Search results for: food composition data

Authors: Gredson Keif Souza, Nehemias Curvelo Pereira

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Kernel oil from Macaúba is an important source of essential fatty acids. Thus, a new knowledge of the oil of this species could be used in new applications, such as pharmaceutical drugs based in the manufacture of cosmetics, and in various industrial processes. The aim of this study was to characterize the kernel oil of macaúba (Acrocomia Totai) at different times of their maturation. The physico-chemical characteristics were determined in accordance with the official analytical methods of oils and fats. It was determined the content of water and lipids in kernel, saponification value, acid value, water content in the oil, viscosity, density, composition in fatty acids by gas chromatography and molar mass. The results submitted to Tukey test for significant value to 5%. Found for the unripe fruits values superior to unsaturated fatty acids.

Keywords: extraction, characterization, kernel oil, acrocomia totai

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Authors: Boutemak Khalida, Dahmani Siham

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Garden cress (Lepidium Sativum L.) belonging to the family Brassicaceae, is edible growing annual herb. Its various parts (roots, leaves and seeds) have been used to treat various human ailments. Its seed extracts have been screened for various biological activities like hypotensive, antimicrobial, bronchodilator, hypoglycaemic and antianemic. The aim of the present study is to optimize the process parameters (cellulase concentration and incubation time) of enzymatic pre-treatment of the garden cress seeds and to evaluate the effect of cellulase pre-treatment of the crushed seeds on the oil yield, physico-chemical properties and antibacterial activity and comparing to non-enzymatic method. The optimum parameters of cellulase pre-treatment were as follows: cellulase of 0,1% w/w and incubation time of 2h. After enzymatic pre-treatment, the oil was extracted by n-hexane for 1.5 h, the oil yield was 4,01% for cellulase pre-treatment as against 10,99% in the control sample. The decrease in yield might be caused a result of mucilage. Garden cress seeds are covered with a layer of mucilage which gels on contact with water. At the same time, the antibacterial activity was carried out using agar diffusion method against 4 food-borne pathogens (Escherichia coli, Salmonella typhi,Staphylococcus aureus, Bacillus subtilis). The results showed that bacterial strains are very sensitive to the oil with cellulase pre-treatment. Staphylococcus aureus is extremely sensitive with the largest zone of inhibition (40 mm), Escherichia coli and salmonella typhi had a very sensitive to the oil with a zone of inhibition (26 mm). Bacillus subtilizes is averagely sensitive which gave an inhibition of 16 mm. But it does not exhibit sensivity to the oil without enzymatic pre-treatment with a zone inhibition (< 8 mm). Enzymatic pre-treatment could be useful for antimicrobial activity of the oil, and hold a good potential for use in food and pharmaceutical industries.

Keywords: Lepidium sativum L., cellulase, enzymatic pretreatment, antibacterial activity.

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Authors: Liu Yang

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Calligraphy has a unique aesthetic value in Chinese traditional culture. Calligraphy reflects the physical beauty and the dynamic beauty of things through the structure of writing and the order of strokes to standardize the style of writing. In recent years, Chinese researchers have carried out research on the appreciation of calligraphy works from the perspective of psychology, such as how Chinese people appreciate the beauty of stippled lines, the beauty of virtual and real, and the beauty of the composition. However, there is currently no domestic research on how foreigners appreciate Chinese calligraphy. People's appreciation of calligraphy is mainly in the form of visual perception, and psychologists have been working on the use of eye trackers to record eye tracking data to explore the relationship between eye tracking and psychological activities. The purpose of this experimental study is to use eye tracking recorders to analyze the eye gaze trajectories of college students with different cultural backgrounds when they appreciate the same calligraphy work to reveal the differences in cognitive processing with different cultural backgrounds. It was found that Chinese students perceived calligraphy as words when viewing calligraphy works, so they first noticed fonts with easily recognizable glyphs, and the overall viewed time was short. Foreign students perceived calligraphy works as graphics, and they first noticed novel and abstract fonts, and the overall viewing time is longer. The understanding of calligraphy content has a certain influence on the appreciation of calligraphy works by foreign students. It is shown that when foreign students who understand the content of calligraphy works. The eye tracking path is more consistent with the calligraphy writing path, and it helps to develop associations with calligraphy works to better understand the connotation of calligraphy works. This result helps us understand the impact of cultural background differences on calligraphy appreciation and helps us to take more effective strategies to help foreign audiences understand Chinese calligraphy art.

Keywords: Chinese calligraphy, eye-tracking, cross-cultural, cultural communication

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Authors: Nikola Tomasevic, Marko Batic, Sanja Vranes

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Emerging Semantic Web technologies can be seen as the next step in evolution of the intelligent facility management systems. Particularly, this considers increased usage of open source and/or standardized concepts for data classification and semantic interpretation. To deliver such facility management systems, providing the comprehensive integration and interoperability platform in from of the facility data model is a prerequisite. In this paper, one of the possible modelling approaches to provide such integrative facility data model which was based on the ontology modelling concept was presented. Complete ontology development process, starting from the input data acquisition, ontology concepts definition and finally ontology concepts population, was described. At the beginning, the core facility ontology was developed representing the generic facility infrastructure comprised of the common facility concepts relevant from the facility management perspective. To develop the data model of a specific facility infrastructure, first extension and then population of the core facility ontology was performed. For the development of the full-blown facility data models, Malpensa and Fiumicino airports in Italy, two major European air-traffic hubs, were chosen as a test-bed platform. Furthermore, the way how these ontology models supported the integration and interoperability of the overall airport energy management system was analyzed as well.

Keywords: airport ontology, energy management, facility data model, ontology modeling

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Authors: Gulcin Yildiz, Gokcen Izli

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Drying (dehydration) is the process of removing water from food in order to preserve the food. Drying is one of the oldest methods known for the preservation of agricultural products such as fruits and vegetables. Drying of agricultural products enhances their storage life, minimizes losses during storage, and save shipping and transportation costs. Apples are considered excellent candidates for drying. The objective of this research was to investigate the effects of microwave and oven processing on the quality of selected apple products. Red delicious and golden delicious apples were washed, peeled, and sliced. Drying experiments were performed in an oven at 50, 75 and 100 °C and in a microwave at 140 W and 210 W. Quality attributes such as color, total phenolic content and antioxidant capacity of dried samples with different methods were compared with the fresh sample. A Minolta CR-300 Chroma Meter was used to examine color changes in the apples. Total phenolic content was determined using the Folin-Ciocalteu reagent. The free radical scavenging activity of the extract was determined using 1,1-diphenyl-2-picrylhydrazyl (DPPH). It was found that the phenolic contents and antioxidant capacities of dried samples under all drying conditions were decreased compared to the fresh samples. The phenolic contents of microwave dried samples at 140 W and 210 W for both red and golden delicious apples were higher than those of the oven drying at 50, 75 and 100 °C. Similarly, the antioxidant activities of microwave dried samples at 140 W and 210 W were higher than those of the oven drying at 50, 75 and 100 °C for both types of apples. All color parameters (L*, a*, b*) were changed significantly depending on the drying methods and temperatures. The closest color values to the fresh sample were found for the microwave dried samples at 140 W. Microwave drying was proven to be more effective than oven drying.

Keywords: antioxidant capacity, color, golden delicious, microwave, red delicious, total phenolic content

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Authors: Zafar Tabrez, Nizamuddin Khan

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Agriculture in India in the pre-green revolution period was mostly controlled by terrain, climate and edaphic factors. But after the introduction of innovative factors and technological inputs, green revolution occurred and agricultural scene witnessed great change. In the development of India’s agriculture, speedy, and extensive introduction of technological change is one of the crucial factors. The technological change consists of adoption of farming techniques such as use of fertilisers, pesticides and fungicides, improved variety of seeds, modern agricultural implements, improved irrigation facilities, contour bunding for the conservation of moisture and soil, which are developed through research and calculated to bring about diversification and increase of production and greater economic return to the farmers. The green revolution in India took place during late 60s, equipped with technological inputs like high yielding varieties seeds, assured irrigation as well as modern machines and implements. Initially the revolution started in Punjab, Haryana and western Uttar Pradesh. With the efforts of government, agricultural planners, as well as policy makers, the modern technocratic agricultural development scheme was also implemented and introduced in backward and marginal regions of the country later on. Agriculture sector occupies the centre stage of India’s social security and overall economic welfare. The country has attained self-sufficiency in food grain production and also has sufficient buffer stock. Our first Prime Minister, Jawaharlal Nehru said ‘everything else can wait but not agriculture’. There is still a continuous change in the technological inputs and cropping patterns. Keeping these points in view, author attempts to investigate extensively the mechanization of agriculture and the change by selecting western Trans-Ghaghara plain as a case study and block a unit of the study. It includes the districts of Gonda, Balrampur, Bahraich and Shravasti which incorporate 44 blocks. It is based on secondary sources of data by blocks for the year 1997 and 2007. It may be observed that there is a wide range of variations and the change in farm mechanization, i.e., agricultural machineries such as ploughs, wooden and iron, advanced harrow and cultivator, advanced thrasher machine, sprayers, advanced sowing instrument, and tractors etc. It may be further noted that due to continuous decline in size of land holdings and outflux of people for the same nature of works or to be employed in non-agricultural sectors, the magnitude and direction of agricultural systems are affected in the study area which is one of the marginalized regions of Uttar Pradesh, India.

Keywords: agriculture, technological inputs, farm mechanization, food production, cropping pattern

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Authors: A. Yönetken, A. Erol, A. Yakar, G. Peşmen

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The microstructure, mechanical properties and metalgraphic characteristics of Ni plated AlN-Astaloy Cr-M powders were investigated using specimens produced by tube furnace sintering at 1000-1400 °C temperature. A uniform nickel layer on AlN powders was deposited prior to sintering using electroless plating technique. A composite consisting of ternary additions, metallic phase, Ni and ceramic phase AlN within a matrix of Astaloy Cr-M had been prepared under Ar shroud and then tube furnace sintered. The experimental results carried out by using XRD (X-Ray Diffraction) and SEM (Scanning Electron Microscope) for composition (10% AlN-Astaloy Cr-M) 10% Ni at 1400 °C suggest that the best properties as 132.45HB and permittivity were obtained at 1400 °C.

Keywords: composite, electroless nickel plating, powder metallurgy, sintering

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Authors: S. B. Mayil Vealan, C. Sekar

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Bisphenol A (BIS A) and 4 Nitrophenol (4N) are the most prevalent environmental endocrine-disrupting chemicals which mimic hormones and have a direct relationship to the development and growth of animal and human reproductive systems. Moreover, intensive exposure to the compound is related to prostate and breast cancer, infertility, obesity, and diabetes. Hence, accurate and reliable determination techniques are crucial for preventing human exposure to these harmful chemicals. Lanthanum Copper Oxide (La₂Cu₂O₅) nanoparticles were synthesized and investigated through various techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy. Cyclic voltammetry and square wave voltammetry techniques are employed to evaluate the electrochemical behavior of as-synthesized samples toward the electrochemical detection of Bisphenol A and 4-Nitrophenol. Under the optimal conditions, the oxidation current increased linearly with increasing the concentration of BIS A and 4-N in the range of 0.01 to 600 μM with a detection limit of 2.44 nM and 3.8 nM. These are the lowest limits of detection and the widest linear ranges in the literature for this determination. The method was applied to the simultaneous determination of BIS A and 4-N in real samples (food packing materials and river water) with excellent recovery values ranging from 95% to 99%. Better stability, sensitivity, selectivity and reproducibility, fast response, and ease of preparation made the sensor well-suitable for the simultaneous determination of bisphenol and 4 Nitrophenol. To the best of our knowledge, this is the first report in which La₂Cu₂O₅ nano particles were used as efficient electron mediators for the fabrication of endocrine disruptor (BIS A and 4N) chemical sensors.

Keywords: endocrine disruptors, electrochemical sensor, Food contacting materials, lanthanum cuprates, nanomaterials

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Authors: Hammadi Larbi

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The major problem with oil-based drilling muds (reverse emulsions) is their thermodynamic instability and their high tendency to coalescence over time, irreversibly leading to destabilization. Water/Oil reverse emulsion drilling Muds are highly recommended when significant depths are reached. This study aimed to contribute experimentally to the knowledge of the structure (stability) and rheological behavior of drilling mud systems based on water/crude oil inverse emulsions through the investigation of the effect of organophilic clay. The chemical composition of organophilic clay such as VG69 shows a strong presence of silicon oxide (SiO2), followed by aluminum oxide (Al2O3), so these two elements are considered to be the main constituents of organophilic clays. The study also shows that the SiO2/Al2O3 ratio is equal to 3.52, which can be explained by the high content of free silica contained in the organophile clay used. The particle size analysis of the organophilic clays showed that the size of the of the particles analysed is in the range of 30 to 80 μm, this result ensures the correct particle size quality of organophilic clays and allows these powders to be used in Drilling mud systems.The experimental data of steady-state flow measurements are analyzed in the classic way by the Herschel-Bulkley model. Microscopic observation shows that the addition of quantities of organophilic clay type VG69 less than or equal to 3 g leading to the stability of the water/oil inverse emulsions, on the other hand, for quantities greater than 3 g, the emulsions are destabilized. The results obtained also showed that adding 3 g of organophilic clay to the crude oil drilling mud improves their stability by 70%.

Keywords: drilling muds, inverse emulsions, rheological behavior, yield stress, stability, organophilic clay

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Igor V. Grigoriev

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Understanding of biological processes encoded in fungi is instrumental in addressing future food, feed, and energy demands of the growing human population. Genomics is a powerful and quickly evolving tool to understand these processes. The Fungal Genomics Program of the US Department of Energy Joint Genome Institute (JGI) partners with researchers around the world to explore fungi in several large scale genomics projects, changing the fungal genomics landscape. The key trends of these changes include: (i) rapidly increasing scale of sequencing and analysis, (ii) developing approaches to go beyond culturable fungi and explore fungal ‘dark matter,’ or unculturables, and (iii) functional genomics and multi-omics data integration. Power of comparative genomics has been recently demonstrated in several JGI projects targeting mycorrhizae, plant pathogens, wood decay fungi, and sugar fermenting yeasts. The largest JGI project ‘1000 Fungal Genomes’ aims at exploring the diversity across the Fungal Tree of Life in order to better understand fungal evolution and to build a catalogue of genes, enzymes, and pathways for biotechnological applications. At this point, at least 65% of over 700 known families have one or more reference genomes sequenced, enabling metagenomics studies of microbial communities and their interactions with plants. For many of the remaining families no representative species are available from culture collections. To sequence genomes of unculturable fungi two approaches have been developed: (a) sequencing DNA from fruiting bodies of ‘macro’ and (b) single cell genomics using fungal spores. The latter has been tested using zoospores from the early diverging fungi and resulted in several near-complete genomes from underexplored branches of the Fungal Tree, including the first genomes of Zoopagomycotina. Genome sequence serves as a reference for transcriptomics studies, the first step towards functional genomics. In the JGI fungal mini-ENCODE project transcriptomes of the model fungus Neurospora crassa grown on a spectrum of carbon sources have been collected to build regulatory gene networks. Epigenomics is another tool to understand gene regulation and recently introduced single molecule sequencing platforms not only provide better genome assemblies but can also detect DNA modifications. For example, 6mC methylome was surveyed across many diverse fungi and the highest among Eukaryota levels of 6mC methylation has been reported. Finally, data production at such scale requires data integration to enable efficient data analysis. Over 700 fungal genomes and other -omes have been integrated in JGI MycoCosm portal and equipped with comparative genomics tools to enable researchers addressing a broad spectrum of biological questions and applications for bioenergy and biotechnology.

Keywords: fungal genomics, single cell genomics, DNA methylation, comparative genomics

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Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

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Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: support vector mechanism (SVM), machine learning (ML), support vector machines (SVM), department of transportation (DFT)

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Authors: Raffaele Danilo Esposito, Domingo Planes Meseguer, Maria Del Pilar Dorado Rodriguez

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As far as we know, it is still unavailable a commercial solution which would allow to manage, openly and configurable up to user needs, the huge amount of data generated in a modern Radiation Oncology Department. Currently, available information management systems are mainly focused on Record & Verify and clinical data, and only to a small extent on physical data. Thus, results in a partial and limited use of the actually available information. In the present work we describe the implementation at our department of a centralized information management system based on a web server. Our system manages both information generated during patient planning and treatment, and information of general interest for the whole department (i.e. treatment protocols, quality assurance protocols etc.). Our objective it to be able to analyze in a simple and efficient way all the available data and thus to obtain quantitative evaluations of our treatments. This would allow us to improve our work flow and protocols. To this end we have implemented a relational data base which would allow us to use in a practical and efficient way all the available information. As always we only use license free software.

Keywords: information management system, radiation oncology, medical physics, free software

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Authors: Komol Phaisarn, Natcha Wattanaprapa

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This research is a survey research with an objective to study the safety of data storage devices of graduate students of academic year 2013, Suan Sunandha Rajabhat University. Data were collected by questionnaire on the safety of data storage devices according to CIA principle. A sample size of 81 was drawn from population by purposive sampling method. The results show that most of the graduate students of academic year 2013 at Suan Sunandha Rajabhat University use handy drive to store their data and the safety level of the devices is at good level.

Keywords: security, safety, storage devices, graduate students

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Authors: Ayu Dwi Hardiyanti, Bernardus Anggit Winahyu, I. Gusti Agung Ayu Sugita Sari, Lestari Sutra Simamora, I. Wayan Warmada

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The Penosogan Formation sandstone, that has Middle Miosen age, has been deemed as a reservoir potential based on sample data from sandstone outcrop in Kebakalan and Kedawung villages, Karangsambung sub-district, Kebumen Regency, Central Java. This research employs the following analytical methods; petrography, X-ray diffraction (XRD), and porosity test. Based on the presence of micritic sandstone, muddy micrite, and muddy sandstone, the Penosogan Formation sandstone has a fine-coarse granular size and middle-to-fine sorting. The composition of the sandstone is mostly made up of plagioclase, skeletal grain, and traces of micrite. The percentage of clay minerals based on petrographic analysis is 10% and appears to envelop grain, resulting enveloping grain which reduces the porosity of rocks. The porosity types as follows: interparticle, vuggy, channel, and shelter, with an equant form of cement. Moreover, the diagenesis process involves compaction, cementation, authigenic mineral growth, and dissolving due to feldspar alteration. The maturity of the reservoir can be seen through the X-ray diffraction analysis results, using ethylene glycol solution for clay minerals fraction transformed from smectite–illite. Porosity test analysis showed that the Penosogan Formation sandstones has a porosity value of 22% based on the Koeseomadinata classification, 1980. That shows high maturity is very influential for the quality of reservoirs sandstone of the Penosogan Formation.

Keywords: sandstone reservoir, Penosogan Formation, smectite, XRD

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Authors: Vitoldas Vaitkevičius, Evaldas Šerelis

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Silica fume, also known as microsilica (MS) or condensed silica fume is a by-product of the production of silicon metal or ferrosilicon alloys. Silica fume is one of the most effective pozzolanic additives which could be used for ultrahigh performance and other types of concrete. Despite the fact, however is not entirely clear, which amount of silica fume is most optimal for UHPC. Main objective of this experiment was to find optimal amount of silica fume for UHPC with and without thermal treatment, when different amount of quartz powder is substituted by silica fume. In this work were investigated four different composition of UHPC with different amount of silica fume. Silica fume were added 0, 10, 15 and 20% of cement (by weight) to UHPC mixture. Optimal amount of silica fume was determined by slump, viscosity, qualitative and quantitative XRD analysis and compression strength tests methods.

Keywords: compressive strength, silica fume, ultrahigh performance concrete, XRD

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Authors: Siddique Ullah Baig, Alisha Manzoor

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The remotest, mountainous, and icy Broghil Valley is a high-profile protected area as a national park, which hosts one of the highest altitude permanent human settlements on the earth. This park hosts a distributed but diverse range of habitats. Due to a lack of infrastructures, higher altitudes, and harsh environmental conditions, poverty-stricken inhabitants mostly rely on its resources, causing ecological dis-balance. This study aims to investigate the environmental degradation of natural resources of the park based on empirical evidence from stakeholders and geoinformatics. The result shows that one-fourth of the park is a gently undulating basin dotted with water bodies / grass, and agricultural land and three fourth is entirely rugged with steep mountains and glaciers. There are virtually no forests as the arid cold tundra climate and high altitude prevent tree growth. Rapid three-decadal land cover changes have led to ecological disequilibrium of the park, narrowing the traditional diverse food base, decreasing the resilience of biodiversity and local livelihoods as crop-land has shifted towards fallow, alpine-grass to peat-land and snow/glacial ice area to bare-soil/rocks. The local community believes in exploiting whatever vegetation or organic material is available for use as food, fodder, and fuel. The permanent presence of the community and limited cost-effective options in the park will be a challenge forever to maintain undisturbed natural processes as the objective of a national park.

Keywords: Broghil National Park, natural resources, environmental degradation, land cover

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Authors: Kaddi Mohammed, A. Benatiallah, D. Benatiallah

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Data grid is a technology that has full emergence of new challenges, such as the heterogeneity and availability of various resources and geographically distributed, fast data access, minimizing latency and fault tolerance. Researchers interested in this technology address the problems of the various systems related to the industry such as task scheduling, load balancing and replication. The latter is an effective solution to achieve good performance in terms of data access and grid resources and better availability of data cost. In a system with duplication, a coherence protocol is used to impose some degree of synchronization between the various copies and impose some order on updates. In this project, we present an approach for placing replicas to minimize the cost of response of requests to read or write, and we implement our model in a simulation environment. The placement techniques are based on a cost model which depends on several factors, such as bandwidth, data size and storage nodes.

Keywords: response time, query, consistency, bandwidth, storage capacity, CERN

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Authors: Emmanuel Bole Akinpelu

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Festival is a social event that takes place every year which showcase culture and other social activities that usually take place in an environment or town. However, Oranyan Festival is an annual event organized and celebrated in Oyo town in honor of Oranyan the great who is reputed to be the overall head of the Kings of the Yoruba. This event is attended by people from all works of life. The Oyos are used to celebrating various cultural festivals; like Ogun, Oya, Sango, Egungun, Obatala and others. However, Oranyan festival in Oyo is a recent development in honour of Oranyan. He was said to be powerful and an embodiment of a unique cultural tradition. The study examined the significance of the festival to the Oyo Yoruba group. Oyo Yoruba cultural heritage include; Ewi, Ijala, Traditional food ‘Amala and Gbegiri’, Ekun Iyawo, (Bridal Chants), Traditional Music, Traditional Dance, Traditional Game ‘Ayo Olopon’ Eke (Traditional wrestling) and others. Data for this work was gathered through archival sources as journals and relevant publications on the various Oyo Yoruba Traditional Art and Culture. The study is of the opinion that the festival has influence over the religion, Political, economic and other aspects of the modern day traditions. The study also revealed that Oranyan Festival made people to have a better understanding of their rich Cultural Heritage and promoted unity among all and sundry. It also promotes peace among the people. Conclusively, it promotes the rich Cultural Heritage of Oyo Yoruba’s both within and outside NIGERIA and the world at large.

Keywords: Yoruba Oyo, arts and culture, Oranyan, festival

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Authors: Komal Niazi, He Guoqiang

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This paper is focused on ‘CPEC (China Pakistan Economic Corridor) a changing mechanism in Pakistan’. China Pakistan Economic Corridor (CPEC) activity under OBOR (One Belt One Road (OBOR) CPEC is a piece of the bigger umbrella and goes for giving another hallway of exchange for China and Pakistan and is relied upon to profit the entire of South Asian area. But this study reveals that significance of acculturation can never be overemphasized in the investigation of diverse impacts and the routes people groups of various ethnic personalities figure out how to adjust and acknowledge the social attributes of a larger part group in a multiethnic culture. This study also deals with the effects of acculturation which can be seen at multiple levels through CPEC for both Pakistani and Chinese people, who were working on this project. China and Pakistan exchanged the cultural and social patterns with each other. Probably the most perceptible gathering level impacts of cultural assimilation regularly incorporate changes in sustenance (food), clothing, and language. At the individual level, the procedure of cultural assimilation alludes to the socialization procedure by which the Pakistani local people and Chinese who were working in Pakistan adopted values, traditions, attitudes, states of mind, and practices. But China has imposed discourse through economic power and language. CPEC dominates Pakistan’s poor area’s and changes their living, social and cultural values. People also claimed this acculturation was a great threat to their cultural values and religious beliefs. Main findings of the study clearly ascertained that research was to find out the conceptual understanding of people about the acculturation process through CPEC. At the cultural level, aggregate activities and social organizations end up plainly adjusted, and at the behavioral level, there are changes in a person's day by day behavioral collection and some of the time in experienced anxiety. Anthropological data methods were used to collect data, like snowball and judgmental sampling, case studied methods.

Keywords: CPEC, acculturation process, language discourse, social norms, cultural values, religious beliefs

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Authors: Abdelkarim Mahdhi, Fdhila Kais, Faouzi Lamari, Zeineb Hmila, Fathi Kamoun, Maria Ángeles Esteban, Amina Bakhrouf

Abstract:

Aquaculture is the world’s fastest growing food-production sector. However, one of the most serious problems regarding the culture of marine fishes is the mortality associated with pathogenic bacteria that occurs in the critical phases of larval development. Conventional approaches, such as the use of antimicrobial drugs to control diseases, have had limited success in the prevention or cure of aquatic diseases. Promising alternatives to antibiotics are probiotics, which are food supplements consisting of live microorganisms that benefit the host organism. In the search for more effective and environmentally friendly treatments with probionts against pathogenic species in shrimp larval culture, the probiotic properties of Bacillus strains isolated from Artemia culture such as antibacterial activity, adhesion, pathogenicity, toxicity and the effect of marine stress on viability and survival were investigated, as well as the changes occurring in their properties. Analyses showed that these bacteria corresponded to the genus Bacillus sp. Antagonism and adherence assays revealed that these strains have an inhibitory effect against pathogenic bacteria in vitro and in vivo conditions and are fairly adherent. Challenge tests performed with Artemia larvae provided evidence that the tested Bacillus strains were neither pathogenic nor toxic to the host. The tested strains maintained their viability and their probiotic properties during the period of study. The results suggest that the tested strains have suffered changes allowing them to survive in seawater in the absence of nutrients and outside their natural host, identifying them as potential probiotic candidates for Artemia culture.

Keywords: bacillus, probiotic, cell viability, stress response

Procedia PDF Downloads 386

Authors: W. Fatmi, F. Kriba, Z. Kechrid

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The aim of this study was to investigate the effect of vitamin C on blood biochemical parameters, tissue zinc, and antioxidants enzymes in diabetic rats fed a zinc-deficient diet. For that purpose, Alloxan-induced diabetic rats were divided into four groups. The first group was fed a zinc-sufficient diet while the second group was fed a zinc-deficient diet. The third and fourth groups received zinc-sufficient or zinc-deficient diets plus oral vitamin C (1mg/l) for 27 days. Body weight and food intake were recorded regularly during 27 days. On day 28, animals were killed and glucose, total lipids, triglycerides, protein, urea, serum zinc , tissues zinc concentrations, liver glycogen, GSH, TBARS concentrations and serum GOT, GPT, ALP and LDH, liver GSH-Px, GST and Catalase activities were determined. Body weight gain and food intake of zinc deficient diabetic animals at the end of experimental period was significantly lower than that of zinc adequate diabetic animals. Dietary zinc intake significantly increased glucose, lipids, triglycerides, urea, and liver TBARS levels of zinc deficient diabetic rats. In contrast, serum zinc, tissues zinc, protein, liver glycogen and GSH levels were decreased. The consumption of zinc deficient diet led also to an increase in serum GOT, GPT and liver GST accompanied with a decrease in serum ALP, LDH and liver GSH-Px, CAT activities. Meanwhile, vitamin C treatment was ameliorated all the previous parameters approximately to their normal levels. Vitamin C supplementation presumably acting as an antioxidant, and it probably led to an improvement of insulin activity, which significantly reduced the severity of zinc deficiency in diabetes.

Keywords: antioxidant, experimental diabetes, liver enzymes, vitamin c, zinc deficiency

Procedia PDF Downloads 366

Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

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Authors: Zebiri Saliha

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Ochratoxin A (OTA) is a mycotoxin produced by certain species of the genera Aspergillus and Penicillium, primarily found in cereals, coffee, and grapevine products. Its accumulation in the body can lead to nephrotoxic, teratogenic, immunosuppressive, and carcinogenic effects. The objective of this study is to investigate the contamination of consumed wheat and its derivatives by toxic fungi in Algeria. For this purpose, an analysis of 200 samples was conducted, including 90 samples of durum wheat and common wheat and 110 samples of wheat derivatives collected from mills (semolina and flour manufacturers). The results revealed an average fungal contamination rate ranging from 60% to 100%. The identified fungal isolates primarily belonged to the genera Aspergillus (70%), Penicillium (27.5%), Alternaria (40%), and Mucor (19.4%). The density of the fungal flora was higher in products intended for animal consumption, such as durum wheat flour (2525 CFU/g), wheat scraps (3175 CFU/g), and wheat bran (2950 CFU/g). Conversely, low fungal density was observed in fine semolina (900 CFU/g) and flour (800 CFU/g) intended for human consumption. The genus Penicillium was isolated in 46% of the analyzed samples of durum wheat derivatives and in 62.7% of the analyzed samples of common wheat derivatives. The Aspergillus genus dominated the majority of the analyzed samples. Molecular identification of Aspergillus and Penicillium isolates by sequencing ITS1-5.8S-ITS2 regions of DNAr and a part of the calmodulin (CaM) gene indicated that the species involved in the production of OTA in wheat and its derivatives were mainly Aspergillus ochraceus, A. westerdijkia, A. alliaceus, A. carbonarius, and Penicillium islandicus. The amounts of OTA produced by these species were determined by HPLC-FLD and ranged between 0,8.9 and 3033μg/g. Given that food safety and quality are major concerns today, understanding the microbial biodiversity of wheat is crucial because it is a staple food in Algeria.

Keywords: wheat derivatives, Aspergillus, microbial biodiversity, OTA

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Authors: S. Anastasiou, C. Nathanailides

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The purpose of this study is to examine the possible link between employee and customer satisfaction. The service provided by employees, help to build a good relationship with customers and can help at increasing their loyalty. Published data for job satisfaction and indicators of customer services were gathered from relevant published works which included data from five different countries. The reviewed data indicate a significant correlation between indicators of customer and employee satisfaction in the Banking sector. There was a significant correlation between the two parameters (Pearson correlation R2=0.52 P<0.05) The reviewed data provide evidence that there is some practical evidence which links these two parameters.

Keywords: job satisfaction, job performance, customer’ service, banks, human resources management

Procedia PDF Downloads 321

Authors: Marine Shavlakadze

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From the raw material base existed in Georgia (manganese ores, manganese containing mud), particularly, within the point of view of production availability, especial interest is paid to micro- fertilizers containing manganese. As a result of conducted investigation, there was established receiving of such manganese containing materials on the basis of manganese raw-material base (ore, mud) existed in Georgia, which shall be able to maximally provide assimilation ability of manganese, as microelement, in the desired period of time. And also, determinant of effectiveness and competitiveness of received materials with new composition shall become high content (more than 30%) of microelements in them (in comparison with existed similar products), when the total sum of useful components presented in them (active i.e. assimilated) is more than 50-70%, i.e. received materials belong to the materials having low-ballast and functionally revealed possibilities.

Keywords: manganese, fertilizers, non-ballast, micro- fertilizers

Procedia PDF Downloads 267

Authors: Suman Podder

Abstract:

As Australian ‘Open Banking’ allows customers to share their financial data with accredited Third-Party Providers (‘TPPs’), it is necessary to evaluate whether the regulators have achieved the balance between protecting customer data privacy and promoting data-related innovation. Recognising the need to increase customers’ influence on their own data, and the benefits of data-related innovation, the Australian Government introduced ‘Consumer Data Right’ (‘CDR’) to the banking sector through Open Banking regulation. Under Open Banking, TPPs can access customers’ banking data that allows the TPPs to tailor their products and services to meet customer needs at a more competitive price. This facilitated access and use of customer data will promote innovation by providing opportunities for new products and business models to emerge and grow. However, the success of Open Banking depends on the willingness of the customers to share their data, so the regulators have augmented the protection of data by introducing new privacy safeguards to instill confidence and trust in the system. The dilemma in policymaking is that, on the one hand, lenient data privacy laws will help the flow of information, but at the risk of individuals’ loss of privacy, on the other hand, stringent laws that adequately protect privacy may dissuade innovation. Using theoretical and doctrinal methods, this paper examines whether the privacy safeguards under Open Banking will add to the compliance burden of the participating financial institutions, resulting in the undesirable effect of stifling other policy objectives such as innovation. The contribution of this research is three-fold. In the emerging field of customer data sharing, this research is one of the few academic studies on the objectives and impact of Open Banking in the Australian context. Additionally, Open Banking is still in the early stages of implementation, so this research traces the evolution of Open Banking through policy debates regarding the desirability of customer data-sharing. Finally, the research focuses not only on the customers’ data privacy and juxtaposes it with another important objective of promoting innovation, but it also highlights the critical issues facing the data-sharing regime. This paper argues that while it is challenging to develop a regulatory framework for protecting data privacy without impeding innovation and jeopardising yet unknown opportunities, data privacy and innovation promote different aspects of customer welfare. This paper concludes that if a regulation is appropriately designed and implemented, the benefits of data-sharing will outweigh the cost of compliance with the CDR.

Keywords: consumer data right, innovation, open banking, privacy safeguards

Procedia PDF Downloads 141

Authors: Hyun-Woo Cho

Abstract:

Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

Procedia PDF Downloads 252