Search results for: nullity of graphs

Authors: Yamina Boughari, Ruxandra Mihaela Botez, Florian Theel, Georges Ghazi

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Clearance of flight control laws of a civil aircraft is a long and expensive process in the Aerospace industry. Thousands of flight combinations in terms of speeds, altitudes, gross weights, centers of gravity and angles of attack have to be investigated, and proved to be safe. Nonetheless, in this method, a worst flight condition can be easily missed, and its missing would lead to a critical situation. Definitively, it would be impossible to analyze a model because of the infinite number of cases contained within its flight envelope, that might require more time, and therefore more design cost. Therefore, in industry, the technique of the flight envelope mesh is commonly used. For each point of the flight envelope, the simulation of the associated model ensures the satisfaction or not of specifications. In order to perform fast, comprehensive and effective analysis, other varying parameters models were developed by incorporating variations, or uncertainties in the nominal models, known as Linear Fractional Representation LFR models; these LFR models were able to describe the aircraft dynamics by taking into account uncertainties over the flight envelope. In this paper, the LFRs models are developed using the speeds and altitudes as varying parameters; The LFR models were built using several flying conditions expressed in terms of speeds and altitudes. The use of such a method has gained a great interest by the aeronautical companies that have seen a promising future in the modeling, and particularly in the design and certification of control laws. In this research paper, we will focus on the Cessna Citation X open loop stability analysis. The data are provided by a Research Aircraft Flight Simulator of Level D, that corresponds to the highest level flight dynamics certification; this simulator was developed by CAE Inc. and its development was based on the requirements of research at the LARCASE laboratory. The acquisition of these data was used to develop a linear model of the airplane in its longitudinal and lateral motions, and was further used to create the LFR’s models for 12 XCG /weights conditions, and thus the whole flight envelope using a friendly Graphical User Interface developed during this study. Then, the LFR’s models are analyzed using Interval Analysis method based upon Lyapunov function, and also the ‘stability and robustness analysis’ toolbox. The results were presented under the form of graphs, thus they have offered good readability, and were easily exploitable. The weakness of this method stays in a relatively long calculation, equal to about four hours for the entire flight envelope.

Keywords: flight control clearance, LFR, stability analysis, robustness analysis

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Authors: Mariam Tsitsagi, Ana Berdzenishvili

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Rainfall intensity change is one of the main indicators of climate change. It has a great influence on agriculture as one of the main factors causing soil erosion. Splash and sheet erosion are one of the most prevalence and harmful for agriculture. It is invisible for an eye at first stage, but the process will gradually move to stream cutting erosion. Our study provides the assessment of rainfall erosivity potential with the use of modern research methods in Kakheti region. The region is the major provider of wheat and wine in the country. Kakheti is located in the eastern part of Georgia and characterized quite a variety of natural conditions. The climate is dry subtropical. For assessment of the exact rate of rainfall erosion potential several year data of rainfall with short intervals are needed. Unfortunately, from 250 active metro stations running during the Soviet period only 55 of them are active now and 5 stations in Kakheti region respectively. Since 1936 we had data on rainfall intensity in this region, and rainfall erosive potential is assessed, in some old papers, but since 1990 we have no data about this factor, which in turn is a necessary parameter for determining the rainfall erosivity potential. On the other hand, researchers and local communities suppose that rainfall intensity has been changing and the number of haily days has also been increasing. However, finding a method that will allow us to determine rainfall erosivity potential as accurate as possible in Kakheti region is very important. The study period was divided into three sections: 1936-1963; 1963-1990 and 1990-2015. Rainfall erosivity potential was determined by the scientific literature and old meteorological stations’ data for the first two periods. And it is known that in eastern Georgia, at the boundary between steppe and forest zones, rainfall erosivity in 1963-1990 was 20-75% higher than that in 1936-1963. As for the third period (1990-2015), for which we do not have data of rainfall intensity. There are a variety of studies, where alternative ways of calculating the rainfall erosivity potential based on lack of data are discussed e.g.based on daily rainfall data, average annual rainfall data and the elevation of the area, etc. It should be noted that these methods give us a totally different results in case of different climatic conditions and sometimes huge errors in some cases. Three of the most common methods were selected for our research. Each of them was tested for the first two sections of the study period. According to the outcomes more suitable method for regional climatic conditions was selected, and after that, we determined rainfall erosivity potential for the third section of our study period with use of the most successful method. Outcome data like attribute tables and graphs was specially linked to the database of Kakheti, and appropriate thematic maps were created. The results allowed us to analyze the rainfall erosivity potential changes from 1936 to the present and make the future prospect. We have successfully implemented a method which can also be use for some another region of Georgia.

Keywords: erosivity potential, Georgia, GIS, Kakheti, rainfall

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Zelalem Teshager

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The Choke Mountains have several endangered and endemic wildlife species and provide important ecosystem services. Despite their environmental importance, the Choke Mountains are found in dangerous conditions. This raised the need for an evaluation of the community's perception of deforestation and its major drivers and suggested possible solutions in the Choke Mountains of northwestern Ethiopia. For this purpose, household surveys, key informant interviews, and focus group discussions were used. A total sample of 102 informants was used for this survey. A purposive sampling technique was applied to select the participants for in-depth interviews and focus group discussions. Both qualitative and quantitative data analyses were used. Computation of descriptive statistics such as mean, percentages, frequency, tables, figures, and graphs was applied to organize, analyze, and interpret the study. This study assessed smallholder agricultural land expansion, Fuel wood collection, population growth; encroachment, free grazing, high demand of construction wood, unplanned resettlement, unemployment, border conflict, lack of a strong forest protecting system, and drought were the serious causes of forest depletion reported by local communities. Loss of land productivity, Soil erosion, soil fertility decline, increasing wind velocity, rising temperature, and frequency of drought were the most perceived impacts of deforestation. Most of the farmers have a holistic understanding of forest cover change. Strengthening forest protection, improving soil and water conservation, enrichment planting, awareness creation, payment for ecosystem services, and zero grazing campaigns were mentioned as possible solutions to the current state of deforestation. Applications of Intervention measures, such as animal fattening, beekeeping, and fruit production can contribute to decreasing the deforestation causes and improve communities’ livelihood. In addition, concerted efforts of conservation will ensure that the forests’ ecosystems contribute to increased ecosystem services. The major drivers of deforestation should be addressed with government intervention to change dependency on forest resources, income sources of the people, and institutional set-up of the forestry sector. Overall, further reduction in anthropogenic pressure is urgent and crucial for the recovery of the afro-alpine vegetation and the interrelated endangered wildlife in the Choke Mountains.

Keywords: choke afro-alpine, deforestation, drivers, intervention measures, perceptions

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Authors: Bharti Singh, Shri K. Singh

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Child malnutrition is a multifaceted issue that transcends geographical boundaries. Malnutrition not only stunts physical growth but also leads to a spectrum of morbidities and child mortality. It is one of the leading causes of death (~50 %) among children under age five. Despite economic progress and advancements in healthcare, child malnutrition remains a formidable challenge for India. The objective is to investigate the impact of women's empowerment on child nutrition outcomes in India from 2006 to 2021. A composite index of women's empowerment was constructed using Confirmatory Factor Analysis (CFA), a rigorous technique that validates the measurement model by assessing how well-observed variables represent latent constructs. This approach ensures the reliability and validity of the empowerment index. Secondly, kernel density plots were utilised to visualise the distribution of key nutritional indicators, such as stunting, wasting, and overweight. These plots offer insights into the shape and spread of data distributions, aiding in understanding the prevalence and severity of malnutrition. Thirdly, linear polynomial graphs were employed to analyse how nutritional parameters evolved with the child's age. This technique enables the visualisation of trends and patterns over time, allowing for a deeper understanding of nutritional dynamics during different stages of childhood. Lastly, multilevel analysis was conducted to identify vulnerable levels, including State-level, PSU-level, and household-level factors impacting undernutrition. This approach accounts for hierarchical data structures and allows for the examination of factors at multiple levels, providing a comprehensive understanding of the determinants of child malnutrition. Overall, the utilisation of these statistical methodologies enhances the transparency and replicability of the study by providing clear and robust analytical frameworks for data analysis and interpretation. Our study reveals that NFHS-4 and NFHS-5 exhibit an equal density of severely stunted cases. NFHS-5 indicates a limited decline in wasting among children aged five, while the density of severely wasted children remains consistent across NFHS-3, 4, and 5. In 2019-21, women with higher empowerment had a lower risk of their children being undernourished (Regression coefficient= -0.10***; Confidence Interval [-0.18, -0.04]). Gender dynamics also play a significant role, with male children exhibiting a higher susceptibility to undernourishment. Multilevel analysis suggests household-level vulnerability (intra-class correlation=0.21), highlighting the need to address child undernutrition at the household level.

Keywords: child nutrition, India, NFHS, women’s empowerment

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Nihan Nugay, Nur Cicek Kekec, Kalman Toth, Turgut Nugay, Joseph P. Kennedy

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In recent years, polyurethane structures are paving the way for elastomer usage in biology, human medicine, and biomedical application areas. Polyurethanes having a combination of high oxidative and hydrolytic stability and excellent mechanical properties are focused due to enhancing the usage of PUs especially for implantable medical device application such as cardiac-assist. Currently, unique polyurethanes consisting of polyisobutylenes as soft segments and conventional hard segments, named as PIB-based PUs, are developed with precise NCO/OH stoichiometry (∽1.05) for obtaining PIB-based PUs with enhanced properties (i.e., tensile stress increased from ∽11 to ∽26 MPa and elongation from ∽350 to ∽500%). Static and dynamic mechanical properties were optimized by examining stress-strain graphs, self-organization and crystallinity (XRD) traces, rheological (DMA, creep) profiles and thermal (TGA, DSC) responses. Annealing procedure was applied for PIB-based PUs. Annealed PIB-based PU shows ∽26 MPa tensile strength, ∽500% elongation, and ∽77 Microshore hardness with excellent hydrolytic and oxidative stability. The surface characters of them were examined with AFM and contact angle measurements. Annealed PIB-based PU exhibits the higher segregation of individual segments and surface hydrophobicity thus annealing significantly enhances hydrolytic and oxidative stability by shielding carbamate bonds by inert PIB chains. According to improved surface and microstructure characters, greater efforts are focused on analyzing protein adsorption and calcification profiles. In biomedical applications especially for cardiological implantations, protein adsorption inclination on polymeric heart valves is undesirable hence protein adsorption from blood serum is followed by platelet adhesion and subsequent thrombus formation. The protein adsorption character of PIB-based PU examines by applying Bradford assay in fibrinogen and bovine serum albumin solutions. Like protein adsorption, calcium deposition on heart valves is very harmful because vascular calcification has been proposed activation of osteogenic mechanism in the vascular wall, loss of inhibitory factors, enhance bone turnover and irregularities in mineral metabolism. The calcium deposition on films are characterized by incubating samples in simulated body fluid solution and examining SEM images and XPS profiles. PIB-based PUs are significantly more resistant to hydrolytic-oxidative degradation, protein adsorption and calcium deposition than ElastEonTM E2A, a commercially available PDMS-based PU, widely used for biomedical applications.

Keywords: biomedical application, calcification, polyisobutylene, polyurethane, protein adsorption

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Authors: Cathy Basterfield

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Issue: To engage in one’s own health care, health professionals need to be aware of an individual’s specific skills and abilities for best communication. One of the most discussed is health literacy. One of the assumed skills and abilities for adults is an individuals’ health literacy. Background: A review of publicly available health content appears to assume all adult readers will have a broad and full capacity to read at a high level of literacy, often at a post-school education level. Health information writers and clinicians need to recognise one critical area for why there may be little or no change in a person’s behaviour, or no-shows to appointments. Perhaps unintentionally, they are miscommunicating with the majority of the adult population. Health information contains many literacy domains. It usually includes technical medical terms or jargon. Many fact sheets and other information require scientific literacy with or without specific numerical literacy. It may include graphs, percentages, timing, distance, or weights. Each additional word or concept in these domains decreases the readers' ability to meaningfully read, understand and know what to do with the information. An attempt to begin to read the heading where long or unfamiliar words are used will reduce the readers' motivation to attempt to read. Critically people who have low literacy are overwhelmed when pages are covered with lots of words. People attending a health environment may be unwell or anxious about a diagnosis. These make it harder to read, understand and know what to do with the information. But access to health information must consider an even wider range of adults, including those with poor school attainment, migrants, and refugees. It is also homeless people, people with mental health illnesses, or people who are ageing. People with low literacy also may include people with lifelong disabilities, people with acquired disabilities, people who read English as a second (or third) language, people who are Deaf, or people who are vision impaired. Outcome: This paper will discuss Easy English, which is developed for adults. It uses the audiences’ everyday words, short sentences, short words, and no jargon. It uses concrete language and concrete, specific images to support the text. It has been developed in Australia since the mid-2000s. This paper will showcase various projects in the health domain which use Easy English to improve the understanding and functional use of written information for the large numbers of adults in our communities who do not have the health literacy to manage a range of day to day reading tasks. See examples from consent forms, fact sheets and choice options, instructions, and other functional documents, where Easy English has been developed. This paper will ask individuals to reflect on their own work practice and consider what written information must be available in Easy English. It does not matter how cutting-edge a new treatment is; when adults can not read or understand what it is about and the positive and negative outcomes, they are less likely to be engaged in their own health journey.

Keywords: health literacy, inclusion, Easy English, communication

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Authors: E. Calil, L. A. Pereira

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The acquisition of orthography is a complex process, involving both lexical and grammatical questions. This learning occurs simultaneously with the domain of multiple textual aspects (e.g.: graphs, punctuation, etc.). However, most of the research on orthographic acquisition focus on this acquisition from an autonomous point of view, separated from the process of textual production. This means that their object of analysis is the production of words selected by the researcher or the requested sentences in an experimental and controlled setting. In addition, the analysis of the Spelling Problems (SP) are identified by the researcher on the sheet of paper. Considering the perspective of Textual Genetics, from an enunciative approach, this study will discuss the SPs recognized by dyads of newly literate students, while they are writing a text collaboratively. Six proposals of textual production were registered, requested by a 2nd year teacher of a Portuguese Primary School between January and March 2015. In our case study we discuss the SPs recognized by the dyad B and L (7 years old). We adopted as a methodological tool the Ramos System audiovisual record. This system allows real-time capture of the text in process and of the face-to-face dialogue between both students and their teacher, and also captures the body movements and facial expressions of the participants during textual production proposals in the classroom. In these ecological conditions of multimodal registration of collaborative writing, we could identify the emergence of SP in two dimensions: i. In the product (finished text): SP identification without recursive graphic marks (without erasures) and the identification of SPs with erasures, indicating the recognition of SP by the student; ii. In the process (text in progress): identification of comments made by students about recognized SPs. Given this, we’ve analyzed the comments on identified SPs during the text in progress. These comments characterize a type of reformulation referred to as Commented Oral Erasure (COE). The COE has two enunciative forms: Simple Comment (SC) such as ' 'X' is written with 'Y' '; or Unfolded Comment (UC), such as ' 'X' is written with 'Y' because...'. The spelling COE may also occur before or during the SP (Early Spelling Recognition - ESR) or after the SP has been entered (Later Spelling Recognition - LSR). There were 631 words entered in the 6 stories written by the B-L dyad, 145 of them containing some type of SP. During the text in progress, the students recognized orally 174 SP, 46 of which were identified in advance (ESRs) and 128 were identified later (LSPs). If we consider that the 88 erasure SPs in the product indicate some form of SP recognition, we can observe that there were twice as many SPs recognized orally. The ESR was characterized by SC when students asked their colleague or teacher how to spell a given word. The LSR presented predominantly UC, verbalizing meta-orthographic arguments, mostly made by L. These results indicate that writing in dyad is an important didactic strategy for the promotion of metalinguistic reflection, favoring the learning of spelling.

Keywords: collaborative writing, erasure, learning, metalinguistic awareness, spelling, text production

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Authors: Tamas Dani

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The author’s research explores the geo-economical role and importance of some small and medium sized states, reviews their adaption strategies in foreign trade and also in foreign affairs in the course of changing into a multipolar world, uses international background. With these, the paper analyses the recent years and the future of ‘Opening towards Eastern foreign economic policies’ from East-Central Europe and parallel with that the ‘Western foreign economy policies’ from Asia, as the Chinese One Belt One Road new silk route plans (so far its huge part is an infrastructural development plan to reach international trade and investment aims). It can be today’s question whether these ideas will reshape the global trade or not. How does the new silk road initiatives and the Eurasian Union reflect the effect of globalization? It is worth to analyse that how did Central and Eastern European countries open to Asia; why does China have the focus of the opening policies in many countries and why could China be seen as the ‘winner’ of the world economic crisis after 2008. The research is based on the following methodologies: national and international literature, policy documents and related design documents, complemented by processing of international databases, statistics and live interviews with leaders from East-Central European countries’ companies and public administration, diplomats and international traders. The results also illustrated by mapping and graphs. The research will find out as major findings whether the state decision-makers have enough margin for manoeuvres to strengthen foreign economic relations. This work has a hypothesis that countries in East-Central Europe have real chance to diversify their relations in foreign trade, focus beyond their traditional partners. This essay focuses on the opportunities of East-Central-European countries in diversification of foreign trade relations towards China and Russia in terms of ‘Eastern Openings’. The effects of the new silk road initiatives and the Eurasian Union to Hungary’s economy with a comparing outlook on East-Central European countries and exploring common regional cooperation opportunities in this area. The essay concentrate on the changing trade relations between East-Central-Europe and China as well as Russia, try to analyse the effects of the new silk road initiatives and the Eurasian Union also. In the conclusion part, it shows how the cooperation is necessary for the East-Central European countries if they want to have a non-asymmetric trade with Russia, China or some Chinese regions (Pearl River Delta, Hainan, …). The form of the cooperation for the East-Central European nations can be Visegrad 4 Cooperation (V4), Central and Eastern European Countries (CEEC16), 3 SEAS Cooperation (or BABS – Baltic, Adriatic, Black Seas Initiative).

Keywords: China, East-Central Europe, foreign trade relations, geoeconomics, geopolitics, Russia

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Authors: Hamed Khosravi, Reza Eslami-Farsani

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Increased interest in lightweight and efficient structural components has created the need for selecting materials with improved mechanical properties. To do so, composite materials are being widely used in many applications, due to durability, high strength and modulus, and low weight. Among the various composite structures, grid-stiffened structures are extensively considered in various aerospace and aircraft applications, because of higher specific strength and stiffness, higher impact resistance, superior load-bearing capacity, easy to repair, and excellent energy absorption capability. Although there are a good number of publications on the design aspects and fabrication of grid structures, little systematic work has been reported on their material modification to improve their properties, to our knowledge. Therefore, the aim of this research is to study the reinforcing effect of silica nanoparticles on the flexural properties of epoxy/E-glass isogrid panels under three-point bending test. Samples containing 0, 1, 3, and 5 wt.% of the silica nanoparticles, with 44 and 48 vol.% of the glass fibers in the ribs and skin components respectively, were fabricated by using a manual filament winding method. Ultrasonic and mechanical routes were employed to disperse the nanoparticles within the epoxy resin. To fabricate the ribs, the unidirectional fiber rovings were impregnated with the matrix mixture (epoxy + nanoparticles) and then laid up into the grooves of a silicone mold layer-by-layer. At once, four plies of woven fabrics, after impregnating into the same matrix mixture, were layered on the top of the ribs to produce the skin part. In order to conduct the ultimate curing and to achieve the maximum strength, the samples were tested after 7 days of holding at room temperature. According to load-displacement graphs, the bellow trend was observed for all of the samples when loaded from the skin side; following an initial linear region and reaching a load peak, the curve was abruptly dropped and then showed a typical absorbed energy region. It would be worth mentioning that in these structures, a considerable energy absorption was observed after the primary failure related to the load peak. The results showed that the flexural properties of the nanocomposite samples were always higher than those of the nanoparticle-free sample. The maximum enhancement in flexural maximum load and energy absorption was found to be for the incorporation of 3 wt.% of the nanoparticles. Furthermore, the flexural stiffness was continually increased by increasing the silica loading. In conclusion, this study suggested that the addition of nanoparticles is a promising method to improve the flexural properties of grid-stiffened fibrous composite structures.

Keywords: grid-stiffened composite structures, nanocomposite, three point flexural test , energy absorption

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Authors: Malek Miladi, Miguel Vegara, Maria Perez-Infantes, Khaled Mohamed Ramadan, Antonio Ruiz-Canales, Damaris Nunez-Gomez

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Coffee is the second consumed commodity worldwide, yet it also generates colossal waste. Proper management of coffee waste is proposed by converting them into products with higher added value to achieve sustainability of the economic and ecological footprint and protect the environment. Based on this, a study looking at the recovery of coffee waste is becoming more relevant in recent decades. Spent coffee grounds (SCG's) resulted from brewing coffee represents the major waste produced among all coffee industry. The fact that SCGs has no economic value be abundant in nature and industry, do not compete with agriculture and especially its high oil content (between 7-15% from its total dry matter weight depending on the coffee varieties, Arabica or Robusta), encourages its use as a sustainable feedstock for bio-oil production. The bio-oil extraction is a crucial step towards biodiesel production by the transesterification process. However, conventional methods used for oil extraction are not recommended due to their high consumption of energy, time, and generation of toxic volatile organic solvents. Thus, finding a sustainable, economical, and efficient extraction technique is crucial to scale up the process and to ensure more environment-friendly production. Under this perspective, the aim of this work was the statistical study to know an efficient strategy for oil extraction by n-hexane using indirect sonication. The coffee waste mixed Arabica and Robusta, which was used in this work. The temperature effect, sonication time, and solvent-to-solid ratio on the oil yield were statistically investigated as dependent variables by Central Composite Rotatable Design (CCRD) 23. The results were analyzed using STATISTICA 7 StatSoft software. The CCRD showed the significance of all the variables tested (P < 0.05) on the process output. The validation of the model by analysis of variance (ANOVA) showed good adjustment for the results obtained for a 95% confidence interval, and also, the predicted values graph vs. experimental values confirmed the satisfactory correlation between the model results. Besides, the identification of the optimum experimental conditions was based on the study of the surface response graphs (2-D and 3-D) and the critical statistical values. Based on the CCDR results, 29 ºC, 56.6 min, and solvent-to-solid ratio 16 were the better experimental conditions defined statistically for coffee waste oil extraction using n-hexane as solvent. In these conditions, the oil yield was >9% in all cases. The results confirmed the efficiency of using an ultrasound bath in extracting oil as a more economical, green, and efficient way when compared to the Soxhlet method.

Keywords: coffee waste, optimization, oil yield, statistical planning

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Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

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Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

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Authors: Sayyed Mostafa Ahmadi, Neda Raeesi

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Background and Objectives: Cervical spondylosis is a common problem that affects the adult spine and is the most common cause of radiculopathy and myelopathy in older patients. Anterior discectomy and fusion is a well-known technique in degenerative cervical disc disease. However, one of the late undesirable complications is adjacent disc degeneration, which affects about 91% of patients in ten years. Many factors can be effective in causing this complication, but some are still debatable. Discovering these risk factors and eliminating them can improve the quality of life. Methods: This is a retrospective cohort study. All patients who underwent anterior discectomy and fusion surgery in the neurosurgery ward of Imam Khomeini Hospital between 2013 and 2016 were evaluated. Their demographic information was collected. All patients were visited and examined for radiculopathy, myelopathy, and muscular force. At the same visit, all patients were asked to have a facelift, and neck profile, as well as a neck MRI(General Tesla 3). Preoperative graphs were used to measure the diameter of the cervical canal(Pavlov ratio) and to evaluate sagittal alignment(Cobb Angle). Preoperative MRI of patients was reviewed for anterior and posterior longitudinal ligament calcification. Result: In this study, 57 patients were studied. The mean age of patients was 50.63 years, and 49.1% were male. Only 3.5% of patients had anterior and posterior longitudinal ligament calcification. Symptomatic ASD was observed in 26.6%. The X-rays and MRIs showed evidence of 80.7% radiological ASD. Among patients who underwent one-level surgery, 20% had symptomatic ASD, but among patients who underwent two-level surgery, the rate of ASD was 50%.In other words, the higher the number of surfaces that are operated and fused, the higher the probability of symptomatic ASD(P-value <0.05). The X-rays and MRIs showed 80.7% of radiological ASD. Among patients who underwent surgery at one level, 78% had radiological ASD, and this number was 92% among patients who underwent two-level surgery(P-value> 0.05). Demographic variables such as age, sex, height, weight, and BMI did not have a significant effect on the incidence of radiological ASD(P-value> 0.05), but sex and height were two influential factors on symptomatic ASD(P-value <0.05). Other related variables such as family history, smoking and exercise also have no significant effect(P-value> 0.05). Radiographic variables such as Pavlov ratio and sagittal alignment were also unaffected by the incidence of radiological and symptomatic ASD(P-value> 0.05). The number of surgical surfaces and the incidence of anterior and posterior longitudinal ligament calcification before surgery also had no statistically significant effect(P-value> 0.05). In the study of the ability of the neck to move in different directions, none of these variables are statistically significant in the two groups with radiological and symptomatic ASD and the non-affected group(P-value> 0.05). Conclusion: According to the findings of this study, this disease is considered to be a multifactorial disease. The incidence of radiological ASD is much higher than symptomatic ASD (80.7% vs. 26.3%) and sex, height and number of fused surfaces are the only factors influencing the incidence of symptomatic ASD and no variable influences radiological ASD.

Keywords: risk factors, anterior neck disectomy and fusion, adjucent segment degeneration, complication

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Authors: Glauberto S. Quirino, Emanuelly V. Pereira, Amana S. Figueiredo, Antonia T. F. Santos, Paulo R. A. Firmino, Denise F. F. Barbosa, Caroline B. Q. Aquino, Eveliny S. Martins, Cinthia G. P. Calou, Ana K. B. Pinheiro

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Introduction: During pregnancy there are adjustments in the physical, emotional, existential and sexual areas, which may contribute to changes in sexual behavior. The objective was to analyze the sexual behavior of pregnant women. Methods: Quantitative, exploratory-descriptive study, approved by the Ethics and Research Committee of the Regional University of Cariri. For data collection, it was used the Sexuality Questionnaire in Gestation and Sexual Quotient - Female Version. It was carried out in public institutions in the urban and rural areas of three municipalities of the Metropolitan Region of Cariri, south of Ceará, Brazil from February to September 2016. The sampling was proportional stratified by convenience. A total of 815 pregnant women who were literate and aged 20 years or over were broached. 461 pregnant women were excluded because of high risk, adolescence, saturation of the extract, incomplete filling of the instrument, mental and physical handicap, without sexual partner, and the sample was 354 pregnant. The data were grouped, organized and analyzed in the statistical program R Studio (version 386 3.2.4). Descriptive frequency statistics and non-parametric tests were used to analyze the variables, and the results were shown in graphs and tables. Results: The women presented a minimum age of 20, maximum 35 and average of 26.9 years, predominantly urban area residents, with a monthly income of up to one minimum wage (US$ 275,00), high school, catholic, with fixed partner, heterosexuals, multiparous, multiple sexual partners throughout life and with the beginning of sexual life in adolescence (median age 17 years). There was a reduction in sexual practices (67%) and when they were performed, they were more frequent in the first trimester (79.7%) and less frequent in the third trimester (30.5%). Preliminary sexual practices did not change and were more frequent in the second trimester (46.6%). Throughout the gestational trimesters, the partner was referred as the main responsible for the sexual initiative. The women performed vaginal sex (97.7%) and provided greater pleasure (42.8%) compared to non-penetrative sex (53.9%) (oral sex and masturbation). There was also a reduction in the sexual disposition of pregnant women (90.7%) and partner (72.9%), mainly in the first trimester (78.8%), and sexual positions. Sexual performance ranged from regular to good (49.7%). Level of schooling, marital status, sexual orientation of the pregnant woman and the partner, sexual practices and positions, preliminaries, frequency of sexual practices and importance attributed to them were variables that influenced negatively sexual performance and satisfaction. It is concluded that pregnancy negatively changes the sexual behavior of the women and it is suggested to further investigations and approach of the partner, in order to clarify the influence of these variables on the sexual function and subsidize intervention strategies, with a view to the integrality of sexual and reproductive health.

Keywords: obstetric nursing, pregnant women, sexual behavior, women's health

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Authors: Corinne Zurmuehle, Andreas Christoph Weber

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In 2019, the Swiss Federal Institute of Sport Magglingen (SFISM) conducted a mixed-methods study on the Swiss elite sports system, which yielded a large quantity of research data. In a quantitative online survey, 1151 elite sports athletes, 542 coaches, and 102 Performance Directors of national sports federations (NF) have submitted their perceptions of the national support measures of the Swiss elite sports system. These data provide an essential database for the further development of the Swiss elite sports system. The results were published in a report presenting the results divided into 40 Olympic summer and 14 winter sports (Olympic classification). The authors of this paper assume that, in practice, this division is too unspecific to assess where further measures would be needed. The aim of this paper is to find appropriate parameters for data visualization in order to identify disparities in sports promotion that allow an assessment of where further interventions by Swiss Olympic (NF umbrella organization) are required. Method: First, the variable 'salary earned from sport' was defined as a variable to measure the impact of elite sports promotion. This variable was chosen as a measure as it represents an important indicator for the professionalization of elite athletes and therefore reflects national level sports promotion measures applied by Swiss Olympic. Afterwards, the variable salary was tested with regard to the correlation between Olympic classification [a], calculating the Eta coefficient. To estimate the appropriate parameters for data visualization, the correlation between salary and four further parameters was analyzed by calculating the Eta coefficient: [a] sport; [b] prioritization (from 1 to 5) of the sports by Swiss Olympic; [c] gender; [d] employment level in sports. Results & Discussion: The analyses reveal a very small correlation between salary and Olympic classification (ɳ² = .011, p = .005). Gender demonstrates an even small correlation (ɳ² = .006, p = .014). The parameter prioritization was correlating with small effect (ɳ² = .017, p = .001) as did employment level (ɳ² = .028, p < .001). The highest correlation was identified by the parameter sport with a moderate effect (ɳ² = .075, p = .047). The analyses show that the disparities in sports promotion cannot be determined by a particular parameter but presumably explained by a combination of several parameters. We argue that the possibility of combining parameters for data visualization should be enabled when the analysis is provided to Swiss Olympic for further strategic decision-making. However, the inclusion of multiple parameters massively multiplies the number of graphs and is therefore not suitable for practical use. Therefore, we suggest to apply interactive dashboards for data visualization using Business Intelligence Software. Practical & Theoretical Contribution: This contribution provides the first attempt to use Business Intelligence Software for strategic decision-making in national level sports regarding the prioritization of national resources for sports and athletes. This allows to set specific parameters with a significant effect as filters. By using filters, parameters can be combined and compared against each other and set individually for each strategic decision.

Keywords: data visualization, business intelligence, Swiss elite sports system, strategic decision-making

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Authors: Waheed O. Majekodunmi

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Climate change is a real global phenomenon and an unquestionable threat to our quest for a healthy and livable planet. It is now regarded as potentially the most monumental environmental challenge people and the planet will be confronted with over the next centuries. Expectedly, climate change mitigation was one of the central themes of COP 28. Despite contributing the least to climate change, Africa is and remains the hardest hit by the negative consequences of climate change including poor growth performance. Currently, it is being hypothesized that the high level of vulnerability and exposure to climate-related disasters, low adaptive capacity against global warming and high mitigation costs of climate change across the continent could be linked to the recent abysmal economic performance of African countries, especially in oil-producing countries where greenhouse gas emissions, is potentially more prevalent. This paper examines the impact of climate change on the economic performance of selected oil-producing countries in Africa using evidence from Nigeria, Algeria and Angola. The objective of the study is to determine whether or not climate change influences the economic performance of oil-producing countries in Africa by examining the nexus between economic growth and climate-related variables. The study seeks to investigate the effect of climate change on the pace of economic growth in African oil-producing countries. To achieve the research objectives, this study utilizes a quantitative approach by using historical and current secondary data sets to determine the relationship between climate-related variables and economic growth variables in the selected countries. The study employed numbers, percentages, tables and trend graphs to explain the trends or common patterns between climate change, economic growth and determinants of economic growth: governance effectiveness, infrastructure, macroeconomic stability and regulatory efficiency. Results from the empirical analysis of data show that the trends of economic growth and climate-related variables in the selected oil-producing countries are in the opposite directions as the increasing share of renewable energy sources in total energy consumption and the reduction in greenhouse gas emissions per capita in the oil-producing countries did not translate to higher economic growth. Further findings show that annual surface temperatures in the selected countries do not share similar trends with the food imports ratio and GDP per capita annual growth rate suggesting that climate change does not impact significantly agricultural productivity and economic growth in oil-producing countries in Africa. Annual surface temperature was also found to not share a similar pattern with governance effectiveness, macroeconomic stability and regulatory efficiency reinforcing the claim that some economic growth variables are independent of climate change. The policy implication of this research is that oil-producing African countries need to focus more on improving the macroeconomic environment and streamlining governance and institutional processes to boost their economic performance before considering the adoption of climate change adaptation and mitigation strategies.

Keywords: climate change, climate vulnerability, economic growth, greenhouse gas emissions per capita, oil-producing countries, share of renewable energy in total energy consumption

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Authors: Julia Terlet, Thomas H. Beach, Yacine Rezgui

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Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.

Keywords: behavioural change, ICT technologies, water consumption, water conservation

Procedia PDF Downloads 335

Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

Procedia PDF Downloads 108

Authors: Alena Semeradtova, Marcel Stofik, Lucie Mareckova, Petr Maly, Ondrej Stanek, Jan Maly

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Recently, novel strategies based on so-called molecular evolution were shown to be effective for the production of various peptide ligand libraries with high affinities to molecular targets of interest comparable or even better than monoclonal antibodies. The major advantage of these peptide scaffolds is mainly their prevailing low molecular weight and simple structure. This study describes a new high-affinity binding molecules based immunesensor using a simple optical system for human serum albumin (HSA) detection as a model molecule. We present a comparison of two variants of recombinant binders based on albumin binding domain of the protein G (ABD) performed on micropatterned glass chip. Binding domains may be tailored to any specific target of interest by molecular evolution. Micropatterened glass chips were prepared using UV-photolithography on chromium sputtered glasses. Glass surface was modified by (3-aminopropyl)trietoxysilane and biotin-PEG-acid using EDC/NHS chemistry. Two variants of high-affinity binding molecules were used to detect target molecule. Firstly, a variant is based on ABD domain fused with TolA chain. This molecule is in vivo biotinylated and each molecule contains one molecule of biotin and one ABD domain. Secondly, the variant is ABD domain based on streptavidin molecule and contains four gaps for biotin and four ABD domains. These high-affinity molecules were immobilized to the chip surface via biotin-streptavidin chemistry. To eliminate nonspecific binding 1% bovine serum albumin (BSA) or 6% fetal bovine serum (FBS) were used in every step. For both variants range of measured concentrations of fluorescently labelled HSA was 0 – 30 µg/ml. As a control, we performed a simultaneous assay without high-affinity binding molecules. Fluorescent signal was measured using inverse fluorescent microscope Olympus IX 70 with COOL LED pE 4000 as a light source, related filters, and camera Retiga 2000R as a detector. The fluorescent signal from non-modified areas was substracted from the signal of the fluorescent areas. Results were presented in graphs showing the dependence of measured grayscale value on the log-scale of HSA concentration. For the TolA variant the limit of detection (LOD) of the optical immunosensor proposed in this study is calculated to be 0,20 µg/ml for HSA detection in 1% BSA and 0,24 µg/ml in 6% FBS. In the case of streptavidin-based molecule, it was 0,04 µg/ml and 0,07 µg/ml respectively. The dynamical range of the immunosensor was possible to estimate just in the case of TolA variant and it was calculated to be 0,49 – 3,75 µg/ml and 0,73-1,88 µg/ml respectively. In the case of the streptavidin-based the variant we didn´t reach the surface saturation even with the 480 ug/ml concentration and the upper value of dynamical range was not estimated. Lower value was calculated to be 0,14 µg/ml and 0,17 µg/ml respectively. Based on the obtained results, it´s clear that both variants are useful for creating the bio-recognizing layer on immunosensors. For this particular system, it is obvious that the variant based on streptavidin molecule is more useful for biosensing on glass planar surfaces. Immunosensors based on this variant would exhibit better limit of detection and wide dynamical range.

Keywords: high affinity binding molecules, human serum albumin, optical immunosensor, protein G, UV-photolitography

Procedia PDF Downloads 368

Authors: Shrestha Sharma, Jasjeet K. Sahni, Javed Ali, Sanjula Baboota

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Introduction: Rutin is a naturally occurring strong antioxidant molecule belonging to bioflavonoid category. Due to its free radical scavenging properties, it has been found to be beneficial in the treatment of various diseases including inflammation, cancer, diabetes, allergy, cardiovascular disorders and various types of microbial infections. Despite its beneficial effects, it suffers from the problem of low aqueous solubility which is responsible for low oral bioavailability. The aim of our study was to optimize and characterize self-nanoemulsifying drug delivery system (SNEDDS) of rutin using Box-Behnken design (BBD) combined with a desirability function. Further various antioxidant, pharmacokinetic and pharmacodynamic studies were performed for the optimized rutin SNEDDS formulation. Methodologies: Selection of oil, surfactant and co-surfactant was done on the basis of solubility/miscibility studies. Sefsol+ Vitamin E, Solutol HS 15 and Transcutol P were selected as oil phase, surfactant and co-surfactant respectively. Optimization of SNEDDS formulations was done by a three-factor, three-level (33)BBD. The independent factors were Sefsol+ Vitamin E, Solutol HS15, and Transcutol P. The dependent variables were globule size, self emulsification time (SEF), % transmittance and cumulative percentage drug released. Various response surface graphs and contour plots were constructed to understand the effect of different factor, their levels and combinations on the responses. The optimized Rutin SNEDDS formulation was characterized for various parameters such as globule size, zeta potential, viscosity, refractive index , % Transmittance and in vitro drug release. Ex vivo permeation studies and pharmacokinetic studies were performed for optimized formulation. Antioxidant activity was determined by DPPH and reducing power assays. Anti-inflammatory activity was determined by using carrageenan induced rat paw oedema method. Permeation of rutin across small intestine was assessed using confocal laser scanning microscopy (CLSM). Major findings:The optimized SNEDDS formulation consisting of Sefsol+ Vitamin E - Solutol HS15 -Transcutol HP at proportions of 25:35:17.5 (w/w) was prepared and a comparison of the predicted values and experimental values were found to be in close agreement. The globule size and PDI of optimized SNEDDS formulation was found to be 16.08 ± 0.02 nm and 0.124±0.01 respectively. Significant (p˂0.05) increase in percentage drug release was achieved in the case of optimized SNEDDS formulation (98.8 %) as compared to rutin suspension. Furthermore, pharmacokinetic study showed a 2.3-fold increase in relative oral bioavailability compared with that of the suspension. Antioxidant assay results indicated better efficacy of the developed formulation than the pure drug and it was found to be comparable with ascorbic acid. The results of anti-inflammatory studies showed 72.93 % inhibition for the SNEDDS formulation which was significantly higher than the drug suspension 46.56%. The results of CLSM indicated that the absorption of SNEDDS formulation was considerably higher than that from rutin suspension. Conclusion: Rutin SNEDDS have been successfully prepared and they can serve as an effective tool in enhancing oral bioavailability and efficacy of Rutin.

Keywords: rutin, oral bioavilability, pharamacokinetics, pharmacodynamics

Procedia PDF Downloads 500

Authors: Mona Isazad Mashinchi, Davood Roshan Sangachin, Francis J. Sullivan, Dietrich Rebholz-Schuhmann

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Background: Decision-making processes are nowadays driven by data, data analytics and Business Intelligence (BI). BI as a software platform can provide a wide variety of capabilities such as organization memory, information integration, insight creation and presentation capabilities. Visualizing data through dashboards is one of the BI solutions (for a variety of areas) which helps managers in the decision making processes to expose the most informative information at a glance. In the healthcare domain to date, dashboard presentations are more frequently used to track performance related metrics and less frequently used to monitor those quality parameters which relate directly to patient outcomes. Providing effective and timely care for patients and improving the health outcome are highly dependent on presenting and visualizing data and information. Objective: In this research, the focus is on the presentation capabilities of BI to design a dashboard for prostate cancer (PC) data that allows better decision making for the patients, the hospital and the healthcare system related to a cancer dataset. The aim of this research is to customize a retrospective PC dataset in a dashboard interface to give a better understanding of data in the categories (risk factors, treatment approaches, disease control and side effects) which matter most to patients as well as other stakeholders. By presenting the outcome in the dashboard we address one of the major targets of a value-based health care (VBHC) delivery model which is measuring the value and presenting the outcome to different actors in HC industry (such as patients and doctors) for a better decision making. Method: For visualizing the stored data to users, three interactive dashboards based on the PC dataset have been developed (using the Tableau Software) to provide better views to the risk factors, treatment approaches, and side effects. Results: Many benefits derived from interactive graphs and tables in dashboards which helped to easily visualize and see the patients at risk, better understanding the relationship between patient's status after treatment and their initial status before treatment, or to choose better decision about treatments with fewer side effects regarding patient status and etc. Conclusions: Building a well-designed and informative dashboard is related to three important factors including; the users, goals and the data types. Dashboard's hierarchies, drilling, and graphical features can guide doctors to better navigate through information. The features of the interactive PC dashboard not only let doctors ask specific questions and filter the results based on the key performance indicators (KPI) such as: Gleason Grade, Patient's Age and Status, but may also help patients to better understand different treatment outcomes, such as side effects during the time, and have an active role in their treatment decisions. Currently, we are extending the results to the real-time interactive dashboard that users (either patients and doctors) can easily explore the data by choosing preferred attribute and data to make better near real-time decisions.

Keywords: business intelligence, dashboard, decision making, healthcare, prostate cancer, value-based healthcare

Procedia PDF Downloads 140

Authors: Michal Geca, Grzegorz Baranski, Ksenia Siadkowska

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The work is a part of the project which aims at developing innovative power and control systems for the high power aircraft piston engine ASz62IR. Developed electronically controlled ignition system will reduce emissions of toxic compounds as a result of lowered fuel consumption, optimized combustion and engine capability of efficient combustion of ecological fuels. The tested unit is an air-cooled four-stroke gasoline engine of 9 cylinders in a radial setup, mechanically charged by a radial compressor powered by the engine crankshaft. The total engine cubic capac-ity is 29.87 dm3, and the compression ratio is 6.4:1. The maximum take-off power is 1000 HP at 2200 rpm. The maximum fuel consumption is 280 kg/h. Engine powers aircrafts: An-2, M-18 „Dromader”, DHC-3 „OTTER”, DC-3 „Dakota”, GAF-125 „HAWK” i Y5. The main problems of the engine includes the imbalanced work of cylinders. The non-uniformity value in each cylinder results in non-uniformity of their work. In radial engine cylinders arrangement causes that the mixture movement that takes place in accordance (lower cylinder) or the opposite (upper cylinders) to the direction of gravity. Preliminary tests confirmed the presence of uneven workflow of individual cylinders. The phenomenon is most intense at low speed. The non-uniformity is visible on the waveform of cylinder pressure. Therefore two studies were conducted to determine the impact of this phenomenon on the engine performance: simulation and real tests. Simplified simulation was conducted on the element of the intake system coated with fuel film. The study shows that there is an effect of gravity on the movement of the fuel film inside the radial engine intake channels. Both in the lower and the upper inlet channels the film flows downwards. It follows from the fact that gravity assists the movement of the film in the lower cylinder channels and prevents the movement in the upper cylinder channels. Real tests on aircraft engine ASz62IR was conducted in transients condition (rapid change of the excess air in each cylinder were performed. Calculations were conducted for mass of fuel reaching the cylinders theoretically and really and on this basis, the factors of fuel evaporation “x” were determined. Therefore a simplified model of the fuel supply to cylinder was adopted. Model includes time constant of the fuel film τ, the number of engine transport cycles of non-evaporating fuel along the intake pipe γ and time between next cycles Δt. The calculation results of identification of the model parameters are presented in the form of radar graphs. The figures shows the averages declines and increases of the injection time and the average values for both types of stroke. These studies shown, that the change of the position of the cylinder will cause changes in the formation of fuel-air mixture and thus changes in the combustion process. Based on the results of the work of simulation and experiments was possible to develop individual algorithms for ignition control. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: radial engine, ignition system, non-uniformity, combustion process

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Authors: Bahareh Ansari

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Background: The Open Government Data (OGD) movement in the last decade has encouraged many government organizations around the world to make their data publicly available to advance democratic processes. But current open data platforms have not yet reached to their full potential in supporting all interested parties. To make the data useful and understandable for everyone, scholars suggested that opening the data should be supplemented by visualization. However, different visualizations of the same information can dramatically change an individual’s cognitive and emotional experience in working with the data. This study reviews the data visualization literature to create a list of the methods empirically tested to enhance users’ performance and experience in working with a visualization tool. This list can be used in evaluating the OGD visualization practices and informing the future open data initiatives. Methods: Previous reviews of visualization literature categorized the visualization outcomes into four categories including recall/memorability, insight/comprehension, engagement, and enjoyment. To identify the papers, a search for these outcomes was conducted in the abstract of the publications of top-tier visualization venues including IEEE Transactions for Visualization and Computer Graphics, Computer Graphics, and proceedings of the CHI Conference on Human Factors in Computing Systems. The search results are complemented with a search in the references of the identified articles, and a search for 'open data visualization,' and 'visualization evaluation' keywords in the IEEE explore and ACM digital libraries. Articles are included if they provide empirical evidence through conducting controlled user experiments, or provide a review of these empirical studies. The qualitative synthesis of the studies focuses on identification and classifying the methods, and the conditions under which they are examined to positively affect the visualization outcomes. Findings: The keyword search yields 760 studies, of which 30 are included after the title/abstract review. The classification of the included articles shows five distinct methods: interactive design, aesthetic (artistic) style, storytelling, decorative elements that do not provide extra information including text, image, and embellishment on the graphs), and animation. Studies on decorative elements show consistency on the positive effects of these elements on user engagement and recall but are less consistent in their examination of the user performance. This inconsistency could be attributable to the particular data type or specific design method used in each study. The interactive design studies are consistent in their findings of the positive effect on the outcomes. Storytelling studies show some inconsistencies regarding the design effect on user engagement, enjoyment, recall, and performance, which could be indicative of the specific conditions required for the use of this method. Last two methods, aesthetics and animation, have been less frequent in the included articles, and provide consistent positive results on some of the outcomes. Implications for e-government: Review of the visualization best-practice methods show that each of these methods is beneficial under specific conditions. By using these methods in a potentially beneficial condition, OGD practices can promote a wide range of individuals to involve and work with the government data and ultimately engage in government policy-making procedures.

Keywords: best practices, data visualization, literature review, open government data

Procedia PDF Downloads 105

Authors: Jorge Cortés, Alejandra Martínez, Carlos Pérez, Anaid Simón

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The presence of government, news media, and general citizenry in social media allows considering interactions between them as a form of political communication (i.e. the public exchange of contradictory discourses about politics). Twitter’s asymmetrical following model (users can follow, mention or reply to other users that do not follow them) could foster alternative democratic practices and have an impact on Mexican political culture, which has been marked by a lack of direct communication channels between these actors. The research aim is to assess Twitter’s role in political communication practices through the analysis of interaction dynamics between government, news media, and citizens by extracting and visualizing data from Twitter’s API to observe general behavior patterns. The hypothesis is that regardless the fact that Twitter’s features enable direct and horizontal interactions between actors, users repeat traditional dynamics of interaction, without taking full advantage of the possibilities of this medium. Through an interdisciplinary team including Communication Strategies, Information Design, and Interaction Systems, the activity on Twitter generated by the controversy over the presence of Uber in Mexico City was analysed; an issue of public interest, involving aspects such as public opinion, economic interests and a legal dimension. This research includes techniques from social network analysis (SNA), a methodological approach focused on the comprehension of the relationships between actors through the visual representation and measurement of network characteristics. The analysis of the Uber event comprised data extraction, data categorization, corpus construction, corpus visualization and analysis. On the recovery stage TAGS, a Google Sheet template, was used to extract tweets that included the hashtags #UberSeQueda and #UberSeVa, posts containing the string Uber and tweets directed to @uber_mx. Using scripts written in Python, the data was filtered, discarding tweets with no interaction (replies, retweets or mentions) and locations outside of México. Considerations regarding bots and the omission of anecdotal posts were also taken into account. The utility of graphs to observe interactions of political communication in general was confirmed by the analysis of visualizations generated with programs such as Gephi and NodeXL. However, some aspects require improvements to obtain more useful visual representations for this type of research. For example, link¬crossings complicates following the direction of an interaction forcing users to manipulate the graph to see it clearly. It was concluded that some practices prevalent in political communication in Mexico are replicated in Twitter. Media actors tend to group together instead of interact with others. The political system tends to tweet as an advertising strategy rather than to generate dialogue. However, some actors were identified as bridges establishing communication between the three spheres, generating a more democratic exercise and taking advantage of Twitter’s possibilities. Although interactions in Twitter could become an alternative to political communication, this potential depends on the intentions of the participants and to what extent they are aiming for collaborative and direct communications. Further research is needed to get a deeper understanding on the political behavior of Twitter users and the possibilities of SNA for its analysis.

Keywords: interaction, political communication, social network analysis, Twitter

Procedia PDF Downloads 221

Authors: Mukul Sharma, Madhusmita Das, Sundeep Chaitanya Vedithi

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Leprosy is a chronic human disease caused by Mycobacterium leprae, that cannot be cultured in vitro. Though treatable with multidrug therapy (MDT), recently, bacteria reported resistance to multiple antibiotics. Targeting DNA replication and repair pathways can serve as the foundation of developing new anti-leprosy drugs. Due to the absence of an axenic culture medium for the propagation of M. leprae, studying cellular processes, especially those belonging to DNA repair pathways, is challenging. Genomic understanding of M. Leprae harbors several protein-coding genes with no previously assigned function known as 'hypothetical proteins'. Here, we report identification and expression of known and hypothetical DNA repair genes from a human skin biopsy and mouse footpads that are involved in base excision repair, direct reversal repair, and SOS response. Initially, a bioinformatics approach was employed based on sequence similarity, identification of known protein domains to screen the hypothetical proteins in the genome of M. leprae, that are potentially related to DNA repair mechanisms. Before testing on clinical samples, pure stocks of bacterial reference DNA of M. leprae (NHDP63 strain) was used to construct standard graphs to validate and identify lower detection limit in the qPCR experiments. Primers were designed to amplify the respective transcripts, and PCR products of the predicted size were obtained. Later, excisional skin biopsies of newly diagnosed untreated, treated, and drug resistance leprosy cases from SIHR & LC hospital, Vellore, India were taken for the extraction of RNA. To determine the presence of the predicted transcripts, cDNA was generated from M. leprae mRNA isolated from clinically confirmed leprosy skin biopsy specimen across all the study groups. Melting curve analysis was performed to determine the integrity of the amplification and to rule out primer‑dimer formation. The Ct values obtained from qPCR were fitted to standard curve to determine transcript copy number. Same procedure was applied for M. leprae extracted after processing a footpad of nude mice of drug sensitive and drug resistant strains. 16S rRNA was used as positive control. Of all the 16 genes involved in BER, DR, and SOS, differential expression pattern of the genes was observed in terms of Ct values when compared to human samples; this was because of the different host and its immune response. However, no drastic variation in gene expression levels was observed in human samples except the nth gene. The higher expression of nth gene could be because of the mutations that may be associated with sequence diversity and drug resistance which suggests an important role in the repair mechanism and remains to be explored. In both human and mouse samples, SOS system – lexA and RecA, and BER genes AlkB and Ogt were expressing efficiently to deal with possible DNA damage. Together, the results of the present study suggest that DNA repair genes are constitutively expressed and may provide a reference for molecular diagnosis, therapeutic target selection, determination of treatment and prognostic judgment in M. leprae pathogenesis.

Keywords: DNA repair, human biopsy, hypothetical proteins, mouse footpads, Mycobacterium leprae, qPCR

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Authors: Catherine Vasnetsov, Victor Vasnetsov

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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.

Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Alexandre Faure, Yoko Mizokami, éRic Dinet

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These recent years, the potential of light in assisting visually impaired people in their indoor mobility has been demonstrated by different studies. Implementing smart lighting systems for selective visual enhancement, especially designed for low-vision people, is an approach that breaks with the existing visual aids. The appearance of the surface of an object is significantly influenced by the lighting conditions and the constituent materials of the objects. Appearance of objects may appear to be different from expectation. Therefore, lighting conditions lead to an important part of accurate material recognition. The main objective of this work was to investigate the effect of the spatial distribution of light on object identification in the context of low vision. The purpose was to determine whether and what specific lighting approaches should be preferred for visually impaired people. A psychophysical experiment was designed to study the ability of individuals to identify the smallest cube of a pair under different lighting diffusion conditions. Participants were divided into two distinct groups: a reference group of observers with normal or corrected-to-normal visual acuity and a test group, in which observers were required to wear visual impairment simulation glasses. All participants were presented with pairs of cubes in a "miniature room" and were instructed to estimate the relative size of the two cubes. The miniature room replicates real-life settings, adorned with decorations and separated from external light sources by black curtains. The correlated color temperature was set to 6000 K, and the horizontal illuminance at the object level at approximately 240 lux. The objects presented for comparison consisted of 11 white cubes and 11 black cubes of different sizes manufactured with a 3D printer. Participants were seated 60 cm away from the objects. Two different levels of light diffuseness were implemented. After receiving instructions, participants were asked to judge whether the two presented cubes were the same size or if one was smaller. They provided one of five possible answers: "Left one is smaller," "Left one is smaller but unsure," "Same size," "Right one is smaller," or "Right one is smaller but unsure.". The method of constant stimuli was used, presenting stimulus pairs in a random order to prevent learning and expectation biases. Each pair consisted of a comparison stimulus and a reference cube. A psychometric function was constructed to link stimulus value with the frequency of correct detection, aiming to determine the 50% correct detection threshold. Collected data were analyzed through graphs illustrating participants' responses to stimuli, with accuracy increasing as the size difference between cubes grew. Statistical analyses, including 2-way ANOVA tests, showed that light diffuseness had no significant impact on the difference threshold, whereas object color had a significant influence in low vision scenarios. The first results and trends derived from this pilot experiment clearly and strongly suggest that future investigations could explore extreme diffusion conditions to comprehensively assess the impact of diffusion on object identification. For example, the first findings related to light diffuseness may be attributed to the range of manipulation, emphasizing the need to explore how other lighting-related factors interact with diffuseness.

Keywords: Lighting, Low Vision, Visual Aid, Object Identification, Psychophysical Experiment

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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