Search results for: rainfall variability coefficient

Authors: Yan-Shen Yang, Bai-Chen Xie

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Background and significance of the study: Both green power trading schemes and interregional power transmission are effective ways to increase green power absorption and achieve renewable power development goals. China accelerates the construction of interregional power transmission lines and the green power market. A critical issue focusing on the close interaction between these two approaches arises, which can heavily affect the green power quota allocation and renewable power development. Existing studies have not discussed this issue adequately, so it is urgent to figure out their relationship to achieve a suitable power market design and a more reasonable power grid construction.Basic methodologies: We develop an equilibrium model of the power market in China to analyze the coupling effect of these two approaches as well as their influence on power generation and interregional transmission in China. Our model considers both the Tradable green certificate (TGC) and green power market, which consists of producers, consumers in the market, and an independent system operator (ISO) minimizing the total system cost. Our equilibrium model includes the decision optimization process of each participant. To reformulate the models presented as a single-level one, we replace the producer, consumer, ISO, and market equilibrium problems with their Karush-Kuhn-Tucker (KKT) conditions, which is further reformulated as a mixed-integer linear programming (MILP) and solved in Gurobi solver. Major findings: The result shows that: (1) the green power market can significantly promote renewable power absorption while the TGC market provides a more flexible way for green power trading. (2) The phenomena of inefficient occupation and no available transmission lines appear simultaneously. The existing interregional transmission lines cannot fully meet the demand for wind and solar PV power trading in some areas while the situation is vice versa in other areas. (3) Synchronous implementation of green power and TGC trading mechanism can benefit the development of green power as well as interregional power transmission. (4) The green power transaction exacerbates the unfair distribution of carbon emissions. The Carbon Gini Coefficient is up to 0.323 under the green power market which shows a high Carbon inequality. The eastern coastal region will benefit the most due to its huge demand for external power.

Keywords: green power market, tradable green certificate, interregional power transmission, power market equilibrium model

Procedia PDF Downloads 104

Authors: Abdullah Al Mohiuddin

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Bangladesh is one of the poorest countries in the world, and ranks low on almost all measures of economic development, thus leaving the population extremely vulnerable to natural disasters and climate events. 20% of GDP come from agriculture but more than 60% of the population relies on agriculture as their main source of income making the entire economy vulnerable to climate change and natural disasters. High population density exacerbates the exposure to and effect of climate events, and increases the levels of vulnerability, as does the poor institutional development of the country. The most vulnerable sectors to climate change impacts in Bangladesh are agriculture, coastal zones, water resources, forestry, fishery, health, biomass, and energy. High temperatures, heavy rainfall, high humidity and fairly marked seasonal variations characterize the climate in Bangladesh: Mild winter, hot humid summer and humid, warm rainy monsoon. Much of the country is flooded during the summer monsoon. The Department of Environment (DOE) under the Ministry of Environment and Forestry (MoEF) is the focal point for the United Nations Framework Convention on Climate Change (UNFCCC) and coordinates climate related activities in the country. Recently, a Climate Change Cell (CCC) has been established to address several issues including adaptation to climate change. The climate change focus started with The National Environmental Management Action Plan (NEMAP) which was prepared in 1995 in order to initiate the process to address environmental and climate change issues as long-term environmental problems for Bangladesh. Bangladesh was one of the first countries to finalise a NAPA (Preparation of a National Adaptation Plan of Action) which addresses climate change issues. The NAPA was completed in 2005, and is the first official initiative for mainstreaming adaptation to national policies and actions to cope with climate change and vulnerability. The NAPA suggests a number of adaptation strategies, for example: - Providing drinking water to coastal communities to fight the enhanced salinity caused by sea level rise, - Integrating climate change in planning and design of infrastructure, - Including climate change issues in education, - Supporting adaptation of agricultural systems to new weather extremes, - Mainstreaming CCA into policies and programmes in different sectors, e.g. disaster management, water and health, - Dissemination of CCA information and awareness raising on enhanced climate disasters, especially in vulnerable communities. Bangladesh has geared up its environment conservation steps to save the world’s poorest countries from the adverse effects of global warming. Now it is turning towards green economy policies to save the degrading ecosystem. Bangladesh is a developing country and always fights against Natural Disaster. At the same time we also fight for establishing ecological environment through promoting Green Economy/Energy by Youth Networking. ANTAR is coordinating a big Youth Network in the southern part of Bangladesh where 30 Youth group involved. It can be explained as the economic development based on sustainable development which generates growth and improvement in human’s lives while significantly reducing environmental risks and ecological scarcities. Green economy in Bangladesh promotes three bottom lines – sustaining economic, environment and social well-being.

Keywords: resilience, networking, mobilizing, resource

Procedia PDF Downloads 285

Authors: Massimiliano Biagini, Marco Spinsanti, Gabriella De Angelis, Sara Tomei, Ilaria Ferlenghi, Maria Scarselli, Alessia Biolchi, Alessandro Muzzi, Brunella Brunelli, Silvana Savino, Marzia M. Giuliani, Isabel Delany, Paolo Costantino, Rino Rappuoli, Vega Masignani, Nathalie Norais

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The gram-negative bacterium Neisseria meningitidis serogroup B (MenB) is an exclusively human pathogen representing the major cause of meningitides and severe sepsis in infants and children but also in young adults. This pathogen is usually present in the 30% of healthy population that act as a reservoir, spreading it through saliva and respiratory fluids during coughing, sneezing, kissing. Among surface-exposed protein components of this diplococcus, factor H binding protein is a lipoprotein proved to be a protective antigen used as a component of the recently licensed Bexsero vaccine. fHbp is a highly variable meningococcal protein: to reflect its remarkable sequence variability, it has been classified in three variants (or two subfamilies), and with poor cross-protection among the different variants. Furthermore, the level of fHbp expression varies significantly among strains, and this has also been considered an important factor for predicting MenB strain susceptibility to anti-fHbp antisera. Different methods have been used to assess fHbp expression on meningococcal strains, however, all these methods use anti-fHbp antibodies, and for this reason, the results are affected by the different affinity that antibodies can have to different antigenic variants. To overcome the limitations of an antibody-based quantification, we developed a quantitative Mass Spectrometry (MS) approach. Selected Reaction Monitoring (SRM) recently emerged as a powerful MS tool for detecting and quantifying proteins in complex mixtures. SRM is based on the targeted detection of ProteoTypicPeptides (PTPs), which are unique signatures of a protein that can be easily detected and quantified by MS. This approach, proven to be highly sensitive, quantitatively accurate and highly reproducible, was used to quantify the absolute amount of fHbp antigen in total extracts derived from 105 clinical isolates, evenly distributed among the three main variant groups and selected to be representative of the fHbp circulating subvariants around the world. We extended the study at the genetic level investigating the correlation between the differential level of expression and polymorphisms present within the genes and their promoter sequences. The implications of fHbp expression on the susceptibility of the strain to killing by anti-fHbp antisera are also presented. To date this is the first comprehensive fHbp expression profiling in a large panel of Neisseria meningitidis clinical isolates driven by an antibody-independent MS-based methodology, opening the door to new applications in vaccine coverage prediction and reinforcing the molecular understanding of released vaccines.

Keywords: quantitative mass spectrometry, Neisseria meningitidis, vaccines, bexsero, molecular epidemiology

Procedia PDF Downloads 282

Authors: Zena F. Mushtaq, Iqbal M. Abbas

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Background: Diabetes mellitus during pregnancy is one of the major medical and social problems with increasing prevalence in last decades and may lead to more vulnerable to dental problems and increased risk for periodontal diseases. Objectives: To assess oral hygiene behaviors among pregnant women with diabetes who attended primary health care centers and find out the relationship between oral hygiene behaviors and studied variables. Methodology: A cross sectional design was conducted from 7 July to 30 September 2014 on non probability (convenient sample) of 150 pregnant women with diabetes was selected from twelve Primary Health Care Centers at Baghdad city. Questionnaire format is tool for data collection which had designed and consisted of three main parts including: socio demographic, reproductive characteristics and items of oral hygiene behaviors among pregnant women with diabetes. Reliability of the questionnaire was determined through internal consistency of correlation coefficient (R= 0.940) and validity of content was determined through reviewing it by (12) experts in different specialties and was determined through pilot study. Descriptive and inferential statistics were used to analyze collected data. Result: Result of study revealed that (35.3%) of study sample was (35-39) years old with mean and SD is (X & SD = 33.57 ± 5.54) years, and (34.7%) of the study sample was graduated from primary school and less, half of the study sample was government employment and self employed, (42.7%) of the study sample had moderate socioeconomic status, the highest percentage (70.0%) of the study sample was nonsmokers, The result indicates that oral hygiene behaviors have moderate mean score in all items. There are no statistical significant association between oral hygiene domain and studied variables. Conclusions: All items related to health behavior concerning oral hygiene is in moderate mean of score, which may expose pregnant women with diabetes to high risk of periodontal diseases. Recommendations: Dental care provider should perform a dental examination at least every three months for each pregnant woman with diabetes, explanation of the effect of DM on periodontal health, oral hygiene instruction, oral prophylaxis, professional cleaning and treatment of periodontal diseases(scaling and root planing) when needed.

Keywords: diabetes, health behavior, pregnant women, oral hygiene

Procedia PDF Downloads 262

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

Procedia PDF Downloads 364

Authors: Jagannath Koravadi, Archith Gupta

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In a world with constantly growing energy prices, and growing concerns about the global climate changes caused by increased energy consumption, it is becoming more and more essential to save energy wherever possible. Refrigeration systems are one of the major and bulk energy consuming systems now-a-days in industrial sectors, residential sectors and household environment. Refrigeration systems with considerable cooling requirements consume a large amount of electricity and thereby contribute greatly to the running costs. Therefore, a great deal of attention is being paid towards improvement of the performance of the refrigeration systems in this regard throughout the world. The Coefficient of Performance (COP) of a refrigeration system is used for determining the system's overall efficiency. The operating cost to the consumer and the overall environmental impact of a refrigeration system in turn depends on the COP or efficiency of the system. The COP of a refrigeration system should therefore be as high as possible. Slight modifications in the technical elements of the modern refrigeration systems have the potential to reduce the energy consumption, and improvements in simple operational practices with minimal expenses can have beneficial impact on COP of the system. Thus, the challenge is to determine the changes that can be made in a refrigeration system in order to improve its performance, reduce operating costs and power requirement, improve environmental outcomes, and achieve a higher COP. The opportunity here, and a better solution to this challenge, will be to incorporate modifications in conventional refrigeration systems for saving energy. Energy efficiency, in addition to improvement of COP, can deliver a range of savings such as reduced operation and maintenance costs, improved system reliability, improved safety, increased productivity, better matching of refrigeration load and equipment capacity, reduced resource consumption and greenhouse gas emissions, better working environment, and reduced energy costs. The present work aims at fabricating a working model of a refrigerator that will provide for effective heat recovery from superheated refrigerant with the help of an efficient de-superheater. The temperature of the refrigerant and water in the de-super heater at different intervals of time are measured to determine the quantity of waste heat recovered. It is found that the COP of the system improves by about 6% with the de-superheater and the power input to the compressor decreases by 4 % and also the refrigeration capacity increases by 4%.

Keywords: coefficiency of performance, de-superheater, refrigerant, refrigeration capacity, heat recovery

Procedia PDF Downloads 303

Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu

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Sesame is an important oilseed crop in Ethiopia, which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool, which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validate the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates, 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99, and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99 and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, normalized water productivity, nitrogen fertilizer, canopy cover, sesame

Procedia PDF Downloads 43

Authors: Suguru Miyauchi, Toshiyuki Hayase

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Biological membranes have selective permeability, and the capsules or cells enclosed by the membrane show the deformation by the osmotic flow. This mass transport phenomenon is observed everywhere in a living body. For the understanding of the mass transfer in a body, it is necessary to consider the mass transfer phenomenon across the membrane as well as the deformation of the membrane by a flow. To our knowledge, in the numerical analysis, the method for mass transfer across the moving membrane has not been established due to the difficulty of the treating of the mass flux permeating through the moving membrane with selective permeability. In the existing methods for the mass transfer across the membrane, the approximate delta function is used to communicate the quantities on the interface. The methods can reproduce the permeation of the solute, but cannot reproduce the non-permeation. Moreover, the computational accuracy decreases with decreasing of the permeable coefficient of the membrane. This study aims to develop the numerical method capable of treating three-dimensional problems of mass transfer across the moving flexible membrane. One of the authors developed the numerical method with high accuracy based on the finite element method. This method can capture the discontinuity on the membrane sharply due to the consideration of the jumps in concentration and concentration gradient in the finite element discretization. The formulation of the method takes into account the membrane movement, and both permeable and non-permeable membranes can be treated. However, searching the cross points of the membrane and fluid element boundaries and splitting the fluid element into sub-elements are needed for the numerical integral. Therefore, cumbersome operation is required for a three-dimensional problem. In this paper, we proposed an improved method to avoid the search and split operations, and confirmed its effectiveness. The membrane shape was treated implicitly by introducing the level set function. As the construction of the level set function, the membrane shape in one fluid element was expressed by the shape function of the finite element method. By the numerical experiment, it was found that the shape function with third order appropriately reproduces the membrane shapes. The same level of accuracy compared with the previous method using search and split operations was achieved by using a number of sampling points of the numerical integral. The effectiveness of the method was confirmed by solving several model problems.

Keywords: finite element method, level set method, mass transfer, membrane permeability

Procedia PDF Downloads 228

Authors: Yusuf Yilmaz, Gamze Gediz Ilis

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Gas Nitrogen where has a boiling point of -189.52oC at atmospheric pressure widely used in the industry. Nitrogen that used in the industry should be transported in liquid form to the plant area. Ambient air vaporizer (AAV) generally used for vaporization of cryogenic gases such as liquid nitrogen (LN2), liquid oxygen (LOX), liquid natural gas (LNG), and liquid argon (LAR) etc. AAV is a group of star-shaped fin vaporizer. The design and the effect of the shape of fins of the vaporizer is one of the most important criteria for the performance of the vaporizer. In this study, the performance of AAV working with liquid nitrogen was analyzed numerically in a star-shaped aluminum finned pipe. The numerical analysis is performed in order to investigate the heat capacity of the vaporizer per meter pipe length. By this way, the vaporizer capacity can be predicted for the industrial applications. In order to achieve the validation of the numerical solution, the experimental setup is constructed. The setup includes a liquid nitrogen tank with a pressure of 9 bar. The star-shaped aluminum finned tube vaporizer is connected to the LN2 tank. The inlet and the outlet pressure and temperatures of the LN2 of the vaporizer are measured. The mass flow rate of the LN2 is also measured and collected. The comparison of the numerical solution is performed by these measured data. The ambient conditions of the experiment are given as boundary conditions to the numerical model. The surface tension and contact angle have a significant effect on the boiling of liquid nitrogen. Average heat transfer coefficient including convective and nucleated boiling components should be obtained for liquid nitrogen saturated flow boiling in the finned tube. Fluent CFD module is used to simulate the numerical solution. The turbulent k-ε model is taken to simulate the liquid nitrogen flow. The phase change is simulated by using the evaporation-condensation approach used with user-defined functions (UDF). The comparison of the numerical and experimental results will be shared in this study. Besides, the performance capacity of the star-shaped finned pipe vaporizer will be calculated in this study. Based on this numerical analysis, the performance of the vaporizer per unit length can be predicted for the industrial applications and the suitable pipe length of the vaporizer can be found for the special cases.

Keywords: liquid nitrogen, numerical modeling, two-phase flow, cryogenics

Procedia PDF Downloads 95

Authors: T. C. C. Soo, S. Bhassu

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Unlike the common presence of both innate and adaptive immunity in vertebrates, crustaceans, in particular, shrimps, have been discovered to possess only innate immunity. This further emphasizes the importance of innate immunity within shrimps in pathogenic resistance. Under the study of pathogenic immune challenge, different shrimp species actually exhibit varying degrees of immune resistance towards the same pathogen. Furthermore, even within the same shrimp species, different batches of challenged shrimps can have different strengths of immune defence. Several important pathways are activated within shrimps during pathogenic infection. One of them is JAK-STAT pathway that is activated during bacterial, viral and fungal infections by which STAT(Signal Transducer and Activator of Transcription) gene is the core element of the pathway. Based on theory of Central Dogma, the genomic information is transmitted in the order of DNA, RNA and protein. This study is focused in uncovering the important evolutionary patterns present within the DNA (non-coding region) and RNA (coding region). The three shrimp species involved are Macrobrachium rosenbergii, Penaeus monodon and Litopenaeus vannamei which all possess commercial significance. The shrimp species were challenged with a famous penaeid shrimp virus called white spot syndrome virus (WSSV) which can cause serious lethality. Tissue samples were collected during time intervals of 0h, 3h, 6h, 12h, 24h, 36h and 48h. The DNA and RNA samples were then extracted using conventional kits from the hepatopancreas tissue samples. PCR technique together with designed STAT gene conserved primers were utilized for identification of the STAT coding sequences using RNA-converted cDNA samples and subsequent characterization using various bioinformatics approaches including Ramachandran plot, ProtParam and SWISS-MODEL. The varying levels of immune STAT gene activation for the three shrimp species during WSSV infection were confirmed using qRT-PCR technique. For one sample, three biological replicates with three technical replicates each were used for qRT-PCR. On the other hand, DNA samples were important for uncovering the structural variations within the genomic region of STAT gene which would greatly assist in understanding the STAT protein functional variations. The partially-overlapping primers technique was used for the genomic region sequencing. The evolutionary inferences and event predictions were then conducted through the Bayesian Inference method using all the acquired coding and non-coding sequences. This was supplemented by the construction of conventional phylogenetic trees using Maximum likelihood method. The results showed that adaptive evolution caused STAT gene sequence mutations between different shrimp species which led to evolutionary divergence event. Subsequently, the divergent sites were correlated to the differing expressions of STAT gene. Ultimately, this study assists in knowing the shrimp species innate immune variability and selection of disease resistant shrimps for breeding purpose. The deeper understanding of STAT gene evolution from the perspective of both purifying and adaptive approaches not only can provide better immunological insight among shrimp species, but also can be used as a good reference for immunological studies in humans or other model organisms.

Keywords: gene evolution, JAK-STAT pathway, immunology, STAT gene

Procedia PDF Downloads 126

Authors: Julio Silva, Lia Hasenclever, Gilson G. Silva Jr.

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The aim of this paper is to check possible convergence in health measures (aged-standard rate of morbidity and mortality) for communicable diseases between developed and developing countries, conditional to productive structures features. Understanding the interrelations between health patterns and economic development is particularly important in the context of low- and middle-income countries, where economic development comes along with deep social inequality. Developing countries with less diversified productive structures (measured through complexity index) but high heterogeneous inter-sectorial labor productivity (using as a proxy inter-sectorial coefficient of variation of labor productivity) has on average low health levels in communicable diseases compared to developed countries with high diversified productive structures and low labor market heterogeneity. Structural heterogeneity and productive diversification may have influence on health levels even considering per capita income. We set up a panel data for 139 countries from 1995 to 2015, joining several data about the countries, as economic development, health, and health system coverage, environmental and socioeconomic aspects. This information was obtained from World Bank, International Labour Organization, Atlas of Economic Complexity, United Nation (Development Report) and Institute for Health Metrics and Evaluation Database. Econometric panel models evidence shows that the level of communicable diseases has a positive relationship with structural heterogeneity, even considering other factors as per capita income. On the other hand, the recent process of convergence in terms of communicable diseases have been motivated for other reasons not directly related to productive structure, as health system coverage and environmental aspects. These evidences suggest a joint dynamics between the unequal distribution of communicable diseases and countries' productive structure aspects. These set of evidence are quite important to public policy as meet the health aims in Millennium Development Goals. It also highlights the importance of the process of structural change as fundamental to shift the levels of health in terms of communicable diseases and can contribute to the debate between the relation of economic development and health patterns changes.

Keywords: economic development, inequality, population health, structural change

Procedia PDF Downloads 109

Authors: Palash Soni, Vivek Kumar Gaba, Shubhankar Bhowmick, Bidyut Mazumdar

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Refrigeration technology is a fast developing field at the present era since it has very wide application in both domestic and industrial areas. It started from the usage of simple ice coolers to store food stuffs to the present sophisticated cold storages along with other air conditioning system. A variety of techniques are used to bring down the temperature below the ambient. Adsorption refrigeration technology is a novel, advanced and promising technique developed in the past few decades. It gained attention due to its attractive property of exploiting unlimited natural sources like solar energy, geothermal energy or even waste heat recovery from plants or from the exhaust of locomotives to fulfill its energy need. This will reduce the exploitation of non-renewable resources and hence reduce pollution too. This work is aimed to develop a model for a solar adsorption refrigeration system and to simulate the same for different operating conditions. In this system, the mechanical compressor is replaced by a thermal compressor. The thermal compressor uses renewable energy such as solar energy and geothermal energy which makes it useful for those areas where electricity is not available. Refrigerants normally in use like chlorofluorocarbon/perfluorocarbon have harmful effects like ozone depletion and greenhouse warming. It is another advantage of adsorption systems that it can replace these refrigerants with less harmful natural refrigerants like water, methanol, ammonia, etc. Thus the double benefit of reduction in energy consumption and pollution can be achieved. A thermodynamic model was developed for the proposed adsorber, and a universal MATLAB code was used to simulate the model. Simulations were carried out for a different operating condition for the silicagel-methanol working pair. Various graphs are plotted between regeneration temperature, adsorption capacities, the coefficient of performance, desorption rate, specific cooling power, adsorption/desorption times and mass. The results proved that adsorption system could be installed successfully for refrigeration purpose as it has saving in terms of power and reduction in carbon emission even though the efficiency is comparatively less as compared to conventional systems. The model was tested for its compliance in a cold storage refrigeration with a cooling load of 12 TR.

Keywords: adsorption, refrigeration, renewable energy, silicagel-methanol

Procedia PDF Downloads 183

Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

Procedia PDF Downloads 320

Authors: X. Simon, D. Copena, M. Montero

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The last decades have witnessed a significant increase in renewable energy, especially wind energy, to achieve sustainable development. Specialized literature in this field has carried out interesting case studies to extensively analyze both the environmental benefits of this energy and its social acceptance. However, to the best of our knowledge, work to date makes no analysis of the role of private owners of lands with wind potential within a broader territory of strong wind implantation, nor does it estimate their economic incomes relating them to social acceptance. This work fills this gap by focusing on Galicia, territory housing over 4,000 wind turbines and almost 3,400 MW of power. The main difficulty in getting this financial information is that it is classified, not public. We develop methodological techniques (semi- structured interviews and work groups), inserted within the Participatory Research, to overcome this important obstacle. In this manner, the work directly compiles qualitative and quantitative information on the processes as well as the economic results derived from implementing wind energy in Galicia. During the field work, we held 106 semi-structured interviews and 32 workshops with owners of lands occupied by wind farms. The compiled information made it possible to create the socioeconomic database on wind energy in Galicia (SDWEG). This database collects a diversity of quantitative and qualitative information and contains economic information on the income received by the owners of lands occupied by wind farms. In the Galician case, regulatory framework prevented local participation under the community wind farm formula. The possibility of local participation in the new energy model narrowed down to companies wanting to install a wind farm and demanding land occupation. The economic mechanism of local participation begins here, thus explaining the level of acceptance of wind farms. Land owners can receive significant income given that these payments constitute an important source of economic resources, favor local economic activity, allow rural areas to develop productive dynamism projects and improve the standard of living of rural inhabitants. This work estimates that land owners in Galicia perceive about 10 million euros per year in total wind revenues. This represents between 1% and 2% of total wind farm invoicing. On the other hand, relative revenues (Euros per MW), far from the amounts reached in other spaces, show enormous payment variability. This signals the absence of a regulated market, the predominance of partial agreements, and the existence of asymmetric positions between owners and developers. Sustainable development requires the replacement of conventional technologies by low environmental impact technologies, especially those that emit less CO₂. However, this new paradigm also requires rural owners to participate in the income derived from the structural transformation processes linked to sustainable development. This paper demonstrates that regulatory framework may contribute to increasing sustainable technologies with high social acceptance without relevant local economic participation.

Keywords: regulatory framework, social acceptance, sustainable development, wind energy, wind income for landowners

Procedia PDF Downloads 124

Authors: Zbigniew Czyż, Adam Majczak, Lukasz Grabowski

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The paper presents a description of geometric models, computational algorithms, and results of numerical analyses of charge exchange in a two-stroke opposed-piston engine. The research engine was a newly designed internal Diesel engine. The unit is characterized by three cylinders in which three pairs of opposed-pistons operate. The engine will generate a power output equal to 100 kW at a crankshaft rotation speed of 3800-4000 rpm. The numerical investigations were carried out using ANSYS FLUENT solver. Numerical research, in contrast to experimental research, allows us to validate project assumptions and avoid costly prototype preparation for experimental tests. This makes it possible to optimize the geometrical model in countless variants with no production costs. The geometrical model includes an intake manifold, a cylinder, and an outlet manifold. The study was conducted for a series of modifications of manifolds and intake and exhaust ports to optimize the charge exchange process in the engine. The calculations specified a swirl coefficient obtained under stationary conditions for a full opening of intake and exhaust ports as well as a CA value of 280° for all cylinders. In addition, mass flow rates were identified separately in all of the intake and exhaust ports to achieve the best possible uniformity of flow in the individual cylinders. For the models under consideration, velocity, pressure and streamline contours were generated in important cross sections. The developed models are designed primarily to minimize the flow drag through the intake and exhaust ports while the mass flow rate increases. Firstly, in order to calculate the swirl ratio [-], tangential velocity v [m/s] and then angular velocity ω [rad / s] with respect to the charge as the mean of each element were calculated. The paper contains comparative analyses of all the intake and exhaust manifolds of the designed engine. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: computational fluid dynamics, engine swirl, fluid mechanics, mass flow rates, numerical analysis, opposed-piston engine

Procedia PDF Downloads 180

Authors: Bharti Jain, Rajeev Jain, Abuzar Kabir, Torki Zughaibi, Shweta Sharma

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Drug-facilitated crimes (DFCs) entail the use of a single drug or a mixture of drugs to render a victim unable. Traditionally, biological samples have been gathered from victims and conducted analysis to establish evidence of drug administration. Nevertheless, the rapid metabolism of various drugs and delays in analysis can impede the identification of such substances. For this, the present article describes a rapid, sustainable, highly efficient and miniaturized protocol for the identification and quantification of three sedative-hypnotic drugs, namely diazepam, chlordiazepoxide and ketamine in alcoholic beverages and complex food samples (cream of biscuit, flavored milk, juice, cake, tea, sweets and chocolate). The methodology involves utilizing fabric phase sorptive extraction (FPSE) to extract diazepam (DZ), chlordiazepoxide (CDP), and ketamine (KET). Subsequently, the extracted samples are subjected to analysis using gas chromatography-mass spectrometry (GC-MS). Several parameters, including the type of membrane, pH, agitation time and speed, ionic strength, sample volume, elution volume and time, and type of elution solvent, were screened and thoroughly optimized. Sol-gel Carbowax 20M (CW-20M) has demonstrated the most effective extraction efficiency for the target analytes among all evaluated membranes. Under optimal conditions, the method displayed linearity within the range of 0.3–10 µg mL–¹ (or µg g–¹), exhibiting a coefficient of determination (R2) ranging from 0.996–0.999. The limits of detection (LODs) and limits of quantification (LOQs) for liquid samples range between 0.020-0.069 µg mL-¹ and 0.066-0.22 µg mL-¹, respectively. Correspondingly, the LODs for solid samples ranged from 0.056-0.090 µg g-¹, while the LOQs ranged from 0.18-0.29 µg g-¹. Notably, the method showcased better precision, with repeatability and reproducibility both below 5% and 10%, respectively. Furthermore, the FPSE-GC-MS method proved effective in determining diazepam (DZ) in forensic food samples connected to drug-facilitated crimes (DFCs). Additionally, the proposed method underwent evaluation for its whiteness using the RGB12 algorithm.

Keywords: drug facilitated crime, fabric phase sorptive extraction, food forensics, white analytical chemistry

Procedia PDF Downloads 43

Authors: Susan Ka Yee Chow

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Effective clinical preceptorship is affecting students’ competence and fostering their growth in applying theoretical knowledge and skills in clinical settings. Any difference between the expected and actual learning experience will reduce nursing students’ interest in clinical practices and having a negative consequence with their clinical performance. This cross-sectional study is an attempt to compare the differences between preferred and actual preceptorship experience of final year nursing students, and to examine the relationship between the actual preceptorship experience and perceived clinical competence of the students in a tertiary institution. Participants of the study were final year bachelor nursing students of a self-financing tertiary institution in Hong Kong. The instruments used to measure the effectiveness of clinical preceptorship was developed by the participating institution. The scale consisted of five items in a 5-point likert scale. The questions including goals development, critical thinking, learning objectives, asking questions and providing feedback to students. The “Clinical Competence Questionnaire” by Liou & Cheng (2014) was used to examine students’ perceived clinical competences. The scale consisted of 47 items categorized into four domains, namely nursing professional behaviours; skill competence: general performance; skill competence: core nursing skills and skill competence: advanced nursing skills. There were 193 questionnaires returned with a response rate of 89%. The paired t-test was used to compare the differences between preferred and actual preceptorship experiences of students. The results showed significant differences (p<0.001) for the five questions. The mean for the preferred scores is higher than the actual scores resulting statistically significance. The maximum mean difference was accepted goal and the highest mean different was giving feedback. The Pearson Correlation Coefficient was used to examine the relationship. The results showed moderate correlations between nursing professional behaviours with asking questions and providing feedback. Providing useful feedback to students is having moderate correlations with all domains of the Clinical Competence Questionnaire (r=0.269 – 0.345). It is concluded that nursing students do not have a positive perception of the clinical preceptorship. Their perceptions are significantly different from their expected preceptorship. If students were given more opportunities to ask questions in a pedagogical atmosphere, their perceived clinical competence and learning outcomes could be improved as a result.

Keywords: clinical preceptor, clinical competence, clinical practicum, nursing students

Procedia PDF Downloads 104

Authors: Saeed Farivar, Mohsen Kahrom

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The purpose of this work is to develop a physical simulation model for the purpose of studying the effect of various design parameters on the performance of packaged-liquid chillers. This paper presents a steady-state model for predicting the performance of package-Liquid chiller over a wide range of operation condition. The model inputs are inlet conditions; geometry and output of model include system performance variable such as power consumption, coefficient of performance (COP) and states of refrigerant through the refrigeration cycle. A computer model that simulates the steady-state cyclic performance of a vapor compression chiller is developed for the purpose of performing detailed physical design analysis of actual industrial chillers. The model can be used for optimizing design and for detailed energy efficiency analysis of packaged liquid chillers. The simulation model takes into account presence of all chiller components such as compressor, shell-and-tube condenser and evaporator heat exchangers, thermostatic expansion valve and connection pipes and tubing’s by thermo-hydraulic modeling of heat transfer, fluids flow and thermodynamics processes in each one of the mentioned components. To verify the validity of the developed model, a 7.5 USRT packaged-liquid chiller is used and a laboratory test stand for bringing the chiller to its standard steady-state performance condition is build. Experimental results obtained from testing the chiller in various load and temperature conditions is shown to be in good agreement with those obtained from simulating the performance of the chiller using the computer prediction model. An entropy-minimization-based optimization analysis is performed based on the developed analytical performance model of the chiller. The variation of design parameters in construction of shell-and-tube condenser and evaporator heat exchangers are studied using the developed performance and optimization analysis and simulation model and a best-match condition between the physical design and construction of chiller heat exchangers and its compressor is found to exist. It is expected that manufacturers of chillers and research organizations interested in developing energy-efficient design and analysis of compression chillers can take advantage of the presented study and its results.

Keywords: optimization, packaged liquid chiller, performance, simulation

Procedia PDF Downloads 255

Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

Procedia PDF Downloads 291

Authors: Rahat Zaman

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The present study was conducted to investigate psychological well-being and positive and negative affect among adults. The sample comprised 221 adults; the sample was collected from all over Pakistan. Psychological well-being was measured with the help of the psychological well-being scale developed by Ryff and Keyes (1995). Lifestyle was measured with the help of the Health Promoting Lifestyle Profile Scale developed by Walker et al. (1995). Positive and negative effects were measured by PANAS, developed by Watson, Clark, and Tellegen (1998). To check the properties of scale, the alpha reliability coefficient was calculated. To test the hypotheses of the research, correlation, independent sample t-rest, and ANOVA were computed. It was hypothesized that there would be a positive relationship between psychological well-being and lifestyles and positive affect. The results show that psychological well-being, lifestyle, and positive affect are positively related. This also supports our hypothesis. The research also searched for relationships in the study variables according to the demographics of the sample. The respondents varied according to their dominant affect levels with respect to their psychological well-being and lifestyles. The research found significant differences for the genders in life appreciation, nutrition, and negative affect. Single and married individuals differed significantly on autonomy, environmental mastery, life appreciation, nutrition, and stress management. Individuals showed significant differences with respect to their living situation, joint and nuclear family members showed significant differences in personal growth, autonomy, health responsibilities, social support, physical activities, and stress management. The sample showed significant differences in environmental mastery, personal growth, purpose in life, life appreciation, health responsibilities, physical activities, stress management, and negative affect when divided in socioeconomic status. Age-wise analysis showed significant differences in autonomy, personal growth, purpose in life, life appreciation, nutrition, and stress management. Provincially significant differences were found in life appreciation, nutrition, social support, physical activities, and stress management, and both positive and negative effects were experienced. Implications of the results are discussed.

Keywords: wellbeing, healthy lifestyle, self acceptance, positive

Procedia PDF Downloads 44

Authors: Michelle Eliane Hernández-García, Angélica Lozano

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The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

Procedia PDF Downloads 113

Authors: Mahnaz Seyedoshohadaee

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Background and Aims: Hospitalization of one of the family members in the hospital, especially in the emergency department, causes anxiety and psychological problems in family members and others. The way nurses interact with patients and their companions can play an important role in controlling and managing their anxiety. This study aims to determine the relationship between the anxiety of family members of patients referring to emergency departments and their views on the communication skills of nurses. Materials and Methods: The current research was a descriptive-correlation cross-sectional study on 263 family members of patients referred to the department. The emergency of two selected medical training centers affiliated with Iran University of Medical Sciences was performed. The samples were selected continuously in 2018 based on the inclusion criteria. Information was collected using the Health Communication Questionnaire (HCCQ) and Beck Anxiety Questionnaire (BAI). To analyze the data, Pearson's correlation coefficient, independent t-tests, analysis of variance, and Kruskal-Wallis were used at a significance level of 0.05. The data was analyzed using SPSS version 16 statistical software. Results: The mean score of communication skills of emergency department nurses from the point of view of patients' companions was at a low level (74.36 with a standard deviation of 3.7). 3.75% of patients' companions had anxiety at a mild level. There was no statistically significant correlation between the anxieties of the patient's companions. The anxiety of the patient's companions had a statistically significant relationship with the educational level (P=0.039), economic status (P=0.033), and family relationship with the patient (P=0.001). Also, the average anxiety score in children was significantly higher than that of patients' wives (P=0.008). The triage level of the patient also had a statistically significant relationship with the anxiety of the patient's companions (P>0.001). Conclusion: Most of the family members of the patients referred to the emergency room experienced mild anxiety. Also, from their point of view, the communication skills of emergency nurses were at a weak level. Despite the fact that there was no statistically significant relationship between the patient's family member's anxiety and their opinion about nurses' communication skills in this study, it seems that the weak communication skills of nurses from the patient's family member's point of view need special attention. The results of the present study can provide the necessary grounds for planning to improve the communication skills of nurses and also control the anxiety of patient caregivers through in-service training or other incentive mechanisms.

Keywords: anxiety, family, emergency department, communication skills, nurse

Procedia PDF Downloads 33

Authors: Yuguang Gao, Mingtao Deng

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The integration of independently operating hospitals into a unified healthcare service system has become a strategic imperative in the pursuit of hospitals’ high-quality development. Central to the concept of group governance over such transformation, exemplified by a collaborative medical alliance, is the delineation of shared value, vision, and goals. Given the inherent disparity in capabilities among hospitals within the alliance, particularly in the treatment of different diseases characterized by Disease Related Groups (DRG) in terms of effectiveness, efficiency and resource utilization, this study aims to address the centralized decision-making of intra-hospital patient referral within the medical alliance to enhance the overall production and quality of service provided. We first introduce the notion of production utility, where a higher production utility for a hospital implies better performance in treating patients diagnosed with that specific DRG group of diseases. Then, a Discrete-Event Simulation (DES) framework is established for patient referral among hospitals, where patient flow modeling incorporates a queueing system with fixed capacities for each hospital. The simulation study begins with a two-member alliance. The pivotal strategy examined is a "whether-to-refer" decision triggered when the bed usage rate surpasses a predefined threshold for either hospital. Then, the decision encompasses referring patients to the other hospital based on DRG groups’ production utility differentials as well as bed availability. The objective is to maximize the total production utility of the alliance while minimizing patients’ average length of stay and turnover rate. Thus the parameter under scrutiny is the bed usage rate threshold, influencing the efficacy of the referral strategy. Extending the study to a three-member alliance, which could readily be generalized to multi-member alliances, we maintain the core setup while introducing an additional “which-to-refer" decision that involves referring patients with specific DRG groups to the member hospital according to their respective production utility rankings. The overarching goal remains consistent, for which the bed usage rate threshold is once again a focal point for analysis. For the two-member alliance scenario, our simulation results indicate that the optimal bed usage rate threshold hinges on the discrepancy in the number of beds between member hospitals, the distribution of DRG groups among incoming patients, and variations in production utilities across hospitals. Transitioning to the three-member alliance, we observe similar dependencies on these parameters. Additionally, it becomes evident that an imbalanced distribution of DRG diagnoses and further disparity in production utilities among member hospitals may lead to an increase in the turnover rate. In general, it was found that the intra-hospital referral mechanism enhances the overall production utility of the medical alliance compared to individual hospitals without partnership. Patients’ average length of stay is also reduced, showcasing the positive impact of the collaborative approach. However, the turnover rate exhibits variability based on parameter setups, particularly when patients are redirected within the alliance. In conclusion, the re-structuring of diagnostic disease groups within the medical alliance proves instrumental in improving overall healthcare service outcomes, providing a compelling rationale for the government's promotion of patient referrals within collaborative medical alliances.

Keywords: collaborative medical alliance, disease related group, patient referral, simulation

Procedia PDF Downloads 27

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

Procedia PDF Downloads 35

Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra

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Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.

Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP

Procedia PDF Downloads 40

Authors: A. Saghatelyan, Sh. Asmaryan, G. Tepanosyan, V. Muradyan

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One of major concern to Armenia has been soil degradation emerged as a result of unsustainable management and use of grasslands, this in turn largely impacting environment, agriculture and finally human health. Hence, assessment of soil degradation is an essential and urgent objective set out to measure its possible consequences and develop a potential management strategy. Since recently, an essential tool for assessing pasture degradation has been remote sensing (RS) technologies. This research was done with an intention to measure preciseness of Linear spectral unmixing (LSU) and NDVI-SMA methods to estimate soil surface components related to degradation (fractional vegetation cover-FVC, bare soils fractions, surface rock cover) and determine appropriateness of these methods for mapping man-induced soil degradation in high mountain pastures. Taking into consideration a spatially complex and heterogeneous biogeophysical structure of the studied site, we used high resolution multispectral QuickBird imagery of a pasture site in one of Armenia’s rural communities - Nerkin Sasoonashen. The accuracy assessment was done by comparing between the land cover abundance data derived through RS methods and the ground truth land cover abundance data. A significant regression was established between ground truth FVC estimate and both NDVI-LSU and LSU - produced vegetation abundance data (R2=0.636, R2=0.625, respectively). For bare soil fractions linear regression produced a general coefficient of determination R2=0.708. Because of poor spectral resolution of the QuickBird imagery LSU failed with assessment of surface rock abundance (R2=0.015). It has been well documented by this particular research, that reduction in vegetation cover runs in parallel with increase in man-induced soil degradation, whereas in the absence of man-induced soil degradation a bare soil fraction does not exceed a certain level. The outcomes show that the proposed method of man-induced soil degradation assessment through FVC, bare soil fractions and field data adequately reflects the current status of soil degradation throughout the studied pasture site and may be employed as an alternate of more complicated models for soil degradation assessment.

Keywords: Armenia, linear spectral unmixing, remote sensing, soil degradation

Procedia PDF Downloads 304

Authors: Muhammad Shafi’U Adamu

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This study examined the effects of two groups of Cognitive Behavioral Therapies (CBT) which, includes Cognitive Restructuring (CB) and Rational Emotive Behavioral Therapy (REBT), on the Psychological Distress of awaiting-trial Inmates in Correctional Centers in North-West Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centers in North-west Nigeria. 131 awaiting trial inmates from three intact Correctional Centers were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to a pilot study using Cronbach's Alpha with a reliability coefficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean scores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicated the posttreatment reduction of psychological distress in the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference in those exposed to REBT. The research recommends that a standardized structured CBT counseling technique treatment should be designed for correctional centers across Nigeria, and CBT counseling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centers, rational emotive behavioral therapy

Procedia PDF Downloads 49

Authors: Simona Dostalova, Dita Munzova, Ana Maria Jimenez Jimenez, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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The boom of nanomedicine in recent years has led to the development of numerous new nanomaterials that can be used as nanocarriers in the drug delivery. These nanocarriers can either be synthetic or natural-based. The disadvantage of many synthetic nanocarriers is their toxicity in patient’s body. Protein cages that can naturally be found in human body do not exhibit such disadvantage. However, the release of cargo from some protein cages in target cells can be problematic. As a special type of protein cages can serve the capsid of many viruses, including phage. Phages infect bacterial cells; therefore they are not harmful to human cells. The targeting of phage particles to cancer cells can be solved by producing of empty phage capsids during which the targeting moieties (e.g. peptides) can be cloned into genes of phage capsid to decorate its surface. Moreover, the produced capsids do not contain viral nucleic acid and are therefore not infectious to beneficial bacteria in the patient’s body. The protein cage composed of viral capsid is larger than other frequently used apoferritin cage but its size is still small enough to benefit from passive targeting by Enhanced Permeability and Retention effect. In this work, bacteriophage λ was used, both whole and its empty capsid for delivery of different cytotoxic drugs (cisplatin, carboplatin, oxaliplatin, etoposide and doxorubicin). Large quantities of phage λ were obtained from phage λ-producing strain of E. coli cultivated in medium with 0.2 % maltose. After killing of E. coli with chloroform and its removal by centrifugation, the phage was concentrated by ultracentrifugation at 130 000 g and 4 °C for 3 h. The encapsulation of the drugs was performed by infusion method and four different concentrations of the drugs were encapsulated (200; 100; 50; 25 µg/ml). Free molecules of drugs were removed by dialysis. The encapsulation was verified using spectrophotometric and electrochemical methods. The amount of encapsulated drug linearly increased with the amount of applied drug (determination coefficient R2=0.8013). 76% of applied drug was encapsulated in phage λ particles (concentration of 10 µg/ml), even with the highest applied concentration of drugs, 200 µg/ml. Only 1% of encapsulated drug was detected in phage DNA. Similar results were obtained with encapsulation in phage empty capsid. Therefore, it can be concluded that the encapsulation of drugs into phage particles is efficient and mostly occurs by interaction of drugs with protein capsid.

Keywords: cytostatics, drug delivery, nanocarriers, phage capsid

Procedia PDF Downloads 467

Authors: P. S. Hsi, Y. F. Wang, Y. F. Ho, P. C. Hung

Abstract:

The aim of the present study was to explore the dermal exposure assessment model of chemicals that have been developed abroad and to evaluate the feasibility of chemical dermal exposure assessment model for manufacturing industry in Taiwan. We conducted and analyzed six semi-quantitative risk management tools, including UK - Control of substances hazardous to health ( COSHH ) Europe – Risk assessment of occupational dermal exposure ( RISKOFDERM ), Netherlands - Dose related effect assessment model ( DREAM ), Netherlands – Stoffenmanager ( STOFFEN ), Nicaragua-Dermal exposure ranking method ( DERM ) and USA / Canada - Public Health Engineering Department ( PHED ). Five types of manufacturing industry were selected to evaluate. The Monte Carlo simulation was used to analyze the sensitivity of each factor, and the correlation between the assessment results of each semi-quantitative model and the exposure factors used in the model was analyzed to understand the important evaluation indicators of the dermal exposure assessment model. To assess the effectiveness of the semi-quantitative assessment models, this study also conduct quantitative dermal exposure results using prediction model and verify the correlation via Pearson's test. Results show that COSHH was unable to determine the strength of its decision factor because the results evaluated at all industries belong to the same risk level. In the DERM model, it can be found that the transmission process, the exposed area, and the clothing protection factor are all positively correlated. In the STOFFEN model, the fugitive, operation, near-field concentrations, the far-field concentration, and the operating time and frequency have a positive correlation. There is a positive correlation between skin exposure, work relative time, and working environment in the DREAM model. In the RISKOFDERM model, the actual exposure situation and exposure time have a positive correlation. We also found high correlation with the DERM and RISKOFDERM models, with coefficient coefficients of 0.92 and 0.93 (p<0.05), respectively. The STOFFEN and DREAM models have poor correlation, the coefficients are 0.24 and 0.29 (p>0.05), respectively. According to the results, both the DERM and RISKOFDERM models are suitable for performance in these selected manufacturing industries. However, considering the small sample size evaluated in this study, more categories of industries should be evaluated to reduce its uncertainty and enhance its applicability in the future.

Keywords: dermal exposure, risk management, quantitative estimation, feasibility evaluation

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Authors: Maria Belen C. Costa, Liza C. Costa

Abstract:

Teachers have an important influence on students’ academic achievement. Teachers play a crucial role in educational attainment because they stand in the interface of the transmission of knowledge, values, and skills in the learning process through the instructional strategies they employ in the classroom. The level of achievement of students in school depends on the degree of effectiveness of instructional strategies used by the teacher. Thus, this study was conceptualized and conducted to examine the instructional strategies preferred and used by the Science and Mathematics teachers and the impact of those strategies in their teaching performance and students’ academic achievement in Science and Mathematics. The participants of the study comprised a total enumeration of 61 teachers who were chosen through total enumeration and 610 students who were selected using two-stage random sampling technique. The descriptive correlation design was used in this study with a self-made questionnaire as the main tool in the data gathering procedure. Relationship among variables was tested and analyzed using Spearman Rank Correlation Coefficient and Wilcoxon Signed Rank statistics. The teacher participants under study mainly belonged to the age group of ‘young’ (35 years and below) and most were females having ‘very much experienced’ (16 years and above) in teaching. Teaching performance was found to be ‘very satisfactory’ while academic achievement in Science and Mathematics was found to be ‘satisfactory’. Demographic profile and teaching performance of teacher participants were found to be ‘not significant’ to their instructional strategy preferences. Results implied that age, sex, level of education and length of service of the teachers does not affect their preference on a particular instructional strategy. However, the teacher participants’ extent of use of the different instructional strategies was found to be ‘significant’ to their teaching performance. The instructional strategies being used by the teachers were found to have a direct effect on their teaching performance. Academic achievement of student participants was found to be ‘significant’ to the teacher participants’ instructional strategy preferences. The preference of the teachers on instructional strategies had a significant effect on the students’ academic performance. On the other hand, teacher participants’ extent of use of instructional strategies was showed to be ‘not significant’ to the academic achievement of students in Science and Mathematics. The instructional strategy being used by the teachers did not affect the level of performance of students in Science and Mathematics. The results of the study revealed that there was a significant difference between the teacher participants’ preference of instructional strategy and the student participants’ instructional strategy preference as well as between teacher participants’ extent of use and student participants’ perceived level of use of the different instructional strategies. Findings found a discrepancy between the teaching strategy preferences of students and strategies implemented by teachers.

Keywords: academic achievement, extent of use, instructional strategy, preferences

Procedia PDF Downloads 288