Search results for: utility value

Authors: Bisi S. Olawoyin

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This study attempts an exploration into behavioural finance in which the traditional assumptions of expected utility maximization with rational investors in efficient markets are dropped. It reviews prior research and evidence about how psychological biases affect investors behaviour and stock selection. This study examined the relationship between demographic variables and financial behaviour biases among public sector retirees who invested in the Nigerian Stock Exchange prior to their retirement. By using questionnaire survey method, a total of 214 valid convenient samples were collected in order to determine how specific demographic and psychological trait affect stock selection between dividend paying and non-dividend paying stocks. Descriptive statistics and OLS were used to analyse the results. Findings showed that most of the retirees prefer dividend paying stocks in few years preceding their retirement but still hold on to their non-dividend paying stock on retirement. A significant difference also exists between senior and junior retirees in preference for non-dividend paying stocks. These findings are consistent with the clientele theories of dividend.

Keywords: behavioural finance, clientele theories, dividend paying stocks, stock selection

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Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Anant Pandey, Kanika Sharma, Vibha Chopra, Shaila Bahl, Pratik Kumar, S. P. Lochab, Birendra Singh

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This paper reports the thermoluminescence (TL) properties of nanocrystalline CaSO₄ activated by Ce, Sm, and Dy. TL properties are investigated by chiefly changing the dopant element and also by varying the concentration of the dopant elements (from 0.05 mol % to 0.5 mol %) so as to establish the optimized dopant concentration for each of the activators. The method of salt preparation used is the typical chemical co-precipitation method and the technique used for characterization of the prepared samples is the X-Ray Diffraction (XRD) technique. Further, the phosphors are irradiated with gamma radiation from Co-60 (1.25 MeV) source (dose range- 30 Gy to 500 Gy). The optimized concentration (vis-a-vis TL peak intensity) of activator for CaSO₄:Ce is found to be 0.2 mol %, for CaSO₄:Sm it is 0.1 mol % and for CaSO₄:Dy it is 0.2 mol %. Further, the primary study of the TL response curves for all the three phosphors confirms linearity in the studied dose range (i.e., 30 Gy to 500 Gy). Finally, CaSO₄:Dy was also studied for its energy dependence property which plays an important role in defining the utility of a phosphor for dosimetric applications. The range of doses used for the energy dependence study was from 30 Gy to 500 Gy from Cs-137 (0.662 MeV). The nano-phosphors showed potential to be used as radiation dosimeter in the studied range of gamma radiation and thus must be studied for a wider range of doses.

Keywords: gamma radiation, nanocrystalline, radiation dosimetry, thermoluminescence

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Authors: Lala Rukh, Muhammad Abbas Choudhary, Saddam Akber Abbasi

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In Pakistan, the privatization of major sector of the national economy i.e. power, telecom, and gas is very strongly advocated since 80s. With varying degree of progress made in these sectors, it has been the government’s approach that the privatization accelerates the sectorial growth, increases operational efficiency and attracts the foreign investment and is of special significance for developing economies. The gas sector was not an exception and the privatization in this sector has moved through various stages during this time within the realms of socio-political agenda. This paper presents the overview of the gas sector in the country. The Oil and Gas Regulatory Authority (OGRA) Ordinance and privatization commission policy position as depicted in the press briefings provides philosophical foundations to the privatization and sectorial restructuring in this paper. The role of the major players from privatization perspective is discussed with special reference to the importance of natural gas sector. The case study further discusses the economic regulations that are being adopted by utility regulators in Pakistan and elsewhere in the world and some issues that the Regulatory Authority will be concerned are outlined. Major operators in the gas sector including Oil & Gas Development Corporation (OGDC), Sui Northern Gas Pipelines Limited (SNGPL), Sui Southern Gas Pipelines Limited (SSGPL) is also presented.

Keywords: privatization, economic regulation, OGDCL, SSGCL, SNGPL

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Authors: William G. "Gus" Simmons

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Municipal and industrial wastewater plants across our country utilize anaerobic digestion as either primary treatment or as a means of waste sludge treatment and reduction. The emphasis on renewable energy and clean energy over the past several years, coupled with increasing electricity costs and increasing consumer demands for efficient utility operations has led to closer examination of the potential for harvesting the energy value of the biogas produced by anaerobic digestion. Although some facilities may have already come to the belief that harvesting this energy value is not practical or a top priority as compared to other capital needs and initiatives at the wastewater plant, we see that many are seeing biogas, and an opportunity for additional revenues, go up in flames as they continue to flare. Conversely, few wastewater plants under progressive and visionary leadership have demonstrated that harvesting the energy value from anaerobic digestion is more than “smoke and hot air”. From providing thermal energy to adjacent or on-campus operations to generating electricity and/or transportation fuels, these facilities are proving that energy harvesting can not only be profitable, but sustainable. This paper explores ways in which wastewater treatment plants can increase their value and import to the communities they serve through the generation of clean, renewable energy; also presented the processes in which these facilities moved from energy and cost sinks to sparks of innovation and pride in the communities in which they operate.

Keywords: anaerobic digestion, harvesting energy, biogas, renewable energy, sustainability

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Authors: Zubier Arfan, Paul Johnson

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The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model.

Keywords: market-making, market-microsctrucure, stochastic volatility, quantitative trading

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Maureen Gibney

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The examination of narrative in psychology has a long tradition, starting with psychoanalytic theory and embracing over time cognitive, social, and personality psychology, among others. Narrative use has been richly detailed as well in medicine, nursing, and social service. One aspect of narrative that has ready utility in higher education and in clinical work is the exploration of suffering and its meaning. Because it is such a densely examined topic, suffering provides a window into identity, sense of purpose, and views of humanity and of the divine. Storytelling analysis permits an exploration of a host of specific manifestations of suffering such as pain and illness, moral injury, and the impact of prolonged suffering on love and relationships. This presentation will review the origins and current understandings of narrative theory in general, and will draw from psychology, medicine, ethics, nursing, and social service in exploring the topic of suffering in particular. It is suggested that the use of narrative themes such as meaning making, agency and communion, generativity, and loss and redemption allows for a finely grained analysis of common and more atypical sources of suffering, their resolution, and the acceptance of their continuation when resolution is not possible. Such analysis, used in professional work and in higher education, can enrich one’s empathy and one’s sense of both the fragility and strength of everyday life.

Keywords: meaning making, narrative theory, suffering, teaching

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Authors: Brian J. Graham, Ronald T. Raines

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The presence of a nearly vacant p orbital on boron endows boronic acids with unique abilities as a catalyst and ligand. An organocatalytic process has been developed for the conversion of biomass-derived sugars to 5-hydroxymethylfurfural, which is a platform chemical. Specifically, 2-carboxyphenylboronic acid (2-CPBA) has been shown to be an optimal catalyst for this process, promoting the desired transformation in the absence of metals. The attributes of 2-CPBA as a catalyst led to additional investigations of its structure and reactivity. 2-CPBA was found to exist as a cyclized benzoxaborolone adduct rather than a free carboxylic acid. This cyclization has profound consequences for the oxidative stability of the boronic acid. Stereoelectronic effects within the oxaborolone ring destabilize the oxidation transition state by reducing electron donation from the cyclic oxygen to the developing p orbital on boron. That leads to a 10,000-fold increase in oxidative stability while maintaining the normal reactivity of boronic acids toward diols (e.g., carbohydrates) and nucleophiles in proteins while also presenting numerous hydrogen-bond accepting and donating groups. Thus, benzoxaborolones are useful in catalysis, chemical biology, medicinal chemistry, and allied fields.

Keywords: bioisosteres, boronic acid, catalysis, oxidative stability, pharmacophore, stereoelectronic effects

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Authors: M. Helen

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Chemical graph serves as a convenient model for any real or abstract chemical system. Dendrimers are novel three dimensional hyper branched globular nanopolymeric architectures. Drug delivery scientists are especially enthusiastic about possible utility of dendrimers as drug delivery tool. Dendrimers like poly L lysine (PLL), poly-propylene imine (PPI) and poly-amidoamine (PAMAM), etc., are used as gene carrier in drug delivery system because of their chemical characteristics. These characteristics of chemical compounds are analysed using topological indices (invariants under graph isomorphism) such as Wiener index, Zagreb index, etc., Prof. V. R. Kulli motivated by the application of Zagreb indices in finding the total π energy and derived Gourava indices which is an improved version over Zagreb indices. In this paper, we study the structure of PLL-Dendrimer that has the following applications: reduction in toxicity, colon delivery, and topical delivery. Also, we determine first and second Gourava indices, first and second hyper Gourava indices, product and sum connectivity Gourava indices for PLL-Dendrimer. Gourava Indices have found applications in Quantitative Structure-Property Relationship (QSPR)/ Quantitative Structure-Activity Relationship (QSAR) studies.

Keywords: connectivity Gourava indices, dendrimer, Gourava indices, hyper GouravaG indices

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Authors: Lateefat Amao, Misagh Faezipour

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Implementing electronic health records (EHR) in healthcare is a pivotal transition aimed at digitizing and optimizing patient health information management. The expectations associated with this transition are high, even towards other health information systems (HIS) and health technology. This multifaceted process involves careful planning and execution to improve the quality and efficiency of patient care, especially as healthcare technology is a sensitive niche. Key considerations include a thorough needs assessment, judicious vendor selection, robust infrastructure development, and training and adaptation of healthcare professionals. Comprehensive training programs, data migration from legacy systems and models, interoperability, as well as security and regulatory compliance are imperative for healthcare staff to navigate EHR systems adeptly. The purpose of this work is to offer a comprehensive review of the literature on EHR implementation. It explores the impact of this health technology on health practices, highlights challenges and barriers to its successful utility, and offers practical strategies that can impact its success in healthcare. This paper provides a thorough review of studies on the adoption of EHRs, emphasizing the wide range of experiences and results connected to EHR use in the medical field, especially across different types of healthcare organizations.

Keywords: healthcare, electronic health records, EHR implementation, patient care, interoperability

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Authors: Noriko Hanakawa, Masaki Obana

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A simulation tool has been proposed for big-scale projection mapping events. The tool has four main functions based on Mapbox and Unity utilities. The first function is building a 3D model of real cities by MapBox. The second function is a movie projection to some buildings in real cities by Unity. The third function is a movie sending function from a PC to a virtual projector. The fourth function is mapping movies with fitting buildings. The simulation tool was adapted to a real projection mapping event that was held in 2019. The event has been finished. The event had a serious problem in the movie projection to the target building. The extra tents were set in front of the target building. The tents became the obstacles to the movie projection. The simulation tool can be reappeared the problems of the event. Therefore, if the simulation tool was developed before the 2019 projection mapping event, the problem of the tents’ obstacles could be avoided with the simulation tool. In addition, we confirmed that the simulation tool is useful to make a plan of future projection mapping events in order to avoid obstacles of various extra equipment such as utility poles, planting trees, monument towers.

Keywords: projection mapping, projector position, real 3D map, avoiding obstacles

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Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: distributed generation photovoltaic (DG PV), optimal location, penetration level, sub–transmission network

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Authors: Irvan Adhin Cholilie, Susinggih Wijana, Yusron Sugiarto

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The aim of this research is to compare the results of black grass jelly produced using laboratory scale and double scale. In this research, the production from the laboratory scale is using ingredients of 1 kg black grass jelly added with 5 liters of water, while the double scale is using 5 kg black grass jelly and 75 liters of water. The results of organoleptic tests performed by 30 panelists (general) to the sample gels of grass black powder produced from both of laboratory and double scale are not different significantly in color, odor, flavor, and texture. Proximate test results conducted in both of grass black jelly powder produced in laboratory scale and double scale also have no significant differences in all parameters. Grass black jelly powder from double scale contains water, carbohydrate, crude fiber, and yield in the amount of 12,25 %; 43,7 %; 5,89 %; and 16,28 % respectively. The results of the energy efficiency analysis by boiling, draining, evaporation, drying, and milling processes are 85,11 %; 76,97 %; 99,64 %; 99,99% and 99,39% respectively. The utility needs including water needs for each batch amounted 0.1 m3 and cost Rp 220,5 per batch, the electricity needs for each batch is 20.01 kWh and cost Rp 18569.28 per batch, and LPG needs for each batch is 30 kg costed Rp 234,000.00 so that the total cost spent for the process is Rp 252,789.78 .

Keywords: black grass jelly, powder, mass balance, energy balance, cost

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Gokhan Zengin, Cengiz Sarikurkcu, Abdurrahman Aktumsek, Ramazan Ceylan

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The present study was designated to characterize the essential oil from S. galatica (SGEOs) and evaluate its antioxidant and enzyme inhibitory activities. Antioxidant capacity were tested different methods including free radical scavenging (DPPH, ABTS and NO), reducing power (FRAP and CUPRAC), metal chelating and phosphomolybdenum. Inhibitory activities were analyzed on acetylcholiesterase, butrylcholinesterase, α-amylase and α-glucosidase. SGEOs were chemically analyzed and identified by gas chromatography (GC) and gas chromatography/mass spectrophotometry (GC/MS). 23 components, representing 98.1% of SGEOs were identified. Monoterpene hydrocarbons (74.1%), especially α- (23.0%) and β-pinene (32.2%), were the main constituents in SGEOs. The main sesquiterpene hydrocarbons were β-caryophyllene (16.9%), Germacrene-D (1.2%) and Caryophyllene oxide (1.2%), respectively. Generally, SGEOs has shown moderate free radical, reducing power, metal chelating and enzyme inhibitory activities. These activities related to chemical profile in SGEOs. Our findings supported that the possible utility of SGEOs is a source of natural agents for food, cosmetics or pharmaceutical industries.

Keywords: sideritis galatica, antioxidant, monoterpenes, cholinesterase, anti-diabetic

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Authors: Kathy Mwende Kiema, Remember Samu, Murat Fahrioglu

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Despite the implementation of a Feed in Tariff (FiT) for solar power plants in Kenya, the uptake and subsequent development of utility scale power plants has been slow. This paper, therefore, proposes a Concentrating Solar Power (CSP) plant configuration that can supply both power to the grid and operate a sea water desalination plant, thus providing an economically viable alternative to Independent Power Producers (IPPs). The largest city on the coast, Mombasa, has a chronic water shortage and authorities are looking to employ desalination plants to supply a deficit of up to 100 million cubic meters of fresh water per day. In this study the desalination plant technology was selected based on an analysis of operational costs in $/m3 of plants that are already running. The output of the proposed CSP plant, Net Present Value (NPV), plant capacity factor, thermal efficiency and quantity of CO2 emission avoided were simulated using Greenius software (Green energy system analysis tool) developed by the institute of solar research at the German Aerospace Center (DLR). Data on solar irradiance were derived from the Solar and Wind Energy Resource Assessment (SWERA) for Kenya.

Keywords: desalination, feed in tariff, independent power producer, solar CSP

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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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Authors: Ezgi Nevruz, Kasirga Yildirak, Ashis SenGupta

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Comparing or ranking risks is the main motivating factor behind the human trait of making choices. Cumulative prospect theory (CPT) is a preference theory approach that evaluates perception and bias in decision making under risk and uncertainty. We aim to investigate the aggregate claims of different risk classes in terms of their comparability and amenability to ordering when the impact of risk perception is considered. For this aim, we prioritize the aggregate claims taken as actuarial risks by using various stochastic ordering relations. In order to prioritize actuarial risks, we use stochastic relations such as stochastic dominance and stop-loss dominance that are proposed in the frame of partial order theory. We take into account the dependency of the individual claims exposed to similar environmental risks. At first, we modify the zero-utility premium principle in order to obtain a solution for the stop-loss premium under CPT. Then, we propose a stochastic stop-loss dominance of the aggregate claims and find a relation between the stop-loss dominance and the first-order stochastic dominance under the dependence assumption by using properties of the familiar as well as some emerging multivariate claim distributions.

Keywords: cumulative prospect theory, partial order theory, risk perception, stochastic dominance, stop-loss dominance

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Authors: Neha Singh

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The incidence of skin cancer has been rising worldwide due to excessive exposure to sun light. Climatic changes and depletion of ozone layer allow the easy entry of UV rays on earth, resulting skin damages such as sunburn, premature skin ageing, allergies and skin cancer. Researches have suggested many modes for protection of human skin against ultraviolet radiation; avoidance to outdoor activities, using textiles for covering the skin, sunscreen and sun glasses. However, this paper gives an insight about how textile material specially woven and knitted cotton can be efficiently utilized for protecting human skin from the harmful ultraviolet radiations by combining reactive dyes with Aloe Vera. Selection of the fabric was based on their utility and suitability as per the climate condition of the country for the upper and lower garment. A standard dyeing process was used, and Aloe Vera molecules were applied by in-micro encapsulation technique. After combining vat dyes with Aloe Vera excellent UPF (Ultra violet Protective Factor) was observed. There is a significant change in the UPF of vat dyed cotton fabric after treatment with Aloe Vera.

Keywords: UV protection, aloe vera, protective clothing, reactive dyes, cotton, woven and knits

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Dawit Gebreegzabher Hagos, Yazezew Kebede Kiro, Mahmud Abdulkader, Henk H. D. F. Schallig, Dawit Wolday

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Rapid and accurate visceral leishmaniasis (VL) diagnosis is needed to initiate prompt treatment to reduce morbidity and mortality. Here, we evaluated the performance of loop-mediated isothermal amplification (LAMP) assay for the diagnosis of VL from blood in an endemic area in Ethiopia. LAMP was positive in 117/122 confirmed VL cases and negative in 149/152 controls, resulting in a sensitivity of 95.9% (95% CI: 90.69–98.66) and a specificity of 98.0% (95% CI: 94.34–99.59), respectively. The sensitivity of the LAMP assay was 95.0% (95% CI: 88.61–98.34) in HIV-negatives and 100% (95% CI: 85.18–100.0) in HIV-positives. Compared with microscopy, LAMP detected 82/87 (94.3%, 95% CI: 87.10–98.11) of the microscopy1 cases and was negative in 11/27 (40.7%, 95% CI: 22.39–61.20) of the microscopy2 cases. Compared with the rK39 serology, LAMP detected 113/120 (94.2%, 95% CI: 88.35–97.62) of the rK391 cases and was negative in 149/154 (96.8%, 95% CI: 92.59–98.94) of the rK392 cases. However, when compared with microscopy only, rK39 detected 83/87 (95.4%, 95% CI: 88.64–98.73) of the microscopy1 cases and negative in only 12/27 (44.4%, 95% CI: 25.48–64.67) of the microscopy– cases. There was an excellent agreement between rK39 and LAMP (Kappa 5 0.91, 95% CI: 0.86–0.96). Furthermore, an algorithm using rK39 followed by LAMP would yield a sensitivity of 99.2% (95%CI: 95.52–99.89) and a specificity of 98.0% (95% CI: 94.34–99.59). The findings demonstrate that the LAMP assay is an accurate and rapid molecular assay for VL diagnosis, including in HIV-1 co-infected patients, in an endemic setting.

Keywords: visceral leishmaniasis, HIV, diagnosis, LAMP, Ethiopia

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Authors: Areti Okalidou, Paul D. Hatzigiannakoglou, Aikaterini Vatou, George Kyriafinis

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Young children are nowadays adept at using technology. Hence, computer-based auditory training programs (CBATPs) have become increasingly popular in aural rehabilitation for children with hearing loss and/or with cochlear implants (CI). Yet, their clinical utility for prognostic, diagnostic, and monitoring purposes has not been explored. The purposes of the study were: a) to develop an updated version of the auditory rehabilitation tool for Greek-speaking children with cochlear implants, b) to develop a database for behavioral responses, and c) to compare accuracy rates and reaction times in children differing in hearing status and other medical and demographic characteristics, in order to assess the tool’s clinical utility in prognosis, diagnosis, and progress monitoring. The updated version of the auditory rehabilitation tool was developed on a tablet, retaining the User-Centered Design approach and the elements of the Virtual Reality (VR) serious game. The visual stimuli were farm animals acting in simple game scenarios designed to trigger children’s responses to animal sounds, names, and relevant sentences. Based on an extended version of Erber’s auditory development model, the VR game consisted of six stages, i.e., sound detection, sound discrimination, word discrimination, identification, comprehension of words in a carrier phrase, and comprehension of sentences. A familiarization stage (learning) was set prior to the game. Children’s tactile responses were recorded as correct, false, or impulsive, following a child-dependent set up of a valid delay time after stimulus offset for valid responses. Reaction times were also recorded, and the database was in Εxcel format. The tablet version of the auditory rehabilitation tool was piloted in 22 preschool children with Νormal Ηearing (ΝΗ), which led to improvements. The study took place in clinical settings or at children’s homes. Fifteen children with CI, aged 5;7-12;3 years with post-implantation 0;11-5;1 years used the auditory rehabilitation tool. Eight children with CI were monolingual, two were bilingual and five had additional disabilities. The control groups consisted of 13 children with ΝΗ, aged 2;6-9;11 years. A comparison of both accuracy rates, as percent correct, and reaction times (in sec) was made at each stage, across hearing status, age, and also, within the CI group, based on presence of additional disability and bilingualism. Both monolingual Greek-speaking children with CI with no additional disabilities and hearing peers showed high accuracy rates at all stages, with performances falling above the 3rd quartile. However, children with normal hearing scored higher than the children with CI, especially in the detection and word discrimination tasks. The reaction time differences between the two groups decreased in language-based tasks. Results for children with CI with additional disability or bilingualism varied. Finally, older children scored higher than younger ones in both groups (CI, NH), but larger differences occurred in children with CI. The interactions between familiarization of the software, age, hearing status and demographic characteristics are discussed. Overall, the VR game is a promising tool for tracking the development of auditory skills, as it provides multi-level longitudinal empirical data. Acknowledgment: This work is part of a project that has received funding from the Research Committee of the University of Macedonia under the Basic Research 2020-21 funding programme.

Keywords: VR serious games, auditory rehabilitation, auditory training, children with cochlear implants

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Authors: Pippa Sipanoun, Jo Wray, Kate Oulton, Faith Gibson

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Background: With rapidly evolving digital health innovation, there is a need for digital health transformation that is accessible and sustainable, that demonstrates utility for all stakeholders while maintaining data safety. Great Ormond Street Hospital for Children aimed to future-proof the hospital by transitioning to an electronic patient record (EPR) system with a tethered patient portal (MyGOSH) in April 2019. MyGOSH patient portal enables patients 12 years or older (with their parent's consent) to access their digital health data. This includes access to results, documentation, and appointments that facilitate communication with their care team. As part of the Going Digital Study conducted between 2018-2021, data were collected from a sample of all relevant stakeholders before and after EPR and MyGOSH implementation. Data collection reach was wide and included the hospital legal and ethics teams. Aims: This study aims to understand the ethical and legal implications of young people and their parents accessing their digital health data. Methods: A focus group was conducted. Recruited participants were members of the Great Ormond Street Hospital Paediatric Bioethics Centre. Participants included expert and lay members from the Committee from a variety of professional or academic disciplines. Written informed consent was provided by all participants (n=7). The focus group was recorded, transcribed verbatim, and analyzed using thematic analysis. Results: Six themes were identified: access, competence and capacity - granting access to the system; inequalities in access resulting in inequities; burden, uncertainty and responding to change - managing expectations; documenting, risks and data safety; engagement, empowerment and understanding – how to use and manage personal information; legal considerations and obligations. Discussion: If healthcare professionals are to empower young people to be more engaged in their care, the importance of including them in decisions about their health is paramount, especially when they are approaching the age of becoming the consenter for treatment. Complexities exist in assessing competence or capacity when granting system access, when disclosing sensitive information, and maintaining confidentiality. Difficulties are also present in managing clinician burden, managing user expectations whilst providing an equitable service, and data management that meets professional and legal requirements. Conclusion: EPR and tethered-portal implementation at Great Ormond Street Hospital for Children was not only timely, due to the need for a rapid transition to remote consultations during the COVID-19 pandemic, which would not have been possible had EPR/MyGOSH not been implemented, but also integral to the digital health revolution required in healthcare today. This study is highly relevant in understanding the complexities around young people and their parents accessing their digital health data and, although the focus of this research related to portal use and access, the findings translate to young people in the wider digital health context. Ongoing support is required for all relevant stakeholders following MyGOSH patient portal implementation to navigate the ethical and legal complexities. Continued commitment is needed to balance the benefits and burdens, promote inclusion and equity, and ensure portal utility for patient benefit, whilst maintaining an individualized approach to care.

Keywords: patient portal, young people and their parents, ethical, legal

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Authors: Zoe Lynch, Kirsty Zieschank

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There are several factors that compromise the utility and wide-spread use of existing emotional and behavioural distress screening instruments. Some of these factors include lengthy administration times, high costs, feasibility issues, and a lack of self-report options for children under 12 years of age. This animation-based resource was developed to overcome as many of these factors as possible. Developed for educators and medical and mental health professionals, this resource offers children a self-guided mechanism for reporting any current emotional and behavioural distress. An avatar assistant, selected by the child, accompanies them through each stage of the screening process, offering further instruction if prompted. Children enter their age and gender before viewing comparative animations conveying common childhood emotional and behavioural difficulties. The child then selects the most relatable animations, along with the frequency with which they experience the depicted emotions. From a perspective of intellectual development, an engaging, animated format means that outcomes will not be constrained by children’s reading, writing, cognitive, or verbal expression abilities. Having been user-tested with children aged 6 to 12, this resource shows promising results as a self-guided screening instrument.

Keywords: animation-based screening instrument, mental health, primary-aged children, self-guided

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Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

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With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver.

Keywords: internet of things, iot, connected vehicle, cv, ts, telematics services, ml, machine learning

Procedia PDF Downloads 275

Authors: Silvana Caglieri

Abstract:

Theoretical study of acetylation of p-methylaniline catalyzed by Cu2+ ions from the analysis of intermediate of the reaction was carried out. The study of acetylation of amines is of great interest by the utility of its products of reaction and is one of the most frequently used transformations in organic synthesis as it provides an efficient and inexpensive means for protecting amino groups in a multistep synthetic process. Acetylation of amine is a nucleophilic substitution reaction. This reaction can be catalyzed by Lewis acid, metallic ion. In reaction mechanism, the metallic ion formed a complex with the oxygen of the acetic anhydride carbonyl, facilitating the polarization of the same and the successive addition of amine at the position to form a tetrahedral intermediate, determining step of the rate of the reaction. Experimental work agreed that this reaction takes place with the formation of a tetrahedral intermediate. In the present theoretical work were investigated the structure and energy of the tetrahedral intermediate of the reaction catalyzed by Cu2+ ions. Geometries of all species involved in the acetylation were made and identified. All of the geometry optimizations were performed by the method at the DFT/B3LYP level of theory and the method MP2. Were adopted the 6-31+G* basis sets. Energies were calculated using the Mechanics-UFF method. Following the same procedure it was identified the geometric parameters and energy of reaction intermediate. The calculations show 61.35 kcal/mol of energy for the tetrahedral intermediate and the energy of activation for the reaction was 15.55 kcal/mol.

Keywords: amides, amines, DFT, MP2

Procedia PDF Downloads 253

Authors: Amir Andria Gad Shehata

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

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