Search results for: real time expression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21813

Search results for: real time expression

21063 Expression of Gro-El under Phloem-Specific Promoter Protects Transgenic Plants against Diverse Begomovirus-Beta Satellite Complex

Authors: Muhammad Yousaf Ali, Shahid Mansoor, Javeria Qazi, Imran Amin, Musarrat Shaheen

Abstract:

Cotton leaf curl disease (CLCuD) is the major threat to the cotton crop and is transmitted by whitefly (Bemisia tabaci). Since multiple begomoviruses and associated satellites are involved in CLCuD, approaches based on the concept of broad-spectrum resistance are essential for effective disease control. Gro-El and G5 are two proteins from whitefly endosymbiont and M13 bacteriophage origin, respectively. Gro-El encapsulates the virus particle when it enters the whitefly and protects the virus from the immune system of the whitefly as well as prevents viral expression in it. This characteristic of Gro-El can be exploited to get resistance against viruses if expressed in plants. G5 is a single-stranded DNA binding protein, expression of which in transgenic plants will stop viral expression on its binding with ssDNA. The use of tissue-specific promoters is more efficient than constitutive promoters. Transgenics of Nicotiana benthamiana for Gro-El under constitutive promoter and Gro-El under phloem specific promoter were made. In comparison to non-transgenic plants, transgenic plants with Gro-El under NSP promoter showed promising results when challenged against cotton leaf curl Multan virus (CLCuMuV) along with cotton leaf curl Multan beta satellite (CLCuMB), cotton leaf curl Khokhran virus (CLCuKoV) along with cotton leaf curl Multan beta satellite (CLCuMB) and Pedilenthus leaf curl virus (PedLCV) along with Tobacco leaf curl beta satellite (TbLCB).

Keywords: cotton leaf curl disease, whitefly, endosymbionts, transgenic, resistance

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21062 Data Collection Techniques for Robotics to Identify the Facial Expressions of Traumatic Brain Injured Patients

Authors: Chaudhary Muhammad Aqdus Ilyas, Matthias Rehm, Kamal Nasrollahi, Thomas B. Moeslund

Abstract:

This paper presents the investigation of data collection procedures, associated with robots when placed with traumatic brain injured (TBI) patients for rehabilitation purposes through facial expression and mood analysis. Rehabilitation after TBI is very crucial due to nature of injury and variation in recovery time. It is advantageous to analyze these emotional signals in a contactless manner, due to the non-supportive behavior of patients, limited muscle movements and increase in negative emotional expressions. This work aims at the development of framework where robots can recognize TBI emotions through facial expressions to perform rehabilitation tasks by physical, cognitive or interactive activities. The result of these studies shows that with customized data collection strategies, proposed framework identify facial and emotional expressions more accurately that can be utilized in enhancing recovery treatment and social interaction in robotic context.

Keywords: computer vision, convolution neural network- long short term memory network (CNN-LSTM), facial expression and mood recognition, multimodal (RGB-thermal) analysis, rehabilitation, robots, traumatic brain injured patients

Procedia PDF Downloads 134
21061 Synergistic Cytotoxicity of Cisplatin and Taxol in Overcoming Taxol Resistance through the Inhibition of LDHA in Oral Squamous Cell Carcinoma

Authors: Lin Feng, Ling-Ling E., Hong-Chen Liu

Abstract:

The development of chemoresistance in patients represents a major challenge in cancer treatment. Lactate dehydrogenase‑A (LDHA) is one of the principle isoforms of LDH that is expressed in breast tissue, controlling the conversion of pyruvate to lactate and also playing a significant role in the metabolism of glucose. The aim of this study was to identify whether LDHA was involved in oral cancer cell resistance to Taxol and whether the downregulation of LDHA, as a result of cisplatin treatment, may overcome Taxol resistance in human oral squamous cells. The OECM‑1 oral epidermal carcinoma cell line was used, which has been widely used as a model of oral cancer in previous studies. The role of LDHA in Taxol and cisplatin resistance was investigated and the synergistic cytotoxicity of cisplatin and/or Taxol in oral squamous cells was analyzed. Cell viability was analyzed by MTT assay, LDHA expression was analyzed by western blot analysis and siRNA transfection was performed to knock down LDHA expression. The present study results showed that decreased levels of LDHA were responsible for the resistance of oral cancer cells to cisplatin (CDDP). CDDP treatments downregulated LDHA expression and lower levels of LDHA were detected in the CDDP‑resistant oral cancer cells compared with the CDDP‑sensitive cells. By contrast, the Taxol‑resistant cancer cells showed elevated LDHA expression levels. In addition, small interfering RNA‑knockdown of LDHA sensitized the cells to Taxol but desensitized them to CDDP treatment while exogenous expression of LDHA sensitized the cells to CDDP, but desensitized them to Taxol. The present study also revealed the synergistic cytotoxicity of CDDP and Taxol for killing oral cancer cells through the inhibition of LDHA. This study highlights LDHA as a novel therapeutic target for overcoming Taxol resistance in oral cancer patients using the combined treatments of Taxol and CDDP.

Keywords: cisplatin, Taxol, carcinoma, oral squamous cells

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21060 Digimesh Wireless Sensor Network-Based Real-Time Monitoring of ECG Signal

Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

Abstract:

DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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21059 Applying Polyphonic Dialogue as an Approach to Thematically Analyse the Development of Online Identities in Social Media

Authors: Maryam Khosronejad

Abstract:

In social media, differences between individuals become salient as they become a member of different groups with particular social and cultural practices and get engaged in various conversations. The influence of the presence of social media on the promotion of self-expression and polyphonic dialogue is an understudied area and is, therefore, the focus of this paper. This exploration aims to understand the formation of online identities as an ongoing process of orchestrating polyphonic dialogue and responding to available positions. In addition, applying the thematic analysis, it gives examples of how discursive transactions facilitate this process. The implications for the use of social media in education will be discussed based on the findings.

Keywords: online identity, polyphonic dialogue, self expression, social media

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21058 SLAMF5 Regulates Myeloid Cells Activation in the Eae Model

Authors: Laura Bellassen, Idit Shachar

Abstract:

Multiple sclerosis (MS) is a chronic neurological disorder characterized by demyelination of the central nervous system (CNS), leading to a wide range of physical and cognitive impairments. Myeloid cells in the CNS, such microglia and border associated macrophage cells, participate in the neuroinflammation in MS. Activation of those cells in MS contributes to the inflammatory response in the CNS and recruitment of immune cells in the this compartment. SLAMF5 is a cell surface receptor that functions as a homophilic adhesion molecule, whose signaling can activate or inhibit leukocyte function. In the current study we followed the expression and function of SLAMF5 in myeloid cells in the CNS and in the periphery in the murine model for MS, the experimental autoimmune encephalomyelitis model (EAE). Our results show that SLAMF5 deficiency or blocking decreases the expression of activation molecules and costimulatory molecules such as MHCII and CD80, resulting in delayed onset and reduced progression of the disease. Moreover, blocking SLAMF5 in peripheral monocytes derived from MS patients and iPSC-derived microglia cells, controls the expression of HLA-DR and CD80. Thus, SLAMF5 is a regulator of myeloid cells function and can serve as a therapeutic target in autoimmune disorders as Multiple Sclerosis.

Keywords: multiple sclerosis, EAE model, myeloid cells, new antibody, neuroimmunology

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21057 A Posteriori Trading-Inspired Model-Free Time Series Segmentation

Authors: Plessen Mogens Graf

Abstract:

Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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21056 Virtual Reality and Other Real-Time Visualization Technologies for Architecture Energy Certifications

Authors: Román Rodríguez Echegoyen, Fernando Carlos López Hernández, José Manuel López Ujaque

Abstract:

Interactive management of energy certification ratings has remained on the sidelines of the evolution of virtual reality (VR) despite related advances in architecture in other areas such as BIM and real-time working programs. This research studies to what extent VR software can help the stakeholders to better understand energy efficiency parameters in order to obtain reliable ratings assigned to the parts of the building. To evaluate this hypothesis, the methodology has included the construction of a software prototype. Current energy certification systems do not follow an intuitive data entry system; neither do they provide a simple or visual verification of the technical values included in the certification by manufacturers or other users. This software, by means of real-time visualization and a graphical user interface, proposes different improvements to the current energy certification systems that ease the understanding of how the certification parameters work in a building. Furthermore, the difficulty of using current interfaces, which are not friendly or intuitive for the user, means that untrained users usually get a poor idea of the grounds for certification and how the program works. In addition, the proposed software allows users to add further information, such as financial and CO₂ savings, energy efficiency, and an explanatory analysis of results for the least efficient areas of the building through a new visual mode. The software also helps the user to evaluate whether or not an investment to improve the materials of an installation is worth the cost of the different energy certification parameters. The evaluated prototype (named VEE-IS) shows promising results when it comes to representing in a more intuitive and simple manner the energy rating of the different elements of the building. Users can also personalize all the inputs necessary to create a correct certification, such as floor materials, walls, installations, or other important parameters. Working in real-time through VR allows for efficiently comparing, analyzing, and improving the rated elements, as well as the parameters that we must enter to calculate the final certification. The prototype also allows for visualizing the building in efficiency mode, which lets us move over the building to analyze thermal bridges or other energy efficiency data. This research also finds that the visual representation of energy efficiency certifications makes it easy for the stakeholders to examine improvements progressively, which adds value to the different phases of design and sale.

Keywords: energetic certification, virtual reality, augmented reality, sustainability

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21055 AI-Based Information System for Hygiene and Safety Management of Shared Kitchens

Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

Abstract:

The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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21054 Effects of Propolis on Immunomodulatory and Antibody Production in Broilers

Authors: Yu-Hsiang Yu

Abstract:

The immunomodulatory effect of propolis has been widely investigated in the past decade. However, the beneficial effects in broilers are still poorly understood. The aim of this study was to evaluate the effect of propolis added in drinking water on immunomodulatory and antibody production in broiler. Total of 48 chicks were randomly allocated into four groups with 12 broilers per group. All birds were intranasal inoculated with Newcastle Disease vaccine at 4 and 14 days old of age. Four groups, including control without any treatment, groups of A, B and F [3 days of anterior (A), 3 days of posterior (P) and 6 days of full (F)] were supplied the propolis at 300 ppm in drinking water when vaccination was performed, respectively. Our results showed that no significant difference was found in growth performance, antibody production and immune organ index among groups. However, propolis treatments in broilers significantly reduced IL-4 expression in spleen at 14 days-old of age and bursa at 28 days-old of age compared with control group. The expression of IFN-gamma in spleen (A, P and F group) and bursal (F group) were elevated compared with control group at 28 days-old of age. In conclusion, our results indicated that propolis-treated birds could bear the capability for immunomodulatory effects by change Th1 subset cytokine expression in vaccination.

Keywords: propolis, broiler, immunomodulatory, vaccination

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21053 Aminopeptidase P (DAP) Expression Pattern in Drosophila Melanogaster

Authors: Suneeta Gireesh Panicker

Abstract:

Aim: Aminopeptidase P (APP) is an enzyme that has specificity for proline, can specifically cleave Xaa-Proline peptides and is a metallo-aminopeptidase. The bonds nearby to the imino acid proline are tough to cleave by many peptidases, but APP can specifically break peptide bonds engaged with proline. Membrane-bound form and a cytosolic form are the two forms in which this enzyme exists. The exact physiological function of APP remains unclear and hence the present work attempts to determine it. Methods: In the present study, the expression pattern of cytosolic Aminopeptidase P (DAP) was determined in all the embryonic stages and larval stages of wild-type Drosophila by using polyclonal monospecific antibodies. To show the presence of DAP RNA in embryonic and larval stages, RNA in situ hybridization was performed. DAP promoter-LacZ fusion reporter gene vector was used to construct transgenic embryos to study the regulation pattern of DAP. To study the DAP expression profile, a transgenic fly consisting of a DAP promoter with β-gal and GFP reporter genes in front of it was constructed. Results: DAP protein expression was observed in neuroectodermal cells, posterior midgut primordium, proctodeum, ventral neuroblast and primordial stomatogastric nervous system. It was observed in the ventral cord and midgut in stage 12. The completely developed embryos showed the intense occurrence of it in the ventral cord and gut region. The eye-antennal disc, wing disc and leg disc also showed the presence of DAP protein. LacZ expression in transgenic embryos also showed the same pattern. Conclusion: Similar to various known multiple-functional proteins, DAP could be one with different functions at different stages and in different cells. Data presented here designates DAP functions in the early embryonic and imaginal dics differentiation and development, suggesting that it may be required for the metabolism of proteins like neuropeptides and tachykinins.

Keywords: aminopeptidase P, in situ hybridization, transgenic fly, embryonic stages

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21052 Induction of Callus and Expression of Compounds in Capsicum Frutescens Supplemented with of 2, 4-D

Authors: Jamilah Syafawati Yaacob, Muhammad Aiman Ramli

Abstract:

Cili padi or Capsicum frutescens is one of capsicum species from nightshade family, Solanaceae. It is famous in Malaysia and is widely used as a food ingredient. Capsicum frutescens also possess vast medicinal properties. The objectives of this study are to determine the most optimum 2,4-D hormone concentration for callus induction from stem explants C. frutescens and the effects of different 2,4-D concentrations on expression of compounds from C. frutescens. Seeds were cultured on MS media without hormones (MS basal media) to yield aseptic seedlings of this species, which were then used to supply explant source for subsequent tissue culture experiments. Stem explants were excised from aseptic seedlings and cultured on MS media supplemented with various concentrations (0.1, 0.3 and 0.5 mg/L) of 2,4-D to induce formation of callus. Fresh weight, dry weight and callus growth percentage in all samples were recorded. The highest mean of dry weight was observed in MS media supplemented with 0.5 mg/L 2,4-D, where 0.4499 ± 0.106 g of callus was produced. The highest percentage of callus growth (16.4%) was also observed in cultures supplemented with 0.5 mg/L 2,4-D. The callus samples were also subjected to HPLC-MS to evaluate the effect of hormone concentration on expression of bio active compounds in different samples. Results showed that caffeoylferuloylquinic acids were present in all samples, but was most abundant in callus cells supplemented with 0.3 & 0.5 mg/L 2,4-D. Interestingly, there was an unknown compound observed to be highly expressed in callus cells supplemented with 0.1 mg/L 2,4-D, but its presence was less significant in callus cells supplemented with 0.3 and 0.5 mg/L 2,4-D. Furthermore, there was also a compound identified as octadecadienoic acid, which was uniquely expressed in callus supplemented with 0.5 mg/L 2,4-D, but absent in callus cells supplemented with 0.1 and 0.3 mg/L 2,4-D. The results obtained in this study indicated that plant growth regulators played a role in expression of secondary metabolites in plants. The increase or decrease of these growth regulators may have triggered a change in the secondary metabolite biosynthesis pathways, thus causing differential expression of compounds in this plant.

Keywords: callus, in vitro, secondary metabolite, 2, 4-Dichlorophenoxyacetic acid

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21051 Elucidation of the Sequential Transcriptional Activity in Escherichia coli Using Time-Series RNA-Seq Data

Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

Abstract:

Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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21050 Combined Treatment of PARP-1 Inhibitor and Carbon Ion or Gamma Exposure Reduces the Metastatic Potential in Cultured Human Cells

Authors: Priyanka Chowdhury, Asitikantha Sarma, Utpal Ghosh

Abstract:

Hadron therapy using high Linear Energy Transfer (LET) ion beam is producing promising clinical results worldwide. The major advantages are its ability to kill radio-resistant tumor and its anti-metastatic activity. Poly(ADP-ribose) polymerase-1 (PARP-1) inhibitors have been widely used as radiosensitizer, but its role in metastasis is unknown. The purpose of our study was to investigate the effect of PARP-1 depletion in combination with either Carbon Ion Beam (CIB) or gamma irradiation on metastatic potential of cultured cancerous cells. A549 cells were irradiated with CIB (0-4Gy) or gamma (0, 2, 4, 6 and 10 Gy) with and without PARP-1 inhibition. The metastatic potential of the cells was determined by cell migratory assay, expression, and activity of MMP-2 and MMP-9, expression of Cadherin, Fibronectin, and Vimentin. CIB exposure reduced migratory property and activity of MMP-2 and MMP-9 significantly. CIB with PARP-1 inhibition reduced cell migration and Matrix Metalloproteinase (MMPs) activity in a synergistic manner. Expression of MMPs was also down-regulated in CIB and combined treatment. On the contrary, MMP- 2 and MMP-9 activity was significantly increased in gamma irradiated cells but decreased upon combined treatment of gamma and PARP-1 inhibitor. MMPs expression and migration was reduced when gamma irradiation was combined with PARP-1 inhibition. Thus, our study clearly demonstrates that PARP-1 inhibition in combination with either high or low LET can significantly suppress metastatic potential in cancer cells and thereby can be a promising tool in controlling metastatic cancers.

Keywords: high LET, low LET, matrix metalloproteinase (MMP), PARP-1

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21049 Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis

Authors: Maryam Alimardani, Kazuo Hiraki

Abstract:

This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)

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21048 Accidental Compartment Fire Dynamics: Experiment, Computational Fluid Dynamics Weakness and Expert Interview Analysis

Authors: Timothy Onyenobi

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Accidental fires and its dynamic as it relates to building compartmentation and the impact of the compartment morphology, is still an on-going area of study; especially with the use of computational fluid dynamics (CFD) modeling methods. With better knowledge on this subject come better solution recommendations by fire engineers. Interviews were carried out for this study where it was identified that the response perspectives to accidental fire were different with the fire engineer providing qualitative data which is based on “what is expected in real fires” and the fire fighters provided information on “what actually obtains in real fires”. This further led to a study and analysis of two real and comprehensively instrumented fire experiments: the Open Plan Office Project by National Institute of Standard and Technology (NIST) USA (to study time to flashover) and the TF2000 project by the Building Research Establishment (BRE) UK (to test for conformity with Building Regulation requirements). The findings from the analysis of the experiments revealed the relative yet critical weakness of fire prediction using a CFD model (usually used by fire engineers) as well as explained the differences in response perspectives of the fire engineers and firefighters from the interview analysis.

Keywords: CFD, compartment fire, experiment, fire fighters, fire engineers

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21047 Electromagnetic Simulation Based on Drift and Diffusion Currents for Real-Time Systems

Authors: Alexander Norbach

Abstract:

The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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21046 Emotion Recognition with Occlusions Based on Facial Expression Reconstruction and Weber Local Descriptor

Authors: Jadisha Cornejo, Helio Pedrini

Abstract:

Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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21045 Optimizing Logistics for Courier Organizations with Considerations of Congestions and Pickups: A Courier Delivery System in Amman as Case Study

Authors: Nader A. Al Theeb, Zaid Abu Manneh, Ibrahim Al-Qadi

Abstract:

Traveling salesman problem (TSP) is a combinatorial integer optimization problem that asks "What is the optimal route for a vehicle to traverse in order to deliver requests to a given set of customers?”. It is widely used by the package carrier companies’ distribution centers. The main goal of applying the TSP in courier organizations is to minimize the time that it takes for the courier in each trip to deliver or pick up the shipments during a day. In this article, an optimization model is constructed to create a new TSP variant to optimize the routing in a courier organization with a consideration of congestion in Amman, the capital of Jordan. Real data were collected by different methods and analyzed. Then, concert technology - CPLEX was used to solve the proposed model for some random generated data instances and for the real collected data. At the end, results have shown a great improvement in time compared with the current trip times, and an economic study was conducted afterwards to figure out the impact of using such models.

Keywords: travel salesman problem, congestions, pick-up, integer programming, package carriers, service engineering

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21044 Circadian Expression of MicroRNAs in Colon and Its Changes during Colorectal Tumorigenesis

Authors: Katerina Balounova, Jiri Pacha, Peter Ergang, Martin Vodicka, Pavlina Kvapilova

Abstract:

MicroRNAs are small non-coding RNAs involved in a wide range of physiological processes. Post-transcriptional regulation of gene expression by microRNAs gives the organism a further level of control of the gene-expression program and the disruption of this microRNA regulatory mechanism seems to increase the risk of various pathophysiological conditions including tumorigenesis. To the present day, microRNAs were shown to participate in the mayor signalization pathways leading to tumorigenesis, including proliferation, cell cycle, apoptosis and metastasis formation. In addition, microRNAs have been found to play important roles in the generation and maintenance of circadian clock. These clocks generate circadian rhythms, which participate in a number of regulatory pathways. Disruption of the circadian signals seems to be associated with the development and the progression of tumours including colorectal cancer. We investigated therefore whether the diurnal profiles of miRNAs linked to tumorigenesis and regulation of circadian clock are changed during tumorigenesis. Based on published data we chose 10 microRNAs linked to tumorigenesis or circadian clock (let-7b-5p, miR 1 3p, miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p, miR 29a 3p, miR 34a 5p and miR 93 5p) and compared their 24-hr expression profiles in healthy and in chemically induces primary colorectal tumours of 52week-old mice. Using RT-qPCR we proved circadian rhythmicity in let-7b-5p, miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p, miR 29a 3p and miR 93 5p in healthy colon but not in tumours. The acrophases of miR 106b 5p, miR 141 3p, miR 191 5p, miR 20a 5p, miR 25 3p and miR 93 5p were reached around CT 24, the acrophases of let-7b-5p and miR-29a-3p were slightly shifted and reached around CT 21. In summary, our results show that circadian regulation of some colonic microRNAs is greatly affected by neoplastic transformation.

Keywords: circadian rhythm, colon, colorectal cancer, microRNA, tumorigenesis

Procedia PDF Downloads 151
21043 Road Condition Monitoring Using Built-in Vehicle Technology Data, Drones, and Deep Learning

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

Abstract:

Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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21042 Toxicological Effects of Atmospheric Fine Particulate Matter on Human Bronchial Epithelial Cells: Metabolic Activation, Genotoxicity and Epigenetic Modifications

Authors: M. Borgie, Z. Dagher, F. Ledoux, A. Verdin, F. Cazier, H. Greige, P. Shirali, D. Courcot

Abstract:

In October 2013, the International Agency for Research on Cancer (IARC) classified outdoor air pollution and fine particulate matter (PM2.5) as carcinogenic to humans. Despite the clearly relationship established by epidemiological studies between PM exposure and the onset of respiratory and cardiovascular diseases, uncertainties remain about the physiopathological mechanisms responsible for these diseases. The aim of this work was to evaluate the toxicological effects of two samples of atmospheric PM2.5 collected at urban and rural sites on human bronchial epithelial cells, BEAS-2B, especially to investigate the metabolic activation of organic compounds, the alteration of epigenetic mechanisms (i.e. microRNAs genes expression), the phosphorylation of H2AX and the telomerase activity. Our results showed a significant increase in CYP1A1, CYP1B1, and AhRR genes expression, miR-21 gene expression, H2AX phosphorylation and telomerase activity in BEAS-2B cells after their exposure to PM2.5, both in a dose and site-dependent manner. These results showed that PM2.5, especially urban PM, are able to induce the expression of metabolizing enzymes which can provide metabolic biotransformation of organic compounds into more toxic and carcinogenic metabolites, and to induce the expression of the oncomiR miR-21 which promotes cell growth and enhances tumor invasion and metastasis in lung cancer. In addition, our results have highlighted the role of PM2.5 in the activation of telomerase, which can maintain the telomeres length and subsequently preventing cell death, and have also demonstrated the ability of PM2.5 to induce DNA breaks and thus to increase the risk of mutations or chromosomal translocations that lead to genomic instability. All these factors may contribute to cell abnormalities, and thus the development of cancer.

Keywords: BEAS-2B cells, carcinogenesis, epigenetic alterations and genotoxicity, PM2.5

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21041 Qualitative Study of Pre-Service Teachers' Imagined Professional World vs. Real Experiences of In-Service Teachers

Authors: Masood Monjezi

Abstract:

The English teachers’ pedagogical identity construction is the way teachers go through the process of becoming teachers and how they maintain their teaching selves. The pedagogical identity of teachers is influenced by several factors within the individual and the society. The purpose of this study was to compare the imagined social world of the pre-service teachers with the real experiences the in-service teachers had in the context of Iran to see how prepared the pre-service teachers are with a view to their identity being. This study used a qualitative approach to collection and analysis of the data. Structured and semi-structured interviews, focus groups and process logs were used to collect the data. Then, using open coding, the data were analyzed. The findings showed that the imagined world of the pre-service teachers partly corresponded with the real world experiences of the in-service teachers leaving the pre-service teachers unprepared for their real world teaching profession. The findings suggest that the current approaches to English teacher training are in need of modification to better prepare the pre-service teachers for the future that expects them.

Keywords: imagined professional world, in-service teachers, pre-service teachers, real experiences, community of practice, identity

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21040 E4D-MP: Time-Lapse Multiphysics Simulation and Joint Inversion Toolset for Large-Scale Subsurface Imaging

Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

Abstract:

A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

Procedia PDF Downloads 139
21039 Optical Flow Based System for Cross Traffic Alert

Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

Abstract:

This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

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21038 Contribution of mTOR to Oxidative/Nitrosative Stress via NADPH Oxidase System Activation in Zymosan-Induced Systemic Inflammation in Rats

Authors: Seyhan Sahan-Firat, Meryem Temiz-Resitoglu, Demet Sinem Guden, Sefika Pinar Kucukkavruk, Bahar Tunctan, Ayse Nihal Sari, Zumrut Kocak

Abstract:

We hypothesized that mTOR inhibition may prevent the multiple organ failures following severe multiple tissue injury associated with increased NADPH oxidase system activity occur in zymosan-induced systemic inflammation. Therefore, we investigated the role of mTOR in oxidative/nitrosative stress associated with increase in NADPH oxidase activity in zymosan-induced systemic inflammation model in rats. Male Wistar rats received saline (4 ml/kg, i.p.) and zymosan (500 mg/kg, i.p.) at time 0. Saline, or zymosan-treated rats were given rapamycin (1 mg/kg, i.p.) 1 h after saline or zymosan injections. Rats were sacrified 4 h after zymosan challenge and kidney, heart, thoracic aorta, and superior mesenteric artery were collected. NADPH oxidase activity, p22phox, gp91phox, and p47phox protein expression and nitrotyrosine levels were measured in tissue samples. Zymosan administration caused an increase in NADPH oxidase activity, p22phox, gp91phox, and p47phox protein expression and nitrotyrosine levels in kidney, heart, thoracic aorta, and superior mesenteric artery. These changes caused by zymosan reversed by rapamycin, a selective mTOR inhibitor. Rapamycin alone had no effect on the parameters measured. Our results demonstrated that zymosan-induced oxidative/nitrosative stress presumably due to enhanced activity of NADPH oxidase, expression of p22phox, gp91phox, and p47phox and production of peroxynitrite were mediated by mTOR. [This work was financially supported by Research Foundation of Mersin University (2016-2-AP3-1900)].

Keywords: oxidative stress, mTOR, nitrosative stress, zymosan

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21037 Transcriptomic Analyses of Kappaphycus alvarezii under Different Wavelengths of Light

Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

Abstract:

Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

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21036 Microarray Data Visualization and Preprocessing Using R and Bioconductor

Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

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Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

Procedia PDF Downloads 460
21035 Project Progress Prediction in Software Devlopment Integrating Time Prediction Algorithms and Large Language Modeling

Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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21034 Augmented Reality in Teaching Children with Autism

Authors: Azadeh Afrasyabi, Ali Khaleghi, Aliakbar Alijarahi

Abstract:

Training at an early age is so important, because of tremendous changes in adolescence, including the formation of character, physical changes and other factors. One of the most sensitive sectors in this field is the children with a disability and are somehow special children who have trouble in communicating with their environment. One of the emerging technologies in the field of education that can be effectively profitable called augmented reality, where the combination of real world and virtual images in real time produces new concepts that can facilitate learning. The purpose of this paper is to propose an effective training method for special and disabled children based on augmented reality. Of course, in particular, the efficiency of augmented reality in teaching children with autism will consider, also examine the various aspect of this disease and different learning methods in this area.

Keywords: technology in education, augmented reality, special education, teaching methods

Procedia PDF Downloads 354