Search results for: utilization patterns

Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: Zahira Belkacemi

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One of the most important tools in conservation biology is information on the geographic distribution of species and the variables determining those patterns. In this study, we used maximum-entropy niche modeling (Maxent) to predict the current and future distribution of Anthus pratensis using climatic variables. The results showed that the species would not be highly affected by the climate change in shifting its distribution; however, the results of this study should be improved by taking into account other predictors, and that the NATURA 2000 protected sites will be efficient at 42% in protecting the species.

Keywords: anthus pratensis, climate change, Europe, species distribution model

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Authors: Zhao Jiashen, Serene Goh, Jerry Goo, Anthony Li, Lim Woan Wui, Paul Drakeford, Chen Qing Yan

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Introduction: Emergency laparotomy (EL) is one of the most common surgeries done in Singapore to treat acute abdominal pathologies. A significant proportion of these surgeries are performed in the geriatric population (65 years and older), who tend to have the highest postoperative morbidity, mortality, and highest utilization of intensive care resources. Frailty, the state of vulnerability to adverse outcomes from an accumulation of physiological deficits, has been shown to be associated with poorer outcomes after surgery and remains a strong driver of healthcare utilization and costs. To date, there is little understanding of the impact it has on emergency laparotomy outcomes. The objective of this study is to examine the impact of frailty on postoperative morbidity, mortality, and length of stay after EL. Methods: A retrospective study was conducted in two tertiary centres in Singapore, Tan Tock Seng Hospital and Khoo Teck Puat Hospital the period from January to December 2019. Patients aged 65 years and above who underwent emergency laparotomy for intestinal obstruction, perforated viscus, bowel ischaemia, adhesiolysis, gastrointestinal bleed, or another suspected acute abdomen were included. Laparotomies performed for trauma, cholecystectomy, appendectomy, vascular surgery, and non-GI surgery were excluded. The Clinical Frailty Score (CFS) developed by the Canadian Study of Health and Aging (CSHA) was used. A score of 1 to 4 was defined as non-frail and 5 to 7 as frail. We compared the clinical outcomes of elderly patients in the frail and non-frail groups. Results: There were 233 elderly patients who underwent EL during the study period. Up to 26.2% of patients were frail. Patients who were frail (CFS 5-9) tend to be older, 79 ± 7 vs 79 ± 5 years of age, p <0.01. Gender distribution was equal in both groups. Indication for emergency laparotomies, time from diagnosis to surgery, and presence of consultant surgeons and anaesthetists in the operating theatre were comparable (p>0.05). Patients in the frail group were more likely to receive postoperative geriatric assessment than in the non-frail group, 49.2% vs. 27.9% (p<0.01). The postoperative complications were comparable (p>0.05). The length of stay in the critical care unit was longer for the frail patients, 2 (IQR 1-6.5) versus 1 (IQR 0-4) days, p<0.01. Frailty was found to be an independent predictor of 90-day mortality but not age, OR 2.9 (1.1-7.4), p=0.03. Conclusion: Up to one-fourth of the elderly who underwent EL were frail. Patients who were frail were associated with a longer length of stay in the critical care unit and a 90-day mortality rate of more than three times that of their non-frail counterparts. PPOSSUM was a better predictor of 90-day mortality in the non-frail group than in the frail group. As frailty scoring was a significant predictor of 90-day mortality, its integration into acute surgical units to facilitate shared decision-making and discharge planning should be considered.

Keywords: frailty elderly, emergency, laparotomy

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Authors: Sidrah Ahmed

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The river and lakes flows are modeled mathematically by shallow water equations that are depth-averaged Reynolds Averaged Navier-Stokes equations under Boussinesq approximation. The temperature stratification dynamics influence the water quality and mixing characteristics. It is mainly due to the atmospheric conditions including air temperature, wind velocity, and radiative forcing. The experimental observations are commonly taken along vertical scales and are not sufficient to estimate small turbulence effects of temperature variations induced characteristics of shallow flows. Wind shear stress over the water surface influence flow patterns, heat fluxes and thermodynamics of water bodies as well. Hence it is crucial to couple temperature gradients with shallow water model to estimate the atmospheric effects on flow patterns. The Ripa system has been introduced to study ocean currents as a variant of shallow water equations with addition of temperature variations within the flow. Ripa model is a hyperbolic system of partial differential equations because all the eigenvalues of the system’s Jacobian matrix are real and distinct. The time steps of a numerical scheme are estimated with the eigenvalues of the system. The solution to Riemann problem of the Ripa model is composed of shocks, contact and rarefaction waves. Solving Ripa model with Riemann initial data with the central schemes is difficult due to the eigen structure of the system.This works presents the comparison of four different finite difference schemes for the numerical solution of Riemann problem for Ripa model. These schemes include Lax-Friedrichs, Lax-Wendroff, MacCormack scheme and a higher order finite difference scheme with WENO method. The numerical flux functions in both dimensions are approximated according to these methods. The temporal accuracy is achieved by employing TVD Runge Kutta method. The numerical tests are presented to examine the accuracy and robustness of the applied methods. It is revealed that Lax-Freidrichs scheme produces results with oscillations while Lax-Wendroff and higher order difference scheme produce quite better results.

Keywords: finite difference schemes, Riemann problem, shallow water equations, temperature gradients

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Authors: Dongwoo Kang, Yunsung Yoo, Injun Kim, Jongin Lee, Jinwon Park

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Since industrial revolution, energy usage by human-beings has been drastically increased resulting in the enormous emissions of carbon dioxide into the atmosphere. High concentration of carbon dioxide is well recognized as the main reason for the climate change by breaking the heat equilibrium of the earth. In order to decrease the amount of carbon dioxide emission, lots of technologies have been developed. One of the methods is to capture carbon dioxide after combustion process using liquid type absorbents. However, for some nations, captured carbon dioxide cannot be treated and stored properly due to their geological structures. Also, captured carbon dioxide can be leaked out when crust activities are active. Hence, the method to convert carbon dioxide as stable and useful products were developed. It is usually called CCU, that is, Carbon Capture and Utilization. There are several ways to convert carbon dioxide into useful substances. For example, carbon dioxide can be converted and used as fuels such as diesel, plastics, and polymers. However, these types of technologies require lots of energy to make stable carbon dioxide into a reactive one. Hence, converting it into metal carbonates salts have been studied widely. When carbon dioxide is captured by alkanolamine-based liquid absorbents, it exists as ionic forms such as carbonate, carbamate, and bicarbonate. When adequate metal ions are added, metal carbonate salt can be produced by ionic reaction with fast reaction kinetics. However, finding metal sources can be one of the problems for this method to be commercialized. If natural resources such as calcium oxide were used to supply calcium ions, it is not thought to have the economic feasibility to use natural resources to treat carbon dioxide. In this research, high concentrated industrial wastewater produced from refined salt production facility have been used as metal supplying source, especially for calcium cations. To ensure purity of final products, calcium ions were selectively separated in the form of gypsum dihydrate. After that, carbon dioxide is captured using alkanolamine-based absorbents making carbon dioxide into reactive ionic form. And then, high purity calcium carbonate salt was produced. The existence of calcium carbonate was confirmed by X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) images. Also, carbon dioxide loading curves for absorption, conversion, and desorption were provided. Also, in order to investigate the possibility of the absorbent reuse, reabsorption experiments were performed either. Produced calcium carbonate as final products is seemed to have potential to be used in various industrial fields including cement and paper making industries and pharmaceutical engineering fields.

Keywords: alkanolamine, calcium carbonate, climate change, seawater, industrial wastewater

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Authors: Arianna Sacerdoti

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There is a rich and frequent representation of uniqueness in Statius’ poem called Thebaid. This topos interweave with a psychoanalytical study about groups and individual but is also a literary device. This paper will analyze all the passages in the 'Thebaid' referred to uniqueness and exceptionality. Antigone, Adrastus and other characters are, in fact, often characterized as the only ones to behave in a specific way or to do something. Also, the insomniac characters are often the only ones who do not sleep. The material of such a tòpos is very rich throughout the 'Thebaid'. The methodology will be text-oriented. Conclusions will enlighten Statius’ specific use of this tòpos, as related to his models, and will be interdisciplinary. In concluding, this is a study linking philology and psychoanalysis and focused on a topic which deserves a specific analysis.

Keywords: statius, Silius Italicus, uniqueness, epic

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Authors: Louise Ödlund, Danica Djuric Ilic

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Sustainable development includes many challenges related to energy use, such as (1) developing flexibility on the demand side of the electricity systems due to an increased share of intermittent electricity sources (e.g., wind and solar power), (2) overcoming economic challenges related to an increased share of renewable energy in the transport sector, (3) increasing efficiency of the biomass use, (4) increasing utilization of industrial excess heat (e.g., approximately two thirds of the energy currently used in EU is lost in the form of excess and waste heat). The European Commission has been recognized DH technology as of essential importance to reach sustainability. Flexibility in the fuel mix, and possibilities of industrial waste heat utilization, combined heat, and power (CHP) production and energy recovery through waste incineration, are only some of the benefits which characterize DH technology. The aim of this study is to provide an overview of the possible business strategies which would enable DH to have an important role in future sustainable energy systems. The methodology used in this study is a systematic literature review. The study includes a systematic approach where DH is seen as a part of an integrated system that consists of transport , industrial-, and electricity sectors as well. The DH technology can play a decisive role in overcoming the sustainability challenges related to our energy use. The introduction of biofuels in the transport sector can be facilitated by integrating biofuel and DH production in local DH systems. This would enable the development of local biofuel supply chains and reduce biofuel production costs. In this way, DH can also promote the development of biofuel production technologies that are not yet developed. Converting energy for running the industrial processes from fossil fuels and electricity to DH (above all biomass and waste-based DH) and delivering excess heat from industrial processes to the local DH systems would make the industry less dependent on fossil fuels and fossil fuel-based electricity, as well as the increasing energy efficiency of the industrial sector and reduce production costs. The electricity sector would also benefit from these measures. Reducing the electricity use in the industry sector while at the same time increasing the CHP production in the local DH systems would (1) replace fossil-based electricity production with electricity in biomass- or waste-fueled CHP plants and reduce the capacity requirements from the national electricity grid (i.e., it would reduce the pressure on the bottlenecks in the grid). Furthermore, by operating their central controlled heat pumps and CHP plants depending on the intermittent electricity production variation, the DH companies may enable an increased share of intermittent electricity production in the national electricity grid.

Keywords: energy system, district heating, sustainable business strategies, sustainable development

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Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

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Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

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Authors: S. D. Abdul, F. B. J. Sawa, D. Z. Andrawus, G. Dan'ilu

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Fresh leaves of twelve accessions of S. indicum were studied to examine their stomatal features, trichomes, epidermal cell shapes and anticlinal cell-wall patterns which may be used for the delimitation of the varieties. The twelve accessions of S. indicum studied have amphistomatic leaves, i.e. having stomata on both surfaces. Four types of stomatal complex types were observed namely, diacytic, anisocytic, tetracytic and anomocytic. Anisocytic type was the most common occurring on both surfaces of all the varieties and occurred 100% in varieties lale-duk, ex-sudan and ex-gombe 6. One-way ANOVA revealed that there was no significant difference between the stomatal densities of ex-gombe 6, ex-sudan, adawa-wula, adawa-ting, ex-gombe 4 and ex-gombe 2 . Accession adawa-ting (improved) has the smallest stomatal size (26.39µm) with highest stomatal density (79.08mm2) while variety adawa-wula possessed the largest stomatal size (74.31µm) with lowest stomatal density (29.60mm2), the exception was found in variety adawa-ting whose stomatal size is larger (64.03µm) but with higher stomatal density (71.54mm2). Wavy, curve or undulate anticlinal wall patterns with irregular and or isodiametric epidermal cell shapes were observed. These accessions were found to exhibit high degree of heterogeneity in their trichome features. Ten types of trichomes were observed: unicellular, glandular peltate, capitate glandular, long unbranched uniseriate, short unbranched uniseriate, scale, multicellular, multiseriate capitate glandular, branched uniseriate and stallate trichomes. The most frequent trichome type is short-unbranched uniseriate, followed by long-unbranched uniseriate (72.73% and 72.5%) respectively. The least frequent was multiseriate capitate glandular (11.5%). The high variation in trichome types and density coupled with the stomatal complex types suggest that these varieties of S. indicum probably have the capacity to conserve water. Furthermore, the leaf micromorphological features varied from one accession to another, hence, are found to be good diagnostic and additional tool in identification as well as nomenclature of the accessions of S. indicum.

Keywords: Sesamum indicum, stomata, trichomes, epidermal cells, taxonomy

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Authors: Weeraya Samnuknit, Apichat Boontawan

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A vacuum fractionation technique was introduced to remove ethanol from fermentation broth. The effect of initial glucose and ethanol concentrations were investigated for specific productivity. The inhibitory ethanol concentration was observed at 100 g/L. In order to increase the fermentation performance, the ethanol product was removed as soon as it is produced. The broth was boiled at 35°C by reducing the pressure to 65 mBar. The ethanol/water vapor was fractionated for up to 90 wt% before leaving the column. Ethanol concentration in the broth was kept lower than 25 g/L, thus minimized the product inhibition effect to the yeast cells. For batch extractive fermentation, a high substrate utilization rate was obtained at 26.6 g/L.h and most of glucose was consumed within 21 h. For repeated-batch extractive fermentation, addition of glucose was carried out up to 9 times and ethanol was produced more than 8-fold higher than batch fermentation.

Keywords: ethanol, extractive fermentation, product inhibition, vacuum fractionation

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Authors: Marion G. Ben-Jacob, David Wang

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There is a mathematics requirement for entry level college and university students, especially those who plan to study STEM (Science, Technology, Engineering and Mathematics). Most of them take College Algebra, and to continue their studies, they need to succeed in this course. Different pedagogical strategies are employed to promote the success of our students. There is, of course, the Traditional Method of teaching- lecture, examples, problems for students to solve. The Emporium Model, another pedagogical approach, replaces traditional lectures with a learning resource center model featuring interactive software and on-demand personalized assistance. This presentation will compare these two methods of pedagogy and the study done with its results on this comparison. Math is the foundation for science, technology, and engineering. Its work is generally used in STEM to find patterns in data. These patterns can be used to test relationships, draw general conclusions about data, and model the real world. In STEM, solutions to problems are analyzed, reasoned, and interpreted using math abilities in a assortment of real-world scenarios. This presentation will examine specific examples of how math is used in the different STEM disciplines. Math becomes practical in science when it is used to model natural and artificial experiments to identify a problem and develop a solution for it. As we analyze data, we are using math to find the statistical correlation between the cause of an effect. Scientists who use math include the following: data scientists, scientists, biologists and geologists. Without math, most technology would not be possible. Math is the basis of binary, and without programming, you just have the hardware. Addition, subtraction, multiplication, and division is also used in almost every program written. Mathematical algorithms are inherent in software as well. Mechanical engineers analyze scientific data to design robots by applying math and using the software. Electrical engineers use math to help design and test electrical equipment. They also use math when creating computer simulations and designing new products. Chemical engineers often use mathematics in the lab. Advanced computer software is used to aid in their research and production processes to model theoretical synthesis techniques and properties of chemical compounds. Mathematics mastery is crucial for success in the STEM disciplines. Pedagogical research on formative strategies and necessary topics to be covered are essential.

Keywords: emporium model, mathematics, pedagogy, STEM

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Authors: Abdelmagid Basyouny Sakr

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Terminological variation is a reality and it is now recognized by terminologists. This paper investigates the terminological variation in the context of specialized economic texts in Italian. It aims to find whether certain patterns or tendencies can be derived from the analysis of these texts. Term variants pose two different kinds of difficulties. The first one is being able to recognize linguistic expressions that denote the same concept in running text. Another one lies in knowing which variant should be considered and for what purpose. This would help to differentiate between variants that could be candidates for inclusion in terminological resources and the ones which are synonyms or contextual variants. New insights about terminological variation in specialized texts could contribute to improve specialized dictionaries which will better account for the different ways in which a given thought is expressed.

Keywords: corpus linguistics, specialized communication, terms and concepts, terminological variation

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Authors: Robin Turner

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In the context of the strengthening conservative movements such as “Brexit” and the election of US President Donald Trump, the global political stage was shaken up by the election of Emmanuel Macron to the French presidency, defeating the far-right candidate Marine Le Pen. The election itself was a first for the Fifth Republic in which neither final candidate was from the traditional two major political parties: the left Parti Socialiste (PS) and the right Les Républicains (LR). Macron, who served as the Minister of Finance under his predecessor, founded the centrist liberal political party En Marche! in April 2016 before resigning from his post in August to launch his bid for the presidency. Between the time of the party’s creation to the first round of elections a year later, Emmanuel Macron and En Marche! had garnered enough support to make it to the run-off election, finishing far ahead of many seasoned national political figures. Now months into his presidency, the youngest President of the Republic shows no sign of losing fuel anytime soon. His unprecedented success raises a lot of questions with respect to international relations, economics, and the evolving relationship between the French government and its citizens. The effectiveness of Macron’s campaign, of course, relies on many factors, one of which is his manner of communicating his platform to French voters. Using data from oral discourse and primary material from Macron and En Marche! in sources such as party publications and Twitter, the study categorizes linguistic instruments – address, lexicon, tone, register, and syntax – to identify prevailing patterns of speech and communication. The linguistic analysis in this project is two-fold. In addition to these findings’ stand-alone value, these discourse patterns are contextualized by comparable discourse of other 2017 presidential candidates with high emphasis on that of Marine Le Pen. Secondly, to provide an alternative approach, the study contextualizes Macron’s discourse using those of two immediate predecessors representing the traditional stronghold political parties, François Hollande (PS) and Nicolas Sarkozy (LR). These comparative methods produce an analysis that gives insight to not only a contributing factor to Macron’s successful 2017 campaign but also provides insight into how Macron’s platform presents itself differently to previous presidential platforms. Furthermore, this study extends analysis to supply data that contributes to a wider analysis of the defeat of “traditional” French political parties by the “start-up” movement En Marche!.

Keywords: Emmanuel Macron, French, discourse analysis, political discourse

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Authors: Zakir Hossain, Md. Saddam Hossain

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A nutritionally balanced diet and selection of appropriate species are important criteria in aquaculture. The present study was conducted to evaluate the effects of polyunsaturated fatty acids (PUFAs) and beta glucan containing diet on growth performance, feed utilization, maturation, immunity, early embryonic and larval development of endangered Pabdah catfish, Ompok pabda. In this study, squid extracted lipids and mushroom powder were used as the source of PUFAs and beta glucan, respectively, and formulated two isonitrogenous diets such as basal or control (CON) diet and treated (PBG) diet with maintaining 30% protein levels. During the study period, similar physicochemical conditions of water such as temperature, pH, and dissolved oxygen (DO) were 26.5±2 °C, 7.4±0.2, and 6.7±0.5 ppm, respectively in each cistern. The results showed that final mean body weight, final mean length gain, food conversion ratio (FCR), specific growth rate (SGR), food conversion efficiency (%), hepatosomatic index (HSI), kidney index (KI), and viscerosomatic index (VSI) were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The length-weight relationship and relative condition factor (K) of O. pabda were significantly (P<0.05) affected by the PBG diet. The gonadosomatic index (GSI), sperm viability, blood serum calcium ion concentrations (Ca²⁺), and vitellogenin level were significantly (P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet; which was used to the indication of fish maturation. During the spawning season, lipid granules and normal morphological structure were observed in the treated fish liver, whereas fewer lipid granules of liver were observed in the control group. Based on the immunity and stress resistance-related parameters such as hematological indices, antioxidant activity, lysozyme level, respiratory burst activity, blood reactive oxygen species (ROS), complement activity (ACH50 assay), specific IgM, brain AChE, plasma PGOT, and PGPT enzyme activity were significantly (P<0.01 and P<0.05) higher in fish fed the PBG diet than that of fish fed the CON diet. The fecundity, fertilization rate (92.23±2.69%), hatching rate (87.43±2.17 %) and survival (76.62±0.82%) of offspring were significantly higher (P˂0.05) in the PBG diet than in the control. Consequently, early embryonic and larval development was better in PBG treated group than in the control. Therefore, the present study showed that the polyunsaturated fatty acids (PUFAs) and beta glucan enriched experimental diet were more effective and achieved better growth, feed utilization, maturation, immunity, and spawning performances of O. pabda.

Keywords: polyunsaturated fatty acids, beta glucan, maturity, immunity, catfish

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Authors: Waraporn Wimuktalop

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This research will select regions which are vulnerable to flooding in different level. Mathematical principles will be systematically and rationally utilized as a tool to solve problems of selection the regions. Therefore the method called Multiple Criteria Decision Making (MCDM) has been chosen by having two analysis standards, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytic Hierarchy Process). There are three criterions that have been considered in this research. The first criterion is climate which is the rainfall. The second criterion is geography which is the height above mean sea level. The last criterion is the land utilization which both forest and agriculture use. The study found that the South has the highest risk of flooding, then the East, the Centre, the North-East, the West and the North, respectively.

Keywords: multiple criteria decision making, TOPSIS, analytic hierarchy process, flooding

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Authors: Jillian Correia, Ali Sakkal

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Lunchtime can play a pivotal role in shaping student eating habits. Studies have previously indicated that eating a healthy meal during the school day can improve students’ well-being and academic performance, and potentially prevent childhood obesity. This study investigated the school lunch program in the United Kingdom in order to gain an understanding of the attitudes and beliefs surrounding school meals and the realities of student food patterns. Using a qualitative research methodology, this study was conducted in three primary and secondary school systems in London, United Kingdom. In depth interviews consisting of 14 headteachers, teachers, staff, and chefs and fieldwork observations of approximately 830 primary and secondary school students in the three schools’ cafeterias provided the data. The results of interview responses and fieldwork observation yielded the following set of themes: (a) school meals are publicly portrayed as healthful and nutritious, yet students’ eating habits do not align with this advertising, (b) the level of importance placed on school lunch varies widely among participants and generates inconsistent views concerning who is responsible (government, families, caterers, or schools) for students’ eating habits, (c) role models (i.e. teachers and chefs) present varying levels of interaction with students and conflicting approaches when monitoring students’ eating habits. The latter finding expanded upon Osowski, Göranzon, and Fjellström’s (2013) concept of teacher roles to formulate three education philosophies – the Removed Authority Role Model, the Accommodating Role Model, and the Social Educational Role Model – concluding that the Social Educational Role Model was the most effective at fostering an environment that encouraged healthy eating habits and positive behavior. For schools looking to cultivate strong relationships between students and teachers and facilitate healthier eating habits, these findings were used to construct three key recommendations: (1) elevate the lunch environment by encouraging proper dining etiquette, (2) get teachers eating at the table with students, and (3) shift the focus from monitoring behavior to a teacher-student dialogue centered on food awareness.

Keywords: food culture, eating habits, school meals, student behavior, education, food patterns, lunchtime

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Authors: A. Vaidya-Soocheta, K. M. Wong-Hon-Lang

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Craft and fashion have always been interlinked. The combination of both often gives stunning results. The present study introduces ‘Paper Cutting Craft Techniques’ like the Japanese –Kirigami, Mexican –PapelPicado, German –Scherenschnitte, Polish –Wycinankito in textiles to develop innovative and novel design structures as embellishments and ornamentation. The project studies various ways of using these paper cutting techniques to obtain interesting features and delicate design patterns on fabrics. While paper has its advantages and related uses, it is fragile rigid and thus not appropriate for clothing. Fabric is sturdy, flexible, dimensionally stable and washable. In the present study, the cut out techniques develop creative design motifs and patterns to give an inventive and unique appeal to the fabrics. The beauty and fascination of lace in garments have always given them a nostalgic charm. Laces with their intricate and delicate complexity in combination with other materials add a feminine touch to a garment and give it a romantic, mysterious appeal. Various textured and decorative effects through fabric manipulation are experimented along with the use of paper cutting craft skills as an innovative substitute for developing lace or “Broderie Anglaise” effects on textiles. A number of assorted fabric types with varied textures were selected for the study. Techniques to avoid fraying and unraveling of the design cut fabrics were introduced. Fabrics were further manipulated by use of interesting prints with embossed effects on cut outs. Fabric layering in combination with assorted techniques such as cutting of folded fabric, printing, appliqué, embroidery, crochet, braiding, weaving added a novel exclusivity to the fabrics. The fabrics developed by these innovative methods were then tailored into garments. The study thus tested the feasibility and practicability of using these fabrics by designing a collection of evening wear garments based on the theme ‘Nostalgia’. The prototypes developed were complemented by designing fashion accessories with the crafted fabrics. Prototypes of accessories add interesting features to the study. The adaptation and application of this novel technique of paper cutting craft on textiles can be an innovative start for a new trend in textile and fashion industry. The study anticipates that this technique will open new avenues in the world of fashion to incorporate its use commercially.

Keywords: collection, fabric cutouts, nostalgia, prototypes

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Authors: Zeina Bou Diab, Arij Daou

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The neural mechanisms of sequential behaviors are intensively studied, with songbirds a focus for learned vocal production. We are studying the premotor nucleus HVC at a nexus of multiple pathways contributing to song learning and production. The HVC consists of multiple classes of neuronal populations, each has its own cellular, electrophysiological and functional properties. During singing, a large subset of motor cortex analog-projecting HVCRA neurons emit a single 6-10 ms burst of spikes at the same time during each rendition of song, a large subset of basal ganglia-projecting HVCX neurons fire 1 to 4 bursts that are similarly time locked to vocalizations, while HVCINT neurons fire tonically at average high frequency throughout song with prominent modulations whose timing in relation to song remains unresolved. This opens the opportunity to define models relating explicit HVC circuitry to how these neurons work cooperatively to control learning and singing. We developed conductance-based Hodgkin-Huxley models for the three classes of HVC neurons (based on the ion channels previously identified from in vitro recordings) and connected them in several physiologically realistic networks (based on the known synaptic connectivity and specific glutaminergic and gabaergic pharmacology) via different architecture patterning scenarios with the aim to replicate the in vivo firing patterning behaviors. We are able, through these networks, to reproduce the in vivo behavior of each class of HVC neurons, as shown by the experimental recordings. The different network architectures developed highlight different mechanisms that might be contributing to the propagation of sequential neural activity (continuous or punctate) in the HVC and to the distinctive firing patterns that each class exhibits during singing. Examples of such possible mechanisms include: 1) post-inhibitory rebound in HVCX and their population patterns during singing, 2) different subclasses of HVCINT interacting via inhibitory-inhibitory loops, 3) mono-synaptic HVCX to HVCRA excitatory connectivity, and 4) structured many-to-one inhibitory synapses from interneurons to projection neurons, and others. Replication is only a preliminary step that must be followed by model prediction and testing.

Keywords: computational modeling, neural networks, temporal neural sequences, ionic currents, songbird

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Authors: Éva Pintér, Péter Bagó, Nikolett Deutsch, Miklós Hetényi

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The process of digital transformation has a profound influence on all sectors of the worldwide economy and the business environment. The influence of blockchain technology can be observed in the digital economy and e-government, rendering it an essential element of a nation's growth strategy. The banking industry is experiencing significant expansion and development of financial technology firms. Utilizing developing technologies such as artificial intelligence (AI), machine learning (ML), and big data (BD), these entrants are offering more streamlined financial solutions, promptly addressing client demands, and presenting a challenge to incumbent institutions. The advantages of digital transformation are evident in the corporate realm, and firms that resist its adoption put their survival at risk. The advent of digital technologies has revolutionized the business environment, streamlining processes and creating opportunities for enhanced communication and collaboration. Thanks to the aid of digital technologies, businesses can now swiftly and effortlessly retrieve vast quantities of information, all the while accelerating the process of creating new and improved products and services. Big data analytics is generally recognized as a transformative force in business, considered the fourth paradigm of science, and seen as the next frontier for innovation, competition, and productivity. Big data, an emerging technology that is shaping the future of the banking sector, offers numerous advantages to banks. It enables them to effectively track consumer behavior and make informed decisions, thereby enhancing their operational efficiency. Banks may embrace big data technologies to promptly and efficiently identify fraud, as well as gain insights into client preferences, which can then be leveraged to create better-tailored products and services. Moreover, the utilization of big data technology empowers banks to develop more intelligent and streamlined models for accurately recognizing and focusing on the suitable clientele with pertinent offers. There is a scarcity of research on big data analytics in the banking industry, with the majority of existing studies only examining the advantages and prospects associated with big data. Although big data technologies are crucial, there is a dearth of empirical evidence about the role of big data analytics (BDA) capabilities in bank performance. This research addresses a gap in the existing literature by introducing a model that combines the resource-based view (RBV), the technical organization environment framework (TOE), and dynamic capability theory (DC). This study investigates the influence of Big Data Analytics (BDA) utilization on the performance of market and risk management. This is supported by a comparative examination of Hungarian mobile banking services.

Keywords: big data, digital transformation, dynamic capabilities, mobile banking

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Authors: Theresa Chinyere ONU

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This paper examines the effect of social terrorism on education in Nigeria. The article looked into some prevailing conditions of international political unrest and insecurity. The fear and risk of these conditions to national security and the struggle for power establishment which has further intensified and taken the shape of terrorism has imposed devastating effects on the growth and prosperity of Nigeria; as traffic patterns get disturbed, hospitals and schools get dysfunctional. This has also affected the educational standard in Nigeria as parents are no longer comfortable in sending their children to schools in some states for the fear of terrorist attacks. The study emphasized the integrated the effort of the government management institutions.

Keywords: education, social terrorism, women, Nigeria

Procedia PDF Downloads 583

Authors: I. Domingos, B. Esteves, A. Figueirinha, Luísa P. Cruz-Lopes, J. Ferreira, H. Pereira

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Chromium is one of the most common heavy metals which exist in very high concentrations in wastewater. The removal is very expensive due to the high cost of normal adsorbents. Lignocellulosic materials and mainly treated materials have proven to be a good solution for this problem. Adsorption tests were performed at different pH, different times and with varying concentrations. Results show that is at pH 3 that treated wood absorbs more chromium ranging from 70% (2h treatment) to almost 100% (12 h treatment) much more than untreated wood with less than 40%. Most of the adsorption is made in the first 2-3 hours for untreated and heat treated wood. Modified wood adsorbs more chromium throughout the time. For all the samples, adsorption fitted relatively well the Langmuir model with correlation coefficient ranging from 0.85 to 0.97. The results show that heat treated wood is a good adsorbent ant that this might be a good utilization for sawdust from treating companies.

Keywords: adsorption, chromium, heat treatment, wood modification

Procedia PDF Downloads 499

Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

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Authors: Mohammad Ahmadi

Abstract:

Argumentative writing is a highly opinion-based form of discourse that necessitates the ability to address commonly held opinions (endoxa). To enhance the development of persuasive, argumentative essays, the incorporation of classical rhetorical theory, with a specific focus on topics related to the canon of Invention (inventio), can be advantageous. This research investigates the practical application of rhetorical theory in teaching students how to construct compelling argumentative essays. The fundamental premise of this study is the limited familiarity of rhetoric and composition students with rhetorical theory. Consequently, this paper presents an effective pedagogical approach to introduce rhetorical theory to students, beginning from a foundational level. It delineates the procedures and progression that educators should adopt to elucidate and facilitate students' comprehension of rhetorical theory while demonstrating its utilization in the writing of an argumentative essay.

Keywords: argumentative essay, rhetorical theory, pedagogy, invention

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Authors: K. R. Balabiyev, A. O. Kaipbayeva

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The article discusses the legal framework of the government’s environmental function and analyzes the role of the national policy in protection of wetlands. The problem is of interest for it deals with the most important branch of economy–utilization of Kazakhstan’s natural resources, protection of health and environmental well being of the population. Development of a long-term environmental program addressing the protection of wetlands represents the final stage of the government’s environmental policy, and is a relatively new function for the public administration system. It appeared due to the environmental measures that require immediate decisions to be taken. It is an integral part of the effort in the field of management of state-owned natural resource, as well as of the measures aimed at efficient management of natural resources to avoid their early depletion or contamination.

Keywords: environmental focus, government’s environmental function, protection of wetlands, Kazakhstan

Procedia PDF Downloads 347

Authors: Nashwah Alnajjar

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This research paper provides an overview of Replika, an AI chatbot application that uses natural language processing technology to engage in conversations with users. The app was developed to provide users with a virtual AI friend who can converse with them on various topics, including mental health. This study explores the experiences of Replika users using quantitative research methodology. A survey was conducted with 12 participants to collect data on their demographics, usage patterns, and experiences with the Replika app. The results showed that Replika has the potential to play a role in mental health support and well-being.

Keywords: Replika, chatbot, mental health, artificial intelligence, natural language processing

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Authors: Muhammad Awais Shafique, Eiji Hato, Hideki Yaginuma

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Recently GPS data is used in a lot of studies to automatically reconstruct travel patterns for trip survey. The aim is to minimize the use of questionnaire surveys and travel diaries so as to reduce their negative effects. In this paper data acquired from GPS and accelerometer embedded in smart phones is utilized to predict the mode of transportation used by the phone carrier. For prediction, Support Vector Machine (SVM) and Adaptive boosting (AdaBoost) are employed. Moreover a unique method to improve the prediction results from these algorithms is also proposed. Results suggest that the prediction accuracy of AdaBoost after improvement is relatively better than the rest.

Keywords: accelerometer, AdaBoost, GPS, mode prediction, support vector machine

Procedia PDF Downloads 359

Authors: Sanjay Rathee, Arti Kashyap

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Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

Procedia PDF Downloads 294

Authors: M. Sari Yilmaz, N. Karamahmut Mermer

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Coal fly ash is formed as a solid waste product from the combustion of coal in coal fired power stations. Huge amounts of fly ash are produced globally every year and are predicted to increase. Nowadays, less than half of the fly ash is used as a raw material for cement manufacturing, construction and the rest of it is disposed as a waste causing yet another environmental concern. For this reason, the recycling of this kind of slurries into useful materials is quite important in terms of economical and environmental aspects. The purpose of this study is to evaluate the Orhaneli and Tuncbilek coal fly ashes for utilization in some industrial applications. Therefore the mineralogical and chemical compositions of these fly ashes were analyzed by X-ray fluorescence (XRF) spectroscopy and X-ray diffraction (XRD). The silicon (Si) and aluminum (Al) in the fly ashes were activated by alkali fusion technique with sodium hydroxide. The obtained extracts were analyzed for Si and Al content by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: extraction, fly ash, fusion, XRD

Procedia PDF Downloads 322

Authors: Abdeljalil Beniiche

Abstract:

The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

Procedia PDF Downloads 136

Authors: Mohammed Jourdani, Hamid Mounir, Abdellatif El Marjani

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Proton exchange membrane fuel cells (PEMFCs) have been developed as a promising power source for transportation and stationary applications, and power devices for computers and mobile telephones. This paper discusses and summarizes the latest developments of materials and remaining challenges of PEMFC. The different contributions to the material of all components and the efficiencies are analyzed. Many technical advances are introduced to increase the PEMFC fuel cell efficiency and life time for transportation, stationary and portable utilization. By the last years the total cost of this system is decreasing. However, the remaining challenges that need to be overcome mean that it will be several years before full commercialization can take place.

Keywords: PEMFC fuel cell, materials, recent development, efficiency, life time, commercialization possibility

Procedia PDF Downloads 311