Search results for: asset specificity
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 997

Search results for: asset specificity

547 Evaluation of Antioxidant Activities of Rice Paddy Herb (Limnophila aromatica (Lam.) Merr.)

Authors: Rutanachai Thaipratum

Abstract:

Free radicals are atoms or molecules with unpaired electrons. Many diseases are caused by free radicals. Normally, free radical formation is controlled naturally by various beneficial compounds known as antioxidants. Several analytical methods have been used for qualitative and quantitative determination of antioxidants, and each has its own specificity. This project aimed to evaluate antioxidant activity of ethanolic and aqueous extracts from the rice paddy herb (Limnophila aromatica (Lam.) Merr.) measured by DPPH and Hydroxyl radical scavenging method. The results showed that averaged antioxidant activity measured in ethanolic extract (µmol Ascorbic acid equivalent/g fresh mass) were 67.09± 4.99 and 15.55±4.82 as determined by DPPH and Hydroxyl radical scavenging activity assays, respectively. Averaged antioxidant activity measured in aqueous extract (µmol Ascorbic acid equivalent/g fresh mass) were 21.08±1.25 and 10.14±3.94 as determined by DPPH and Hydroxyl radical scavenging activity assays respectively.

Keywords: free radical, antioxidant, rice paddy herb, Limnophila aromatica (Lam.) Merr.

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546 Maturity Transformation Risk Factors in Islamic Banking: An Implication of Basel III Liquidity Regulations

Authors: Haroon Mahmood, Christopher Gan, Cuong Nguyen

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Maturity transformation risk is highlighted as one of the major causes of recent global financial crisis. Basel III has proposed new liquidity regulations for transformation function of banks and hence to monitor this risk. Specifically, net stable funding ratio (NSFR) is introduced to enhance medium- and long-term resilience against liquidity shocks. Islamic banking is widely accepted in many parts of the world and contributes to a significant portion of the financial sector in many countries. Using a dataset of 68 fully fledged Islamic banks from 11 different countries, over a period from 2005 – 2014, this study has attempted to analyze various factors that may significantly affect the maturity transformation risk in these banks. We utilize 2-step system GMM estimation technique on unbalanced panel and find bank capital, credit risk, financing, size and market power are most significant among the bank specific factors. Also, gross domestic product and inflation are the significant macro-economic factors influencing this risk. However, bank profitability, asset efficiency, and income diversity are found insignificant in determining the maturity transformation risk in Islamic banking model.

Keywords: Basel III, Islamic banking, maturity transformation risk, net stable funding ratio

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545 An Effective and Efficient Web Platform for Monitoring, Control, and Management of Drones Supported by a Microservices Approach

Authors: Jorge R. Santos, Pedro Sebastiao

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In recent years there has been a great growth in the use of drones, being used in several areas such as security, agriculture, or research. The existence of some systems that allow the remote control of drones is a reality; however, these systems are quite simple and directed to specific functionality. This paper proposes the development of a web platform made in Vue.js and Node.js to control, manage, and monitor drones in real time. Using a microservice architecture, the proposed project will be able to integrate algorithms that allow the optimization of processes. Communication with remote devices is suggested via HTTP through 3G, 4G, and 5G networks and can be done in real time or by scheduling routes. This paper addresses the case of forest fires as one of the services that could be included in a system similar to the one presented. The results obtained with the elaboration of this project were a success. The communication between the web platform and drones allowed its remote control and monitoring. The incorporation of the fire detection algorithm in the platform proved possible a real time analysis of the images captured by the drone without human intervention. The proposed system has proved to be an asset to the use of drones in fire detection. The architecture of the application developed allows other algorithms to be implemented, obtaining a more complex application with clear expansion.

Keywords: drone control, microservices, node.js, unmanned aerial vehicles, vue.js

Procedia PDF Downloads 128
544 Logistics Process of Pineapple’s Leaves Product in Prachuapkhirikhan Province

Authors: Atcharawan Phenwansuk

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The product design is important to the development of SME towards the global, because it made to the quality product to react the needs of consumers and could reduces cost in the production, making it more profitable. As a results, the business are competition advantage for more marketing. It also enhance image of product and firms to build its own brand products to be acceptable. The product was designed should be shape, size, colorful, and direct of target consumers. This is method to add value products to get popular and effective, because the beauty is first satisfaction which come from main shape and color of the design product, but the product was designed need to hold data and law combination of shape and color between artistic theory and satisfaction of consumers together. The design must consider the safety of life and asset of consumers the most important. From to use of designed products should be to consider the cost savings, convenient distance, transportation, routes (land, water or air) of living space on transport (capacity, volume, width, length of the car, truck and container, etc). The packaging must be can to prevent not damage of the products. If products is more large , maybe to design new packaging, which can easily disassembled for make smaller package such as designing the assembly. Products must be packed in the container for size standard for save costs, as well as the buyer can make transport and assembly of products to fit easily on your own.

Keywords: logistics process , pineapple’s leaves product, product design, satisfaction of consumers

Procedia PDF Downloads 389
543 Effectiveness of Public Speaking Extracurricular in Gontor in Raising Leaders of the Advanced Global World's Needs

Authors: Ummi Sholihah Pertiwi Abidin, Khusnul Hajar Nuansari

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Human resource is one of the most important components that can not be separated from communication fields, either in a large community like a mass or narrow ones such as an institution, office, group and even family. Human resource is an asset which is often used as a tool to achieve certain goals. Therefore, development of human resources is essential for improving skills and character of a person especially at the time that has entered globalization era. People are required to be able to compete both in the local and international arena, no matter what. This paper raised topic related to human resource development solution by a unique educational leadership and communication skill improvement through a linguistic approach. Here the authors want to go by form of public speaking method applied in Modern Islamic Boarding School Darussalam Gontor as the extracurricular activity that is using three languages, they are: Indonesian as the mother language or the nation language of the students, Arabic and English as the second language and Gontor’s mean to supply its students to be able to conquer the globalization needs. This implementation produced the establishment of great leaders through confidence growing to speak in public by adjusting the listener context. In linguistic term, it will help enhancing verbal and nonverbal communication skills and so forth in owning a lot of vocabulary.

Keywords: public speaking, Gontor, language, leadership

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542 Tsunami Vulnerability of Critical Infrastructure: Development and Application of Functions for Infrastructure Impact Assessment

Authors: James Hilton Williams

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Recent tsunami events, including the 2011 Tohoku Tsunami, Japan, and the 2015 Illapel Tsunami, Chile, have highlighted the potential for tsunami impacts on the built environment. International research in the tsunami impacts domain has been largely focused toward impacts on buildings and casualty estimations, while only limited attention has been placed on the impacts on infrastructure which is critical for the recovery of impacted communities. New Zealand, with 75% of the population within 10 km of the coast, has a large amount of coastal infrastructure exposed to local, regional and distant tsunami sources. To effectively manage tsunami risk for New Zealand critical infrastructure, including energy, transportation, and communications, the vulnerability of infrastructure networks and components must first be determined. This research develops infrastructure asset vulnerability, functionality and repair- cost functions based on international post-event tsunami impact assessment data from technologically similar countries, including Japan and Chile, and adapts these to New Zealand. These functions are then utilized within a New Zealand based impact framework, allowing for cost benefit analyses, effective tsunami risk management strategies and mitigation options for exposed critical infrastructure to be determined, which can also be applied internationally.

Keywords: impact assessment, infrastructure, tsunami impacts, vulnerability functions

Procedia PDF Downloads 148
541 Comparison of Real-Time PCR and FTIR with Chemometrics Technique in Analysing Halal Supplement Capsules

Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman

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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10-1 to 10-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.

Keywords: halal, real-time PCR, gelatine, chemometrics

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540 Reverse Logistics in Clothing Recycling: A Case Study in Chengdu

Authors: Guo Yan

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Clothing recycling bin is a traditional way to collect textile waste in many areas. In the clothing recycling business, the transportation cost normally takes over 50% of total costs. This case gives a good way to reduce transportation cost by reverse logistics system. In this reverse logistics system, there are offline strategic alliance partners, such as transport firms, convenience stores, laundries, and post office which are integrated onto the mobile APP. Offline strategic alliance partners provide the service of textile waste collection, and transportation by their vacant vehicles return journey from convenience stores, laundries and post offices to sorting centers. The results of the case study provide the strategic alliance with a valuable and light - asset business model by using the logistics of offline memberships. The company in this case just focuses on textile waste sorting, reuse, recycling etc. The research method of this paper is a case study of a clothing recycling company in Chengdu by field research and interview; the analysis is based on the theory of the reverse logistics system.

Keywords: closed-loop recycles system, clothing recycling, end-of-life clothing, sharing economy, strategic alliance, reverse logistics.

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539 Kinetics and Specificity of Drosophila melanogaster Molybdo-Flavoenzymes towards Their Substrates

Authors: Khaled S. Al Salhen

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Aldehyde oxidase (AO) and xanthine oxidoreductase (XOR) catalyze the oxidation of many different N-heterocyclic compounds as well as aliphatic and aromatic aldehydes to their corresponding lactam and carboxylic acids respectively. The present study examines the oxidation of dimethylamino-cinnamaldehyde (DMAC), vanillin and phenanthridine by AO and xanthine by XOR from Drosophila cytosol. Therefore, the results obtained in the present study showed the DMAC, vanillin and phenanthridine substrates used were found to be good substrates of Drosophila AO and xanthine is the preferred substrate for Drosophila XOR. Km values of AO substrates were observed with DMAC (50±5.4 µM), phenanthridine (80±9.1 µM) and vanillin (303±11.7 µM) respectively for Drosophila cytosol. The Km values for DMAC and phenanthridine were ~6 and ~4 fold lower than that for vanillin as a substrate. The Km for XOR with xanthine using NAD+ as an electron acceptor was 27±4.1 µM. Relatively low Vmax values were obtained with phenanthridine (1.78±0.38 nmol/min/mg protein) and DMAC (1.80±0.35 nmol/min/mg protein). The highest Vmax was obtained from Drosophila cytosol with vanillin (7.58±2.11 nmol/min/mg protein). It is concluded these results that AO and XOR in Drosophila were able to catalyse the biotransformation of numerous substrates of the well-characterised mammalian AO and XOR. The kinetic parameters have indicated that the activity of AO of Drosophila may be a significant factor the oxidation of aromatic aldehyde compounds.

Keywords: aldehyde oxidase, xanthine oxidoreductase, dimethylamino-cinnamaldehyde, vanillin, phenanthridine, Drosophila melanogaster

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538 Predictive Value of ¹⁸F-Fdg Accumulation in Visceral Fat Activity to Detect Colorectal Cancer Metastases

Authors: Amil Suleimanov, Aigul Saduakassova, Denis Vinnikov

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Objective: To assess functional visceral fat (VAT) activity evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in colorectal cancer (CRC). Materials and methods: We assessed 60 patients with histologically confirmed CRC who underwent 18F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVmax) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also report the best areas under the curve (AUC) for SUVmax with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted for age regression models and ROC analysis, 18F-FDG accumulation in RLH (cutoff SUVmax 0.74; Se 75%; Sp 61%; AUC 0.668; p = 0.049), RU (cutoff SUVmax 0.78; Se 69%; Sp 61%; AUC 0.679; p = 0.035), RRL (cutoff SUVmax 1.05; Se 69%; Sp 77%; AUC 0.682; p = 0.032) and RRI (cutoff SUVmax 0.85; Se 63%; Sp 61%; AUC 0.672; p = 0.043) could predict later metastases in CRC patients, as opposed to age, sex, primary tumor location, tumor grade and histology. Conclusions: VAT SUVmax is significantly associated with later metastases in CRC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, colorectal cancer, predictive value

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537 BIM Data and Digital Twin Framework: Preserving the Past and Predicting the Future

Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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536 Rural Households’ Resilience to Food Insecurity in Niger

Authors: Aboubakr Gambo, Adama Diaw, Tobias Wunscher

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This study attempts to identify factors affecting rural households’ resilience to food insecurity in Niger. For this, we first create a resilience index by using Principal Component Analysis on the following five variables at the household level: income, food expenditure, duration of grain held in stock, livestock in Tropical Livestock Units and number of farms exploited and second apply Structural Equation Modelling to identify the determinants. Data from the 2010 National Survey on Households’ Vulnerability to Food Insecurity done by the National Institute of Statistics is used. The study shows that asset and social safety nets indicators are significant and have a positive impact on households’ resilience. Climate change approximated by long-term mean rainfall has a negative and significant effect on households’ resilience to food insecurity. The results indicate that to strengthen households’ resilience to food insecurity, there is a need to increase assistance to households through social safety nets and to help them gather more resources in order to acquire more assets. Furthermore, early warning of climatic events could alert households especially farmers to be prepared and avoid important losses that they experience anytime an uneven climatic event occur.

Keywords: food insecurity, principal component analysis, structural equation modelling, resilience

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535 Coordinated Renewal Planning of Civil Infrastructure Systems

Authors: Hesham Osman

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The challenges facing aging urban infrastructure systems require a more holistic and comprehensive approach to their management. The large number of urban infrastructure renewal activities occurring in cities throughout the world leads to social, economic and environmental impacts on the communities in its vicinity. As such, a coordinated effort is required to streamline these activities. This paper presents a framework to enable temporal (time-based) coordination of water, sewer and road intervention activities. Intervention activities include routine maintenance, renewal, and replacement of physical assets. The coordination framework considers 1) Life-cycle costs, 2) Infrastructure level-of-service, and 3) Risk exposure to system operators. The model enables infrastructure asset managers to trade-off options of delaying versus bringing forward intervention activities of one system in order to be executed in conjunction with another co-located system in the right-of-way. The framework relies on a combination of meta-heuristics and goal-based optimization. In order to demonstrate the applicability of the framework, a case study for a major infrastructure corridor in Cairo, Egypt is taken as an example. Results show that the framework can be scaled-up to include other infrastructure systems located in the right-of-way like electricity, gas and telecom, provided that information can be shared among these entities.

Keywords: infrastructure, rehabilitation, construction, optimization

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534 Development of pH Responsive Nanoparticles for Colon Targeted Drug Delivery System

Authors: V. Balamuralidhara

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The aim of the present work was to develop Paclitaxel loaded polyacrylamide grafted guar gum nanoparticles as pH responsive nanoparticle systems for targeting colon. The pH sensitive nanoparticles were prepared by modified ionotropic gelation technique. The prepared nanoparticles showed mean diameters in the range of 264±0.676 nm to 726±0.671nm, and a negative net charge 10.8 mV to 35.4mV. Fourier Transformed Infrared Spectroscopy (FT-IR) and Differential Scanning Calorimetry (DSC) studies suggested that there was no chemical interaction between drug and polymers. The encapsulation efficiency of the drug was found to be 40.92% to 48.14%. The suitability of the polyacrylamide grafted guar gum ERN’s for the release of Paclitaxel was studied by in vitro release at pH 1.2 and 7.4. It was observed that, there was no significant amount of drug release at gastric pH and 97.63% of drug release at pH 7.4 was obtained for optimized formulation F3 at the end of 12 hrs. In vivo drug targeting performance for the prepared optimized formulation (F3) and pure drug Paclitaxel was evaluated by HPLC. It was observed that the polyacrylamide grafted guar gum can be used to prepare nanoparticles for targeting the drug to the colon. The release performance was greatly affected by the materials used in ERN’s preparation, which allows maximum release at colon’s pH. It may be concluded that polyacrylamide grafted guar gum nanoparticles loaded with paclitaxel have desirable release responsive to specific pH. Hence it is a unique approach for colonic delivery of drug having appropriate site specificity and feasibility and controlled release of drug.

Keywords: colon targeting, polyacrylamide grafted guar gum nanoparticles, paclitaxel, nanoparticles

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533 Selection of Green Fluorescent Protein and mCherry Nanobodies Using the Yeast Surface Display Method

Authors: Lavinia Ruta, Ileana Farcasanu

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The yeast surface display (YSD) technique enables the expression of proteins on yeast cell surfaces, facilitating the identification and isolation of proteins with targeted binding properties, such as nanobodies. Nanobodies, derived from camelid species, are single-domain antibody fragments renowned for their high affinity and specificity towards target proteins, making them valuable in research and potentially in therapeutics. Their advantages include a compact size (~15 kDa), robust stability, and the ability to target challenging epitopes. The project endeavors to establish and validate a platform for producing Green Fluorescent Protein (GFP) and mCherry nanobodies using the yeast surface display method. mCherry, a prevalent red fluorescent protein sourced from coral species, is commonly utilized as a genetic marker in biological studies due to its vibrant red fluorescence. The GFP-nanobody, a single variable domain of heavy-chain antibodies (VHH), exhibits specific binding to GFP, offering a potent means for isolating and engineering fluorescent protein fusions across various biological research domains. Both GFP and mCherry nanobodies find specific utility in cellular imaging and protein analysis applications.

Keywords: YSD, nanobodies, GFP, Saccharomyces cerevisiae

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532 An Overall Evaluation of Food Nanotechnology

Authors: Raana Babadi Fathipour

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Nourishment nanotechnology is an range of rising intrigued and opens up a entirety universe of modern conceivable outcomes for the nourishment industry. The essential categories of nanotechnology applications and functionalities right now within the improvement of nourishment bundling incorporate: the enhancement of plastic materials obstructions, the consolidation of dynamic components that can convey utilitarian properties past those of customary dynamic bundling, and the detecting and signaling of significant data. Nano nourishment bundling materials may amplify nourishment life, move forward nourishment security, alarm buyers that nourishment is sullied or ruined, repair tears in bundling, and indeed release preservatives to expand the life of the nourishment within the bundle. Nanotechnology applications within the nourishment industry can be utilized to identify microbes in bundling, or produce stronger flavors and color quality, and security by expanding the obstruction properties. Nanotechnology holds extraordinary guarantee to supply benefits not fair inside nourishment items but too around nourishment items. In reality, nanotechnology presents modern chances for advancement within the nourishment industry at monstrous speed, but instability and wellbeing concerns are moreover developing. EU/WE/global enactment for the direction of nanotechnology in nourishment are scanty. Besides, current enactment shows up unacceptable to nanotechnology specificity.

Keywords: nano technology, nano foods, food packaging, nano participle

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531 A Model for Diagnosis and Prediction of Coronavirus Using Neural Network

Authors: Sajjad Baghernezhad

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Meta-heuristic and hybrid algorithms have high adeer in modeling medical problems. In this study, a neural network was used to predict covid-19 among high-risk and low-risk patients. This study was conducted to collect the applied method and its target population consisting of 550 high-risk and low-risk patients from the Kerman University of medical sciences medical center to predict the coronavirus. In this study, the memetic algorithm, which is a combination of a genetic algorithm and a local search algorithm, has been used to update the weights of the neural network and develop the accuracy of the neural network. The initial study showed that the accuracy of the neural network was 88%. After updating the weights, the memetic algorithm increased by 93%. For the proposed model, sensitivity, specificity, positive predictivity value, value/accuracy to 97.4, 92.3, 95.8, 96.2, and 0.918, respectively; for the genetic algorithm model, 87.05, 9.20 7, 89.45, 97.30 and 0.967 and for logistic regression model were 87.40, 95.20, 93.79, 0.87 and 0.916. Based on the findings of this study, neural network models have a lower error rate in the diagnosis of patients based on individual variables and vital signs compared to the regression model. The findings of this study can help planners and health care providers in signing programs and early diagnosis of COVID-19 or Corona.

Keywords: COVID-19, decision support technique, neural network, genetic algorithm, memetic algorithm

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530 Amniotic Fluid Mesenchymal Stem Cells Selected for Neural Specificity Ameliorates Chemotherapy Induced Hearing Loss and Pain Perception

Authors: Jan F. Talts, Amit Saxena, Kåre Engkilde

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Chemotherapy-induced peripheral neuropathy (CIPN) is one of the most frequent side effects caused by anti-neoplastic agents, with a prevalence from 19 % to 85 %. Clinically, CIPN is a mostly sensory neuropathy leading to pain and to motor and autonomic changes. Due to its high prevalence among cancer patients, CIPN constitutes a major problem for both cancer patients and survivors, especially because currently, there is no single effective method of preventing CIPN. Hearing loss is the most common form of sensory impairment in humans and can be caused by ototoxic chemical compounds such as chemotherapy (platinum-based antineoplastic agents).In rodents, single or repeated cisplatin injections induce peripheral neuropathy and hearing impairment mimicking human disorder, allowing studying the efficacy of new pharmacological candidates in chemotherapy-induced hearing loss and peripheral neuropathy. RNA sequencing data from full term amniotic fluid (TAF) mesenchymal stemcell (MSC) clones was used to identify neural-specific markers present on TAF-MSC. Several prospective neural markers were tested by flow cytometry on cultured TAF-MSC. One of these markers was used for cell-sorting using Tyto MACSQuant cell sorter, and the neural marker positive cell population was expanded for several passages to the final therapeutic product stage. Peripheral neuropathy and hearing loss was induced in mice by administration of cisplatin in three week-long cycles. The efficacy of neural-specific TAF-MSC in treating hearing loss and pain perception was evaluated by administration of three injections of 3 million cells/kg by intravenous route or three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment. Auditory brainstem responses (ABR) are electric potentials recorded from scalp electrodes, and the first ABR wave represents the summed activity of the auditory nerve fibers contacting the inner hair cells. For ABR studies, mice were anesthetized, then earphones were placed in the left ear of each mouse, an active electrode was placed in the vertex of the skull, a reference electrode under the skin of the mastoid bone, and a ground electrode in the neck skin. The stimuli consisted of tone pips of five frequencies (2, 4, 6, 12, 16, and 24 kHz) at various sound levels (from 0 to 90 dB) ranging to cover the mouse auditory frequency range. The von Frey test was used to assess the onset and maintenance of mechanical allodynia over time. Mice were placed in clear plexiglass cages on an elevated mesh floor and tested after 30 min of habituation. Mechanical paw withdrawal threshold was examined using an electronic von Frey anesthesiometer. Cisplatin groups treated with three injections of 3 million cells/kg by intravenous route and three injections of 3 million cells/kg by intra-arterial route after each cisplatin cycle treatment presented, a significant increase of hearing acuity characterized by a decrease of ABR threshold and a decrease of neuropathic pain characterized by an increase of von Frey paw withdrawal threshold compared to controls only receiving cisplatin. This study shows that treatment with MSCselected for neural specificity presents significant positive efficacy on the chemotherapy-induced neuropathic pain and the chemotherapy-induced hearing loss.

Keywords: mesenchymal stem cell, peripheral neuropathy, amniotic fluid, regenerative medicine

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529 Predictive Value of ¹⁸F-Fluorodeoxyglucose Accumulation in Visceral Fat Activity to Detect Epithelial Ovarian Cancer Metastases

Authors: A. F. Suleimanov, A. B. Saduakassova, V. S. Pokrovsky, D. V. Vinnikov

Abstract:

Relevance: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognoses. The aim of the study was to evaluate functional visceral fat activity (VAT) evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in epithelial ovarian cancer (EOC). Materials and methods: We assessed 53 patients with histologically confirmed EOC who underwent ¹⁸F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVₘₐₓ) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also identified the best areas under the curve (AUC) for SUVₘₐₓ with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted-for regression models and ROC analysis, ¹⁸F-FDG accumulation in RE (cut-off SUVₘₐₓ 1.18; Se 64%; Sp 64%; AUC 0.669; p = 0.035) could predict later metastases in EOC patients, as opposed to age, sex, primary tumor location, tumor grade, and histology. Conclusions: VAT SUVₘₐₓ is significantly associated with later metastases in EOC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, EOC, predictive value

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528 Development of Trigger Tool to Identify Adverse Drug Events From Warfarin Administered to Patient Admitted in Medical Wards of Chumphae Hospital

Authors: Puntarikorn Rungrattanakasin

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Objectives: To develop the trigger tool to warn about the risk of bleeding as an adverse event from warfarin drug usage during admission in Medical Wards of Chumphae Hospital. Methods: A retrospective study was performed by reviewing the medical records for the patients admitted between June 1st,2020- May 31st, 2021. ADEs were evaluated by Naranjo’s algorithm. The international normalized ratio (INR) and events of bleeding during admissions were collected. Statistical analyses, including Chi-square test and Reciever Operating Characteristic (ROC) curve for optimal INR threshold, were used for the study. Results: Among the 139 admissions, the INR range was found to vary between 0.86-14.91, there was a total of 15 bleeding events, out of which 9 were mild, and 6 were severe. The occurrence of bleeding started whenever the INR was greater than 2.5 and reached the statistical significance (p <0.05), which was in concordance with the ROC curve and yielded 100 % sensitivity and 60% specificity in the detection of a bleeding event. In this regard, the INR greater than 2.5 was considered to be an optimal threshold to alert promptly for bleeding tendency. Conclusions: The INR value of greater than 2.5 (>2.5) would be an appropriate trigger tool to warn of the risk of bleeding for patients taking warfarin in Chumphae Hospital.

Keywords: trigger tool, warfarin, risk of bleeding, medical wards

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527 The Effect of Knowledge Management in Lean Organization

Authors: Mehrnoosh Askarizadeh

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In an ever changeable and globalized world with new economic and global competitors competing for the same customers and resources, is increasing the pressure on organizations' competitiveness. In addition, organizations faces additional challenges due to an ever-growing amount of data and the ever-bigger challenge of analyzing that data and keeping the data secure. Successful companies are characterized by exploiting their intellectual capital in an efficient manner. Thus, the most valuable asset an organization has today has become its employees' knowledge. To enable this, there is a tool that supports easier handling and optimizes the use of knowledge, which is knowledge management. Based on the theoretical framework and careful review as well as analysis of interviews and observations resulted in six essential areas: structure, management, compensation, communication, trust and motivation. The analysis showed that the scientific articles and literature have different perspectives, different definitions and are based on different theories but the essence is that they all finally seems to arrive at the same result and conclusion, although with different viewpoints and perspectives. This is regardless of whether the focus is on management style, rewards or communication they all focus on the individual. The conclusion is that organizational culture affects knowledge management and dissemination of information, because of its direct impact on the individual. The largest and most important underlying factor why we choose to participate in improvement work or share knowledge is our motivation. Motivation is the reason for and the reason behind our actions.

Keywords: lean, lean production, knowledge management, information management, motivation

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526 Genetic Variation among the Wild and Hatchery Raised Populations of Labeo rohita Revealed by RAPD Markers

Authors: Fayyaz Rasool, Shakeela Parveen

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The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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525 A Risk-Based Comprehensive Framework for the Assessment of the Security of Multi-Modal Transport Systems

Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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524 Predicting Relative Performance of Sector Exchange Traded Funds Using Machine Learning

Authors: Jun Wang, Ge Zhang

Abstract:

Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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523 Price Heterogeneity in Establishing Real Estate Composite Price Index as Underlying Asset for Property Derivatives in Russia

Authors: Andrey Matyukhin

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Russian official statistics have been showing a steady decline in residential real estate prices for several consecutive years. Price risk in real estate markets is thus affecting various groups of economic agents, namely, individuals, construction companies and financial institutions. Potential use of property derivatives might help mitigate adverse consequences of negative price dynamics. Unless a sustainable price indicator is developed, settlement of such instruments imposes constraints on counterparties involved while imposing restrictions on real estate market development. The study addresses geographical and classification heterogeneity in real estate prices by means of variance analysis in various groups of real estate properties. In conclusion, we determine optimal sample structure of representative real estate assets with sufficient level of price homogeneity. The composite price indicator based on the sample would have a higher level of robustness and reliability and hence improving liquidity in the market for property derivatives through underlying standardization. Unlike the majority of existing real estate price indices, calculated on country-wide basis, the optimal indices for Russian market shall be constructed on the city-level.

Keywords: price homogeneity, property derivatives, real estate price index, real estate price risk

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522 Impact of Macroeconomic Variables on Indian Mutual Funds: A Time Series Analysis

Authors: Sonali Agarwal

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The investor perception about investment avenues is affected to a great degree by the current happenings, within the country, and on the global stage. The influencing events can range from government policies, bilateral trade agreements, election agendas, to changing exchange rates, appreciation and depreciation of currency, recessions, meltdowns, bankruptcies etc. The current research attempts to discover and unravel the effect of various macroeconomic variables (crude oil price, gold price, silver price and USD exchange rate) on the Indian mutual fund industry in general and the chosen funds (Axis Gold Fund, BSL Gold Fund, Kotak Gold Fund & SBI gold fund) in particular. Cointegration tests and Vector error correction equations prove that the chosen variables have strong effect on the NAVs (net asset values) of the mutual funds. However, the greatest influence is felt from the fund’s own past and current information and it is found that when an innovation of fund’s own lagged NAVs is given, variance caused is high that changes the current NAVs markedly. The study helps to highlight the interplay of macroeconomic variables and their repercussion on mutual fund industry.

Keywords: cointegration, Granger causality, impulse response, macroeconomic variables, mutual funds, stationarity, unit root test, variance decomposition, VECM

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521 Simultaneous Extraction and Estimation of Steroidal Glycosides and Aglycone of Solanum

Authors: Karishma Chester, Sarvesh Paliwal, Sayeed Ahmad

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Solanumnigrum L. (Family: Solanaceae), is an important Indian medicinal plant and have been used in various traditional formulations for hepato-protection. It has been reported to contain significant amount of steroidal glycosides such as solamargine and solasonine as well as their aglycone part solasodine. Being important pharmacologically active metabolites of several members of Solanaceae these markers have been attempted various times for their extraction and quantification but separately for glycoside and aglycone part because of their opposite polarity. Here, we propose for the first time simultaneous extraction and quantification of aglycone (solasodine)and glycosides (solamargine and solasonine) inleaves and berries of S.nigrumusing solvent extraction followed by HPTLC analysis. Simultaneous extraction was carried out by sonication in mixture of chloroform and methanol as solvent. The quantification was done using silica gel 60F254HPTLC plates as stationary phase and chloroform: methanol: acetone: 0.5 % ammonia (7: 2.5: 1: 0.4 v/v/v/v) as mobile phaseat 400 nm, after derivatization with an isaldehydesul furic acid reagent. The method was validated as per ICH guideline for calibration, linearity, precision, recovery, robustness, specificity, LOD, and LOQ. The statistical data obtained for validation showed that method can be used routinely for quality control of various solanaceous drugs reported for these markers as well as traditional formulations containing those plants as an ingredient.

Keywords: solanumnigrum, solasodine, solamargine, solasonine, quantification

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520 Numerical Pricing of Financial Options under Irrational Exercise Times and Regime-Switching Models

Authors: Mohammad Saber Rohi, Saghar Heidari

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In this paper, we studied the pricing problem of American options under a regime-switching model with the possibility of a non-optimal exercise policy (early or late exercise time) which is called an irrational strategy. For this, we consider a Markovmodulated model for the dynamic of the underlying asset as an alternative model to the classical Balck-Scholes-Merton model (BSM) and an intensity-based model for the irrational strategy, to provide more realistic results for American option prices under the irrational behavior in real financial markets. Applying a partial differential equation (PDE) approach, the pricing problem of American options under regime-switching models can be formulated as coupled PDEs. To solve the resulting systems of PDEs in this model, we apply a finite element method as the numerical solving procedure to the resulting variational inequality. Under some appropriate assumptions, we establish the stability of the method and compare its accuracy to some recent works to illustrate the suitability of the proposed model and the accuracy of the applied numerical method for the pricing problem of American options under the regime-switching model with irrational behaviors.

Keywords: irrational exercise strategy, rationality parameter, regime-switching model, American option, finite element method, variational inequality

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519 An Empirical Study of the Best Fitting Probability Distributions for Stock Returns Modeling

Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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518 Factors Affecting the Profitability of Commercial Banks: An Empirical Study of Indian Banking Sector

Authors: Neeraj Gupta, Jitendra Mahakud

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The banking system plays a major role in the Indian economy. Banking system is the payment gateway of most of the financial transactions. Banking has gone a major transition that is still in progress. Recent banking reforms after liberalization in 1991 have led to the establishment of the foreign banks in the country. The foreign banks are not listed in the Indian stock markets and have increased the competition leading to the capture of the significant share in the revenue from the public sector banks which are still the major players in the Indian banking sector. The performance of the banking sector depends on the internal (bank specific) as well as the external (market specific and macroeconomic) factors. Profitability in banking sector is affected by numerous factors which can be internal or external. The present study examines these internal and external factors which are likely to effect the profitablilty of the Indian banks. The sample consists of a panel dataset of 64 commercial banks in India, consisting of 1088 observations over the years from 1998 to 2016. The GMM dynamic panel estimation given by Arellano and Bond has been used. The study revealed that the variables capital adequacy ratio, deposit, age, labour productivity, non-performing asset, inflation and concentration have significant effect on performance measured.

Keywords: banks in India, bank performance, bank productivity, banking management

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