) osteoprotegerin gene promoter and G1181C (rs2073618) osteoprotegerin first exon polymorphisms in the group of 180 unrelated postmenopausal women with diagnosed osteoporosis and 180 normal controls. Genomic DNA was isolated from peripheral blood leukocytes using standard methodology. Genotyping for presence of different polymorphisms was performed using the Custom Taqman®SNP Genotyping assays. Hardy-Weinberg equilibrium was tested for each SNP in the groups of participants using the chi-square (χ2) test. The distribution of investigated genotypes in the group of patients with osteoporosis were as follows: AA (66.7%), AG (32.2%), GG (1.1%) for A163G polymorphism; GG (19.4%), CG (44.4%), CC (36.1%) for G1181C polymorphism. The distribution of genotypes in normal controls were follows: AA (71.1%), AG (26.1%), GG (2.8%) for A163G polymorphism; GG (22.2%), CG (48.9%), CC (28.9%) for G1181C polymorphism. In A163G polymorphism the variant G allele was more common among patients with osteoporosis: 17.2% versus 15.8% in normal controls. Also, in G1181C polymorphism the phenomenon of more frequent occurrence of C allele in the group of patients with osteoporosis was observed (58.3% versus 53.3%). Genotype and allele distributions showed no significant differences (A163G: χ2=0.270, p=0.605; χ2=0.250, p=0.616; G1181C: χ2= 1.730, p=0.188; χ2=1.820, p=0.177). Our results represents an initial study, further studies of more numerous file and associations studies will be carried out. Knowing the distribution of genotypes is important for assessing the impact of these polymorphisms on various parameters associated with osteoporosis. Screening for identification of “at-risk” women likely to develop osteoporosis and initiating subsequent early intervention appears to be most effective strategy to substantially reduce the risks of osteoporosis.

Keywords: osteoporosis, real-time PCR method, SNP polymorphisms

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17217 The Influence of Beta Shape Parameters in Project Planning

Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

Abstract:

Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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17216 Performance Analysis of BLDC Motors for Flywheel Energy Storage Applications with Nonmagnetic vs. Magnetic Core Stator using Finite Element Time Stepping Method

Authors: Alok Kumar Pasa, Krs Raghavan

Abstract:

This paper presents a comparative analysis of Brushless DC (BLDC) motors for flywheel applications with a focus on the choice of stator core materials. The study employs a Finite Element Method (FEM) in time domain to investigate the performance characteristics of BLDC motors equipped with nonmagnetic and magnetic type stator core materials. Preliminary results reveal significant differences in motor efficiency, torque production, and electromagnetic properties between the two configurations. This research sheds light on the advantages of utilizing nonmagnetic materials in BLDC motors for flywheel applications, offering potential advantages in terms of efficiency, weight reduction and cost-effectiveness.

Keywords: finite element time stepping method, high-speed BLDC motor, flywheel energy storage system, coreless BLDC motors

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17215 Enhancement of Road Defect Detection Using First-Level Algorithm Based on Channel Shuffling and Multi-Scale Feature Fusion

Authors: Yifan Hou, Haibo Liu, Le Jiang, Wandong Su, Binqing Wang

Abstract:

Road defect detection is crucial for modern urban management and infrastructure maintenance. Traditional road defect detection methods mostly rely on manual labor, which is not only inefficient but also difficult to ensure their reliability. However, existing deep learning-based road defect detection models have poor detection performance in complex environments and lack robustness to multi-scale targets. To address this challenge, this paper proposes a distinct detection framework based on the one stage algorithm network structure. This article designs a deep feature extraction network based on RCSDarknet, which applies channel shuffling to enhance information fusion between tensors. Through repeated stacking of RCS modules, the information flow between different channels of adjacent layer features is enhanced to improve the model's ability to capture target spatial features. In addition, a multi-scale feature fusion mechanism with weighted dual flow paths was adopted to fuse spatial features of different scales, thereby further improving the detection performance of the model at different scales. To validate the performance of the proposed algorithm, we tested it using the RDD2022 dataset. The experimental results show that the enhancement algorithm achieved 84.14% mAP, which is 1.06% higher than the currently advanced YOLOv8 algorithm. Through visualization analysis of the results, it can also be seen that our proposed algorithm has good performance in detecting targets of different scales in complex scenes. The above experimental results demonstrate the effectiveness and superiority of the proposed algorithm, providing valuable insights for advancing real-time road defect detection methods.

Keywords: roads, defect detection, visualization, deep learning

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17214 Seismic Behavior and Loss Assessment of High–Rise Buildings with Light Gauge Steel–Concrete Hybrid Structure

Authors: Bing Lu, Shuang Li, Hongyuan Zhou

Abstract:

The steel–concrete hybrid structure has been extensively employed in high–rise buildings and super high–rise buildings. The light gauge steel–concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a new–type steel–concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high–rise buildings with three different concrete hybrid structures were investigated through finite element software, respectively. The three concrete hybrid structures are reinforced concrete column–steel beam (RC‒S) hybrid structure, concrete–filled steel tube column–steel beam (CFST‒S) hybrid structure, and tubed concrete column–steel beam (TC‒S) hybrid structure. The nonlinear time-history analysis of three high–rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high–rise buildings were superior. Under extremely rare earthquakes, the maximum inter–storey drifts of three high–rise buildings are significantly lower than 1/50. The inter–storey drift and floor acceleration of high–rise building with CFST‒S hybrid structure were bigger than those of high–rise buildings with RC‒S hybrid structure, and smaller than those of high–rise building with TC‒S hybrid structure. Then, based on the time–history analysis results, the post-earthquake repair cost ratio and repair time of three high–rise buildings were predicted through an economic performance analysis method proposed in FEMA‒P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC‒S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel–concrete hybrid structure, high–rise building, time–history analysis

Procedia PDF Downloads 185
17213 Modeling and Simulation of Secondary Breakup and Its Influence on Fuel Spray in High Torque Low Speed Diesel Engine

Authors: Mohsin Raza, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

Abstract:

High torque low-speed diesel engine has a wide range of industrial and commercial applications. In literature, it’s found that lot of work has been done for the high-speed diesel engine and research on High Torque low-speed is rare. The fuel injection plays a key role in the efficiency of engine and reduction in exhaust emission. The fuel breakup plays a critical role in air-fuel mixture and spray combustion. The current study explains numerically an important phenomenon in spray combustion which is deformation and breakup of liquid drops in compression ignition internal combustion engine. The secondary breakup and its influence on spray and characteristics of compressed gas in-cylinder have been calculated by using simulation software in the backdrop of high torque low-speed diesel like conditions. The secondary spray breakup is modeled with KH - RT instabilities. The continuous field is described by turbulence model and dynamics of the dispersed droplet is modeled by Lagrangian tracking scheme. The results by using KH - RT model are compared against other default methods in OpenFOAM and published experimental data from research and implemented in CFD (Computational Fluid Dynamics). These numerical simulation, done in OpenFoam and Matlab, results are analyzed for the complete 720- degree 4 stroke engine cycle at a low engine speed, for favorable agreement to be achieved. Results thus obtained will be analyzed for better evaporation in near nozzle region. The proposed analyses will further help in better engine efficiency, low emission and improved fuel economy.

Keywords: diesel fuel, KH-RT, Lagrangian , Open FOAM, secondary breakup

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17212 CAP-Glycine Protein Governs Growth, Differentiation, and the Pathogenicity of Global Meningoencephalitis Fungi

Authors: Kyung-Tae Lee, Li Li Wang, Kwang-Woo Jung, Yong-Sun Bahn

Abstract:

Microtubules are involved in mechanical support, cytoplasmic organization as well as in a number of cellular processes by interacting with diverse microtubule-associated proteins (MAPs), such as plus-end tracking proteins, motor proteins, and tubulin-folding cofactors. A common feature of these proteins is the presence of a cytoskeleton-associated protein-glycine-rich (CAP-Gly) domain, which is evolutionarily conserved and generally considered to bind to α-tubulin to regulate functions of microtubules. However, there has been a dearth of research on CAP-Gly proteins in fungal pathogens, including Cryptococcus neoformans, which causes fatal meningoencephalitis globally. In this study, we identified five CAP-Gly proteins encoding genes in C. neoformans. Among these, Cgp1, encoded by CNAG_06352, has a unique domain structure that has not been reported before in other eukaryotes. Supporting the role of Cpg1 in microtubule-related functions, we demonstrate that deletion or overexpression of CGP1 alters cellular susceptibility to thiabendazole, a microtubule destabilizer, and Cgp1 is co-localized with cytoplasmic microtubules. Related to the cellular functions of microtubules, Cgp1 also governs maintenance of membrane stability and genotoxic stress responses. Furthermore, we demonstrate that Cgp1 uniquely regulates sexual differentiation of C. neoformans with distinct roles in the early and late stage of mating. Our domain analysis reveals that the CAP-Gly domain plays major roles in all the functions of Cgp1. Finally, the cgp1Δ mutant is attenuated in virulence. In conclusion, this novel CAP-Gly protein, Cgp1, has pleotropic roles in regulating growth, stress responses, differentiation and pathogenicity of C. neoformans.

Keywords: human fungal pathogen, CAP-Glycine protein, microtubule, meningoencephalitis

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17211 Generating Swarm Satellite Data Using Long Short-Term Memory and Generative Adversarial Networks for the Detection of Seismic Precursors

Authors: Yaxin Bi

Abstract:

Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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17210 Modification of Polyolefin Membrane Using Supercritical Carbon Dioxide for Redox Flow Batteries

Authors: Vadim V. Zefirov, Victor E. Sizov, Marina A. Pigaleva, Igor V. Elmanovich, Mikhail S. Kondratenko, Marat O. Gallyamov

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This work presents a novel method for treating porous hydrophobic polyolefin membranes using supercritical carbon dioxide that allows usage of the modified membrane in redox flow batteries with an aqueous electrolyte. Polyolefin membranes are well known and widely used, however, they cannot be used as separators in redox flow batteries with an aqueous electrolyte since they have insufficient wettability, and therefore do not provide sufficient proton conductivity. The main aim of the presented work was the development of hydrophilic composites based on cheap membranes and precursors. Supercritical fluid was used as a medium for the deposition of the hydrophilic phase on the hydrophobic surface of the membrane. Due to the absence of negative capillary effects in a supercritical medium, a homogeneous composite is obtained as a result of synthesis. The in-situ synthesized silicon oxide nanoparticles and the chitosan polymer layer act as the hydrophilic phase and not only increase the affinity of the membrane towards the electrolyte, but also reduce the pore size of the polymer matrix, which positively affects the ion selectivity of the membrane. The composite material obtained as a result of synthesis has enhanced hydrophilic properties and is capable of providing proton conductivity in redox flow batteries. The morphology of the obtained composites was characterized by electron microscopy. To analyze the phase composition, infrared spectroscopy was used. The hydrophilic properties were studied by water contact angle measurements. In addition, the proton conductivity and ion selectivity of the obtained samples were studied, and tests in real redox flow batteries were performed. As a result, modified membrane was characterised in detail and moreover it was shown that modified cheap polyolefin membranes have pronounced proton conductivity and high ion selectivity, so their performance in a real redox flow battery approaches expensive commercial analogues, reaching 70% of energy efficiency.

Keywords: carbon dioxide, chitosan, polymer membrane, redox flow batteries, silica nanoparticles, supercritical fluid

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17209 Cracking of Tar Analogue in N₂ Carrier Gas Using Non-Thermal Plasma Dielectric Barrier Discharge Reactor

Authors: Faisal Saleem, Kui Zhang, Adam Harvey

Abstract:

The role of N₂ carrier gas towards the conversion of tar analogue was studied in a non-thermal plasma dielectric barrier discharge (DBD) reactor. The important parameters such as power (5-40W), residence time (1.41-4.23 s), concentration (20-82 g/Nm³), and temperature (Ambient-400°C) were explored. The present study demonstrated that plasma power and residence time played a key role in the decomposition of toluene, and almost complete removal of toluene was observed at 40w and 4.23 s. H₂ is obtained as a major gaseous product with a maximum selectivity of 40% along with some lighter hydrocarbons (5.5%). The removal efficiency of toluene slightly decreases with increasing the concentration of toluene from 20 g/Nm³ to 82 g/Nm³. The solid residue formation takes place inside the plasma reactor. The selectivity of LHC (lower hydrocarbons) increased up to 15% by increasing the temperature to 400°C. Introducing H₂ to the gas at elevated temperature opens up new reaction routes to raise the selectivity to lower hydrocarbons. The selectivity to methane reaches to 42% using 35% H₂ at 400°C and total selectivity of LHC increases to 57%.

Keywords: biomass gasification tar, non-thermal plasma, dielectric barrier discharge, residence time

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17208 Isolation and Molecular Detection of Marek’s Disease Virus from Outbreak Cases in Chicken in South Western Ethiopia

Authors: Abdela Bulbula

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

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

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17207 A Multidimensional Genetic Algorithm Applicable for Our VRP Variant Dealing with the Problems of Infrastructure Defaults SVRDP-CMTW: “Safety Vehicle Routing Diagnosis Problem with Control and Modified Time Windows”

Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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17206 Serum MicroRNA and Inflammatory Mediators: Diagnostic Biomarkers for Endometritis in Arabian Mares

Authors: Sally Ibrahim, Mohamed Hedia, Mohamed Taqi, Mohamed Derbala, Karima Mahmoud, Youssef Ahmed, Sayed Ismail, Mohamed El-Belely

Abstract:

The identification and quantification of serum microRNA (miRNA) from mares with endometritis might serve as useful and implementable clinical biomarkers for the early diagnosis of endometiritis. Aims of the current study were (I) to study the expression pattern of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205, and (II) to determine the levels of interleukin 6 (IL-6), prostaglandins (PGF₂α and PGE₂), in the serum of Arabian mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares (4-14 years old). Mares were divided into 48 sub-fertile mares suspected of endometritis and 32 fertile at stud farms. The criteria for mares to be enrolled in the endometritis group were that they had been bred three or more times unsuccessfully in the breeding season or had a history of more than one year of reproductive failure. In addition, two or more of the following criteria on a checklist were present: abnormal clinical findings, transrectal ultrasonographic uterine examination showed abnormal fluid in the uterus (echogenic or ≥2 cm in diameter), positive endometrial cytology; and bacterial and/or fungal growth. Serum samples were collected for measuring IL-6, PGF₂α, and PGE₂ concentrations, as well as serum miRNA isolation and quantitative real-time PCR. Serum concentrations of IL-6, PGE₂, and PGF₂α were higher (P ≤ 0.001) in mares with endometritis compared to the control healthy ones. The expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 increased (P≤0.001) in mares with endometritis compared to the control ones. To the best of our knowledge, this is the first study that revealed that serum miRNA and serum inflammatory mediators (IL-6, PGE₂, and PGF₂α) could be used as non-invasive gold standard biomarkers, and therefore might be served as an important additional diagnostic tool for endometritis in Arabian mares. Moreover, estimation of the serum concentrations of serum miRNA, IL-6, PGE₂, and PGF₂α is a promising recommended tool during the breeding soundness examination in mares.

Keywords: Arabian Mares, endometritis, inflammatory mediators, serum miRNA

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17205 Polymer Patterning by Dip Pen Nanolithography

Authors: Ayse Cagil Kandemir, Derya Erdem, Markus Niederberger, Ralph Spolenak

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Dip Pen nanolithography (DPN), which is a tip based method, serves a novel approach to produce nano and micro-scaled patterns due to its high resolution and pattern flexibility. It is introduced as a new constructive scanning probe lithography (SPL) technique. DPN delivers materials in the form of an ink by using the tip of a cantilever as pen and substrate as paper in order to form surface architectures. First studies rely on delivery of small organic molecules on gold substrate in ambient conditions. As time passes different inks such as; polymers, colloidal particles, oligonucleotides, metallic salts were examined on a variety of surfaces. Discovery of DPN also enabled patterning with multiple inks by using multiple cantilevers for the first time in SPL history. Specifically, polymer inks, which constitute a flexible matrix for various materials, can have a potential in MEMS, NEMS and drug delivery applications. In our study, it is aimed to construct polymer patterns using DPN by studying wetting behavior of polymer on semiconductor, metal and polymer surfaces. The optimum viscosity range of polymer and effect of environmental conditions such as humidity and temperature are examined. It is observed that there is an inverse relation with ink viscosity and depletion time. This study also yields the optimal writing conditions to produce consistent patterns with DPN. It is shown that written dot sizes increase with dwell time, indicating that the examined writing conditions yield repeatable patterns.

Keywords: dip pen nanolithography, polymer, surface patterning, surface science

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17204 Kalman Filter for Bilinear Systems with Application

Authors: Abdullah E. Al-Mazrooei

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In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.

Keywords: bilinear systems, state space model, Kalman filter, application, models

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17203 Relationship of Indoor and Outdoor Levels of Black Carbon in an Urban Environment

Authors: Daria Pashneva, Julija Pauraite, Agne Minderyte, Vadimas Dudoitis, Lina Davuliene, Kristina Plauskaite, Inga Garbariene, Steigvile Bycenkiene

Abstract:

Black carbon (BC) has received particular attention around the world, not only for its impact on regional and global climate change but also for its impact on air quality and public health. In order to study the relationship between indoor and outdoor BC concentrations, studies were carried out in Vilnius, Lithuania. The studies are aimed at determining the relationship of concentrations, identifying dependencies during the day and week with a further opportunity to analyze the key factors affecting the indoor concentration of BC. In this context, indoor and outdoor continuous real-time measurements of optical BC-related light absorption by aerosol particles were carried out during the cold season (from October to December 2020). The measurement venue was an office located in an urban background environment. Equivalent black carbon (eBC) mass concentration was measured by an Aethalometer (Magee Scientific, model AE-31). The optical transmission of carbonaceous aerosol particles was measured sequentially at seven wavelengths (λ= 370, 470, 520, 590, 660, 880, and 950 nm), where the eBC mass concentration was derived from the light absorption coefficient (σab) at 880 nm wavelength. The diurnal indoor eBC mass concentration was found to vary in the range from 0.02 to 0.08 µgm⁻³, while the outdoor eBC mass concentration - from 0.34 to 0.99 µgm⁻³. Diurnal variations of eBC mass concentration outdoor vs. indoor showed an increased contribution during 10:00 and 12:00 AM (GMT+2), with the highest indoor eBC mass concentration of 0.14µgm⁻³. An indoor/outdoor eBC ratio (I/O) was below one throughout the entire measurement period. The weekend levels of eBC mass concentration were lower than in weekdays for indoor and outdoor for 33% and 28% respectively. Hourly mean mass concentrations of eBC for weekdays and weekends show diurnal cycles, which could be explained by the periodicity of traffic intensity and heating activities. The results show a moderate influence of outdoor eBC emissions on the indoor eBC level.

Keywords: black carbon, climate change, indoor air quality, I/O ratio

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17202 Collation between the Architecture of the Churches and Housing from Antiquity to the Present Day

Authors: Shaloom Mbambu Kabeya, Léonard Kabeya Mukeba

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Churches, cathedrals and castles beaten from antiquity to modern times were relevant from that time to the present day, and preserved as cultural heritage. Our predecessors as François 1er1, Michelangelo2, and Giotto3 left us traces. Gustave Eiffel4, Hector Guimard5 did not decrease their time to show modernization (evolution) in architecture. Plagiarism is a brake on architectural development, construction works of spirits is necessary architecture. This work explains the relationship between ancient and modern architecture. It also shows the power of mathematics in modern architecture.

Keywords: architectural modernization, heritage, mathematical architecture, materials

Procedia PDF Downloads 599