Search results for: brain tumor classification

Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

Procedia PDF Downloads 358

Authors: Kalu Uka Orji, Nasiman Sapari, Khamaruzaman W. Yusof

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Exposure of galena (PbS), tealite (PbSnS2), and other associated minerals during mining activities release lead (Pb) and other heavy metals into the mining water through oxidation and dissolution. Heavy metal pollution has become an environmental challenge. Lead, for instance, can cause toxic effects to human health, including brain damage. Ex-mining pond water was reported to contain lead as high as 69.46 mg/L. Conventional treatment does not easily remove lead from water. A promising and emerging treatment technology for lead removal is the application of the electrocoagulation (EC) process. However, some of the problems associated with EC are systematic reactor design, selection of maximum EC operating parameters, scale-up, among others. This study investigated an EC process for the removal of lead from synthetic ex-mining pond water using a batch reactor and Fe electrodes. The effects of various operating parameters on lead removal efficiency were examined. The results obtained indicated that the maximum removal efficiency of 98.6% was achieved at an initial PH of 9, the current density of 15mA/cm2, electrode spacing of 0.3cm, treatment time of 60 minutes, Liquid Motion of Magnetic Stirring (LM-MS), and electrode arrangement = BP-S. The above experimental data were further modeled and optimized using a 2-Level 4-Factor Full Factorial design, a Response Surface Methodology (RSM). The four factors optimized were the current density, electrode spacing, electrode arrangements, and Liquid Motion Driving Mode (LM). Based on the regression model and the analysis of variance (ANOVA) at 0.01%, the results showed that an increase in current density and LM-MS increased the removal efficiency while the reverse was the case for electrode spacing. The model predicted the optimal lead removal efficiency of 99.962% with an electrode spacing of 0.38 cm alongside others. Applying the predicted parameters, the lead removal efficiency of 100% was actualized. The electrode and energy consumptions were 0.192kg/m3 and 2.56 kWh/m3 respectively. Meanwhile, the adsorption kinetic studies indicated that the overall lead adsorption system belongs to the pseudo-second-order kinetic model. The adsorption dynamics were also random, spontaneous, and endothermic. The higher temperature of the process enhances adsorption capacity. Furthermore, the adsorption isotherm fitted the Freundlish model more than the Langmuir model; describing the adsorption on a heterogeneous surface and showed good adsorption efficiency by the Fe electrodes. Adsorption of Pb2+ onto the Fe electrodes was a complex reaction, involving more than one mechanism. The overall results proved that EC is an efficient technique for lead removal from synthetic mining pond water. The findings of this study would have application in the scale-up of EC reactor and in the design of water treatment plants for feed-water sources that contain lead using the electrocoagulation method.

Keywords: ex-mining water, electrocoagulation, lead, adsorption kinetics

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Antonina A. Shumakova, Sergey A. Khotimchenko

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The relevance of research is associated, on the one hand, with an ever-increasing volume of production and the expansion of the scope of application of engineered nanomaterials (ENMs), and on the other hand, with the lack of sufficient scientific information on the nature of the interactions of nanoparticles (NPs) with components of biogenic and abiogenic origin. In particular, studying the effect of ENMs (TiO2 NPs, SiO2 NPs, Al2O3 NPs, fullerenol) on the toxicometric characteristics of common contaminants such as lead and cadmium is an important hygienic task, given the high probability of their joint presence in food products. Data were obtained characterizing a multidirectional change in the toxicity of model toxicants when they are co-administered with various types of ENMs. One explanation for this fact is the difference in the adsorption capacity of ENMs, which was further studied in in vitro studies. For this, a method was proposed based on in vitro modeling of conditions simulating the environment of the small intestine. It should be noted that the obtained data are in good agreement with the results of in vivo experiments: - with the combined administration of lead and TiO2 NPs, there were no significant changes in the accumulation of lead in rat liver; in other organs (kidneys, spleen, testes and brain), the lead content was lower than in animals of the control group; - studying the combined effect of lead and Al2O3 NPs, a multiple and significant increase in the accumulation of lead in rat liver was observed with an increase in the dose of Al2O3 NPs. For other organs, the introduction of various doses of Al2O3 NPs did not significantly affect the bioaccumulation of lead; - with the combined administration of lead and SiO2 NPs in different doses, there was no increase in lead accumulation in all studied organs. Based on the data obtained, it can be assumed that at least three scenarios of the combined effects of ENMs and chemical contaminants on the body: - ENMs quite firmly bind contaminants in the gastrointestinal tract and such a complex becomes inaccessible (or inaccessible) for absorption; in this case, it can be expected that the toxicity of both ENMs and contaminants will decrease; - the complex formed in the gastrointestinal tract has partial solubility and can penetrate biological membranes and / or physiological barriers of the body; in this case, ENMs can play the role of a kind of conductor for contaminants and, thus, their penetration into the internal environment of the body increases, thereby increasing the toxicity of contaminants; - ENMs and contaminants do not interact with each other in any way, therefore the toxicity of each of them is determined only by its quantity and does not depend on the quantity of another component. Authors hypothesized that the degree of adsorption of various elements on the surface of ENMs may be a unique characteristic of their action, allowing a more accurate understanding of the processes occurring in a living organism.

Keywords: absorption, cadmium, engineered nanomaterials, lead

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Authors: Yude Wu

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Mongolia, grappling with significant socio-economic challenges, faces pressing issues of inequality and poverty, as evidenced by a high Gini coefficient and the highest poverty rate among the top 20 largest Asian countries. Despite government efforts, Mongolia's poverty rate experienced only a slight reduction from 29.6 percent in 2016 to 27.8 percent in 2020. PEER countries, such as South Africa, Botswana, Kazakhstan, and Peru, share characteristics with Mongolia, including reliance on the mining industry and classification as lower middle-income countries. Successful transitions of these countries to upper middle-income status between 1994 and the 2010s provide valuable insights. Drawing on secondary analyses of existing research and PEER country profiles, the study evaluates past policies, identifies gaps in current approaches, and proposes recommendations to combat poverty sustainably. The hypothesis includes a reliance on the mining industry and a transition from lower to upper middle-income status. Policies from these countries, such as the GEAR policy in South Africa and economic diversification in Botswana, offer insights into Mongolia's development. This essay aims to illuminate the multidimensional nature of underdevelopment in Mongolia through a secondary analysis of existing research and PEER country profiles, evaluating past policies, identifying gaps in current approaches, and providing recommendations for sustainable progress. Drawing inspiration from PEER countries, Mongolia can implement policies such as economic diversification to reduce vulnerability and create stable job opportunities. Emphasis on infrastructure, human capital, and strategic partnerships for Foreign Direct Investment (FDI) aligns with successful strategies implemented by PEER countries, providing a roadmap for Mongolia's development objectives.

Keywords: inequality, PEER countries, comparative analysis, nomadic animal husbandry, sustainable growth

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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Authors: Luisa Villani

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The proposal aims to express concerns about the connection between mind, body, society, and environment in the Flyers’ dance, a very well-known rotatory dance in Mexico, to create meanings and to make the apprehension of the world possible. The interaction among the brain, mind, body, and environment, and the intersubjective relation among them, means the world creates and recreates a social interaction. The purpose of this methodology, based on the embodied cognition theory, which was named “A Performance-Embodied Theory” is to find the principles and patterns that organize the culture and the rules of the apprehension of the environment by Totonac people while the dance is being performed. The analysis started by questioning how anthropologists can interpret how Totonacs transform their unconscious knowledge into conscious knowledge and how the scheme formation of imagination and their collective imagery is understood in the context of public-facing rituals, such as Flyers’ dance. The problem is that most of the time, researchers interpret elements in a separate way and not as a complex ritual dancing whole, which is the original contribution of this study. This theory, which accepts the fact that people are body-mind agents, wants to interpret the dance as a whole, where the different elements are joined to an integral interpretation. To understand incorporation, data was recollected in prolonged periods of fieldwork, with participant observation and linguistic and extralinguistic data analysis. Laban’s notation for the description and analysis of gestures and movements in the space was first used, but it was later transformed and gone beyond this method, which is still a linear and compositional one. Performance in a ritual is the actualization of a potential complex of meanings or cognitive domains among many others in a culture: one potential dimension becomes probable and then real because of the activation of specific meanings in a context. It can only be thought what language permits thinking, and the lexicon that is used depends on the individual culture. Only some parts of this knowledge can be activated at once, and these parts of knowledge are connected. Only in this way, the world can be understood. It can be recognized that as languages geometrize the physical world thanks to the body, also ritual does. In conclusion, the ritual behaves as an embodied grammar or a text in movement, which, depending on the ritual phases and the words and sentences pronounced in the ritual, activates bits of encyclopedic knowledge that people have about the world. Gestures are not given by the performer but emerge from the intentional perception in which gestures are “understood” by the audio-spectator in an inter-corporeal way. The impact of this study regards the possibility not only to disseminate knowledge effectively but also to generate a balance between different parts of the world where knowledge is shared, rather than being received by academic institutions alone. This knowledge can be exchanged, so indigenous communities and academies could be together as part of the activation and the sharing of this knowledge with the world.

Keywords: dance, flyers, performance, embodied, cognition

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Authors: Hanan M. Hassan, Laila Abouzeid, Lamya H. Al-Wahaibi, George S. G. Shehatou, Ali A. El-Emam

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Cancer is a major public health problem and the second leading cause of death worldwide. In 2020, cancer diagnosis and treatment have been negatively affected by the coronavirus 2019 (COVID-19) pandemic. During the quarantine, because of the limited access to healthcare and avoiding exposure to COVID-19 as a contagious disease; patients of cancer suffered deferments in follow-up and treatment regimens leading to substantial worsening of disease, death, and increased healthcare costs. Thus, this study is designed to investigate the molecular mechanisms by which adamantne derivatives attenuate hepatocllular carcinoma experimentally and theoretically. There is a close association between increased resistance to anticancer drugs and defective apoptosis that considered a causative factor for oncogenesis. Cancer cells use different molecular pathways to inhibit apoptosis, BAX and Bcl-2 proteins have essential roles in the progression or inhibition of intrinsic apoptotic pathways triggered by mitochondrial dysfunction. Therefore, their balance ratio can promote the cellular apoptotic fate. In this study, the in vitro cytotoxic effects of seven synthetic adamantyl isothiorea derivatives were evaluated against five human tumor cell lines by MTT assay. Compounds 5 and 6 showed the best results, mostly against hepatocellular carcinoma (HCC). Hence, in vivo studies were performed in male Sprague-Dawley (SD) rats in which experimental hepatocellular carcinoma was induced with thioacetamide (TAA) (200 mg/kg, i.p., twice weekly) for 16 weeks. The most promising compounds, 5 and 6, were administered to treat liver cancer rats at a dose of 10 mg/kg/day for an additional two weeks, and the effects were compared with doxorubicin (DR), the anticancer drug. Hepatocellular carcinoma was evidenced by a dramatic increase in liver indices, oxidative stress markers, and immunohistochemical studies that were accompanied by a plethora of inflammatory mediators and alterations in the apoptotic cascade. Our results showed that treatment with adamantane derivatives 5 and 6 significantly suppressed fibrosis, inflammation, and other histopathological insults resulting in the diminished formation of hepatocyte tumorigenesis. Moreover, administration of the tested compounds resulted in amelioration of EGFR protein expression, upregulation of BAX, and lessening down of Bcl-2 levels that prove their role as apoptosis inducers. Also, the docking simulations performed for adamantane showed good fit and binding to the EGFR protein through hydrogen bond formation with conservative amino acids, which gives a shred of strong evidence for its hepatoprotective effect. In most analyses, the effects of compound 6 were more comparable to DR than compound 5. Our findings suggest that adamantane derivatives 5 and 6 are shown to have cytotoxic activity against HCC in vitro and in vivo, by more than one mechanism, possibly by inhibiting the TLR4-MyD88-NF-κB pathway and targeting EGFR signaling.

Keywords: adamantane, EGFR, HCC, apoptosis

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: M. Ghasemi, S.Fazelifar

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Abstract Aim: Over-weight is not desirable and has implications for health and in the case of athletes affects performance. Exercise is a strategy used to counteract overweight owing to create a negative energy balance by increasing energy expenditure and influencing appetite regulating hormones. Interestingly, recent studies have revealed inhibitory effects of exercise on the hunger associated with these hormones in healthy subjects Neuropeptide Y(NPY) is a 36 amino acid protein that is a powerful stimulant appetite. NPY is an important central orexigenic hormone predominantly produced by the hypothalamus, and recently found to be secreted in adipose tissue. This neurotransmitter is secreted in the brain and autonomic nervous system. On the other hand, research has shown that thyme in addition to various properties, also affects the appetite. The purpose of this study was to determine Effects of eight weeks endurance training and thyme consumption on neuropeptide Y in untrained men. Methodology: 36 Healthy untrained men (mean body weight 78.25±3.2 kg, height 176±6.8 cm, age 34.32±4.54 years and BMI 29.1±4.3 kg/m2) voluntarily participated in this study . Subjects were randomly divided into four groups: 1. control, 2. Endurance training, 3. Thyme 4. Endurance training + Thyme. Amount of 10cc Blood sampling were obtained pre-test and post-test (after 8 weeks). The taken blood samples were centrifuged at 1500 × g for 15 min then plasma was stored at -20 °C until analysis. Endurance training consisted three session per week with 60% -75% of reserve heart rate for eight weeks. Exclusion criteria were history of gastrointestinal, endocrine, cardiovascular or psychological disease, and consuming any supplementation, alcohol and tobacco products. Descriptive statistics including means, standard deviations, and ranges were calculated for all measures. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p<0/05 accepted. Results: Results showed that aerobic training significantly reduced body weight, body mass index, percent body fat, but significant increase observed in maximal oxygen consumption level (p ≤ 0/05). The neuropeptide Y levels were significantly increased after exercise. Analysis of data determined that there was no significant difference between the four groups. Conclusion: Appetite control plays a critical role in the competition between energy consumption and energy expenditure. The results of this study showed that endurance training and thyme consumption can be cause improvement in physiological parameters such as increasing aerobic capacity, reduction of fat mass and improve body composition in untrained men.

Keywords: Endurance training, neuropeptide Y, thyme, untrained men

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Authors: Nwogiji Cletus Olando, Oselebe Happiness Ogba, Enoch Achigan-Dako

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Digitaria iburua, commonly known as black fonio, is a cereal crop native to Africa and extensively cultivated by smallholder farmers in Northern Benin, Togo, and Nigeria. This crop holds immense nutritional and socio-cultural value. Unfortunately, limited knowledge about its genetic diversity exists due to a lack of scientific attention. As a result, its potential for improvement in food and agriculture remains largely untapped. To address this gap, a study was conducted using 41 accessions of D. iburua stored in the genebank of the Laboratory of Genetics, Biotechnology, and Seed Science at Abomey-Calavi University, Benin. The study employed both morphological and simple sequence repeat (SSR) markers to evaluate the genetic variability of the accessions. Agro-morphological assessments were carried out during the 2020 cropping season, utilizing an alpha lattice design with three replications. The collected data encompassed qualitative and quantitative traits. Additionally, molecular variability was assessed using eleven SSR markers. The results revealed significant phenotypic variability among the evaluated accessions, leading to their classification into three main clusters. Furthermore, the eleven SSR markers identified a total of 50 alleles, averaging 4.55 alleles per locus. The primers exhibited an average polymorphic information content value of 0.43, with the DE-ARC019 primer displaying the highest value (0.59). These findings suggest a substantial degree of genetic heterogeneity within the evaluated accessions, and the SSR markers employed in the study proved highly effective in detecting and characterizing this genetic variability. In conclusion, this study highlights the presence of significant genetic diversity in black fonio and provides valuable insights for future efforts aimed at its genetic improvement and conservation.

Keywords: genetic diversity, digitaria iburua, genetic improvement, simple sequence repeat markers, Nigeria, conservation

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Authors: Nyamela M. ‘Masekhohola, Khanare P. Fumane

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The Lesotho downward trend in mathematics attainment at all levels is compounded by the absence of innovative approaches to teaching and learning in Early Childhood. However, studies have shown that play pedagogy can be used to mitigate the challenges of mathematics education. Despite the benefits of play pedagogy to rural learners, its full potential has not been realized in early childhood care and education classrooms to improve children’s performance in mathematics because the adoption of play pedagogy depends on a strength-based approach. The study explores the potential of play pedagogy to improve mathematics education in early childhood care and education in Lesotho. Strength-based approach is known for its advocacy of recognizing and utilizing children’s strengths, capacities and interests. However, this approach and its promisingattributes is not well-known in Lesotho. In particular, little is known about the attributes of play pedagogy that are essential to improve mathematic education in ECCE programs in Lesotho. To identify such attributes and strengthen mathematics education, this systematic review examines evidence published on the strengths of play pedagogy that supports the teaching and learning of mathematics education in ECCE. The purpose of this review is, therefore, to identify and define the strengths of play pedagogy that supports mathematics education. Moreover, the study intends to understand the rural teachers’ perceived intention of using play in ECCE math classrooms through a strength-based approach. Eight key strengths were found (cues for reflection, edutainment, mathematics language development, creativity and imagination, cognitive promotion, exploration, classification, and skills development). This study is the first to identify and define the strength-based attributes of play pedagogy to improve the teaching and learning of mathematics in ECCE centers in Lesotho. The findings reveal which opportunities teachers find important for improving the teaching of mathematics as early as in ECCE programs. We conclude by discussing the implications of the literature for stimulating dialogues towards formulating strength-based approaches to teaching mathematics, as well as reflecting on the broader contributions of play pedagogy as an asset to improve mathematics in Lesotho and beyond.

Keywords: early childhood education, mathematics education, lesotho, play pedagogy, strength-based approach.

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Authors: S. Kudlacik-Kramarczyk, M. Kedzierska, B. Tyliszczak

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Recently, the continuous development of medicine and related sciences has been observed. Particular emphasis is directed on the development of biomaterials, i.e., non-toxic, biocompatible and biodegradable materials that may improve the effectiveness of treatment as well as the comfort of patients. This is particularly important in the case of cancer treatment. Currently, there are many methods of cancer treatment based primarily on chemotherapy and the surgical removal of the tumor, but it is worth noting that these therapies also cause many side effects. Among women, the most common cancer is breast cancer. It may be completely cured, but the consequence of treatment is partial or complete breast mastectomy and radiation therapy, which results in severe skin burns. The skin of the patient after radiation therapy is very burned, and therefore requires intensive care and high frequency of dressing changes. The traditional dressing adheres to the burn wounds and does not absorb adequate amount of exudate from injuries and the patient is forced to change the dressing every 2 hours. Therefore, the main purpose was to develop an innovative combination of dressing material with drug carriers that may be used in anti-cancer therapy. The innovation of this solution is the combination of these two products into one system, i.e., a transdermal system with the possibility of a controlled release of the drug- cytostatic. Besides, the possibility of modifying the hydrogel matrix with aloe vera juice provides this material with new features favorable from the point of view of healing processes of burn wounds resulting from the radiation therapy. In this study, hydrogel materials containing protein spheres with the active substance have been obtained as a result of photopolymerization process. The reaction mixture consisting of the protein (albumin) spheres incorporated with cytostatic, chitosan, adequate crosslinking agent and photoinitiator has been subjected to the UV radiation for 2 minutes. Prepared materials have been subjected to the numerous studies including the analysis of cytotoxicity using murine fibroblasts L929. Analysis was conducted based on the mitochondrial activity test (MTT reduction assay) which involves the determining the number of cells characterized by proper metabolism. Hydrogel materials obtained using different amount of crosslinking agents have been subjected to the cytotoxicity analysis. According to the standards, tested material is defined as cytotoxic when the viability of cells after 24 h incubation with this material is lower than 70%. In the research, hydrogel polymer materials containing protein spheres incorporated with the active substance, i.e. a cytostatic, have been developed. Such a dressing may support the treatment of cancer due to the content of the anti-cancer drug - cytostatic, and may also provide a soothing effect on the healing of the burn wounds resulted from the radiation therapy due to the content of aloe vera juice in the hydrogel matrix. Based on the conducted cytotoxicity studies, it may be concluded that the obtained materials do not adversely affect the tested cell lines, therefore they can be subjected to more advanced analyzes.

Keywords: hydrogel polymers, cytostatics, drug carriers, cytotoxicity

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Authors: Honey Bryant, Elvina Chu

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Stroke is the leading cause of disability in adults in Canada and directly related to depression, anxiety, and sleep disorders; with an estimated annual cost of $50 billion in health care. Strokes not only impact the individual but society as a whole. Current stroke rehabilitation does not include Music Therapy, although it has success in clinical research in the use of stroke rehabilitation. This study examines the use of neurologic music therapy (NMT) in conjunction with stroke rehabilitation to improve sleep quality, reduce stress levels, and promote neurogenesis. Existing research on NMT in stroke is limited, which means any conclusive information gathered during this study will be significant. My novel hypotheses are a.) stroke patients will become less depressed and less anxious with improved sleep following NMT. b.) NMT will reduce stress levels and promote neurogenesis in stroke patients admitted for rehabilitation. c.) Beneficial effects of NMT will be sustained at least short-term following treatment. Participants were recruited from the in-patient stroke rehabilitation program at Providence Care Hospital in Kingston, Ontario, Canada. All participants-maintained stroke rehabilitation treatment as normal. The study was spilt into two groups, the first being Passive Music Listening (PML) and the second Neurologic Music Therapy (NMT). Each group underwent 10 sessions of intensive music therapy lasting 45 minutes for 10 consecutive days, excluding weekends. Psychiatric Assessments, Epworth Sleepiness Scale (ESS), Hospital Anxiety & Depression Rating Scale (HADS), and Music Engagement Questionnaire (MusEQ), were completed, followed by a general feedback interview. Physiological markers of stress were measured through blood pressure measurements and heart rate variability. Serum collections reviewed neurogenesis via Brain-derived neurotrophic factor (BDNF) and stress markers of cortisol levels. As this study is still on-going, a formal analysis of data has not been fully completed, although trends are following our hypotheses. A decrease in sleepiness and anxiety is seen upon the first cohort of PML. Feedback interviews have indicated most participants subjectively felt more relaxed and thought PML was useful in their recovery. If the hypothesis is supported, larger external funding which will allow for greater investigation of the use of NMT in stroke rehabilitation. As we know, NMT is not covered under Ontario Health Insurance Plan (OHIP), so there is limited scientific data surrounding its uses as a clinical tool. This research will provide detailed findings of the treatment of neuropsychiatric aspects of stroke. Concurrently, a passive music listening study is being designed to further review the use of PML in rehabilitation as well.

Keywords: music therapy, psychotherapy, neurologic music therapy, passive music listening, neuropsychiatry, counselling, behavioural, stroke, stroke rehabilitation, rehabilitation, neuroscience

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Authors: Anargha A. Dhorde, Deshpande Gauri, Amit G. Dhorde

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Mula-Mutha basin is one of the speedily urbanizing watersheds, wherein two major urban centers, Pune and Pimpri-Chinchwad, have developed at a shocking rate in the last two decades. Such changing land use/land cover (LULC) is prone to hydrological problems and flash floods are a frequent, eventuality in the lower reaches of the basin. The present research brings out the impact of varying LULC, impervious surfaces on urban surface hydrology and generates storm-runoff scenarios for the hydrological units. The two multi-temporal satellite images were processed and supervised classification is performed with > 75% accuracy. The built-up has increased from 14.4% to 34.37% in the 28 years span, which is concentrated in and around the Pune-PCMC region. Impervious surfaces that were obtained by population calibrated multiple regression models. Almost 50% area of the watershed is impervious, which attribute to increase surface runoff and flash floods. The SCS-CN method was employed to calculate surface runoff of the watershed. The comparison between calculated and measured values of runoff was performed in a statistically precise way which shows no significant difference. Increasing built-up areas, as well as impervious surface areas due to rapid urbanization and industrialization, may lead to generating high runoff volumes in the basin especially in the urbanized areas of the watershed and along the major transportation arteries. Simulations generated with 50 mm and 100 mm rainstorm depth conspicuously noted that most of the changes in terms of increased runoff are constricted to the highly urbanized areas. Considering whole watershed area, the runoff values 39 m³ generated with 1'' rainfall whereas only urbanized areas of the basin (Pune and Pimpari-Chinchwad) were generated 11154 m³ runoff. Such analysis is crucial in providing information regarding their intensity and location, which proves instrumental in their analysis in order to formulate proper mitigation measures and rehabilitation strategies.

Keywords: land use/land cover, LULC, impervious surfaces, surface hydrology, storm-runoff scenarios

Procedia PDF Downloads 215

Authors: Dmitriy Syssoyev, Aslan Seitkamzin, Natalya Lim, Kamilla Mussina, Abduzhappar Gaipov, Dimitri Poddighe, Dinara Galiyeva

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Background: Data on the epidemiology of congenital heart defects (CHD) in Kazakhstan is scarce. Therefore, the aim of this study was to describe the incidence, prevalence and all-cause mortality of patients with CHD in Kazakhstan, using national large-scale registry data from the Unified National Electronic Healthcare System (UNEHS) for the period of 2014-2020. Methods: In this retrospective cohort study, the included data pertained to all patients diagnosed with CHD in Kazakhstan and registered in UNEHS between January 2014 and December 2020. CHD was defined based on International Classification of Diseases 10th Revision (ICD-10) codes Q20-Q26. Incidence, prevalence, and all-cause mortality rates were calculated per 100,000 population. Survival analysis was performed using Cox proportional hazards regression modeling and the Kaplan-Meier method. Results: In total, 66,512 patients were identified. Among them, 59,534 (89.5%) were diagnosed with a single CHD, while 6,978 (10.5%) had more than two CHDs. The median age at diagnosis was 0.08 years (interquartile range (IQR) 0.01 – 0.66) for people with multiple CHD types and 0.39 years (IQR 0.04 – 8.38) for those with a single CHD type. The most common CHD types were atrial septal defect (ASD) and ventricular septal defect (VSD), accounting for 25.8% and 21.2% of single CHD cases, respectively. The most common multiple types of CHD were ASD with VSD (23.4%), ASD with patent ductus arteriosus (PDA) (19.5%), and VSD with PDA (17.7%). The incidence rate of CHD decreased from 64.6 to 47.1 cases per 100,000 population among men and from 68.7 to 42.4 among women. The prevalence rose from 66.1 to 334.1 cases per 100,000 population among men and from 70.8 to 328.7 among women. Mortality rates showed a slight increase from 3.5 to 4.7 deaths per 100,000 in men and from 2.9 to 3.7 in women. Median follow-up was 5.21 years (IQR 2.47 – 11.69). Male sex (HR 1.60, 95% CI 1.45 - 1.77), having multiple CHDs (HR 2.45, 95% CI 2.01 - 2.97), and living in a rural area (HR 1.32, 95% CI 1.19 - 1.47) were associated with a higher risk of all-cause mortality. Conclusion: The incidence of CHD in Kazakhstan has shown a moderate decrease between 2014 and 2020, while prevalence and mortality have increased. Male sex, multiple CHD types, and rural residence were significantly associated with a higher risk of all-cause mortality.

Keywords: congenital heart defects (CHD), epidemiology, incidence, Kazakhstan, mortality, prevalence

Procedia PDF Downloads 90

Authors: Amir Reza Asnafi, Masoumeh Kazemizadeh, Najmeh Salemi

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Due to the diversity of information resources in the web0.2 environment, which is increasing in number from time to time, the social tagging system should be used to discuss Internet resources. Studying the relevance of social tags to thematic headings can help enrich resources and make them more accessible to resources. The present research is of applied-theoretical type and research method of content analysis. In this study, using the listing method and content analysis, the level of accurate, approximate, relative, and non-conformity of social labels of books available in the field of information science and bibliography of Kitabrah website with Persian subject headings was determined. The exact matching of subject headings with social tags averaged 22 items, the approximate matching of subject headings with social tags averaged 36 items, the relative matching of thematic headings with social tags averaged 36 social items, and the average matching titles did not match the title. The average is 116. According to the findings, the exact matching of subject headings with social labels is the lowest and the most inconsistent. This study showed that the average non-compliance of subject headings with social labels is even higher than the sum of the three types of exact, relative, and approximate matching. As a result, the relevance of thematic titles to social labels is low. Due to the fact that the subject headings are in the form of static text and users are not allowed to interact and insert new selected words and topics, and on the other hand, in websites based on Web 2 and based on the social classification system, this possibility is available for users. An important point of the present study and the studies that have matched the syntactic and semantic matching of social labels with thematic headings is that the degree of conformity of thematic headings with social labels is low. Therefore, these two methods can complement each other and create a hybrid cataloging that includes subject headings and social tags. The low level of conformity of thematic headings with social tags confirms the results of backgrounds and writings that have compared the social tags of books with the thematic headings of the Library of Congress. It is not enough to match social labels with thematic headings. It can be said that these two methods can be complementary.

Keywords: Web 2/0, social tags, subject headings, hybrid cataloging

Procedia PDF Downloads 156

Authors: Ivana Loncarevic, Biljana Pajin, Jovana Petrovic, Danica Zaric, Vesna Tumbas Saponjac, Aleksandar Fistes

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Chocolate is a food that activates pleasure centers in the human brain. In comparison to black and milk chocolate, white chocolate does not contain fat-free cocoa solids and thus lacks bioactive components. The aim of this study was to examine the sensory characteristics of enriched white chocolate with the addition of 10% of raspberry juice encapsulated in maltodextrins (denoted as encapsulate). Chocolate is primarily intended for enjoyment, and therefore, the sensory expectation is a critical factor for consumers when selecting a new type of chocolate. Consumer acceptance of chocolate depends primarily on the appearance and taste, but also very much on the mouthfeel, which mainly depends on the particle size of chocolate. Chocolate samples were evaluated by a panel of 8 trained panelists, food technologists, trained according to ISO 8586 (2012). Panelists developed the list of attributes to be used in this study: intensity of red color (light to dark); glow on the surface (mat to shiny); texture on snap (appearance of cavities or holes on the snap surface that are seen - even to gritty); hardness (hardness felt during the first bite of chocolate sample in half by incisors - soft to hard); melting (the time needed to convert solid chocolate into a liquid state – slowly to quickly); smoothness (perception of evenness of chocolate during melting - very even to very granular); fruitiness (impression of fruity taste - light fruity notes to distinct fruity notes); sweetness (organoleptic characteristic of pure substance or mixture giving sweet taste - lightly sweet to very sweet). The chocolate evaluation was carried out 24 h after sample preparation in the sensory laboratory, in partitioned booths, which were illuminated with fluorescent lights (ISO 8589, 2007). Samples were served in white plastic plates labeled with three-digit codes from a random number table. Panelist scored the perceived intensity of each attribute using a 7-point scale (1 = the least intensity and 7 = the most intensity) (ISO 4121, 2002). The addition of 10% of encapsulate had a big influence on chocolate color, where enriched chocolate got a nice reddish color. At the same time, the enriched chocolate sample had less intensity of gloss on the surface. The panelists noticed that addition of encapsulate reduced the time needed to convert solid chocolate into a liquid state, increasing its hardness. The addition of encapsulate had a significant impact on chocolate flavor. It reduced the sweetness of white chocolate and contributed to the fruity raspberry flavor.

Keywords: white chocolate, encapsulated raspberry juice, color, sensory characteristics

Procedia PDF Downloads 157

Authors: Ana Breda, Catarina Cruz

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Daily, we face unpredictable events, often attributed to chance, as there is no justification for such an occurrence. Chance, understood as a source of uncertainty, is present in several aspects of human life, such as weather forecasts, dice rolling, and lottery. Surprisingly, humans and some animals can quickly adjust their behavior to handle efficiently doubly stochastic processes (random events with two layers of randomness, like unpredictable weather affecting dice rolling). This adjustment ability suggests that the human brain has built-in mechanisms for perceiving, understanding, and responding to simple probabilities. It also explains why current trends in mathematics education include probability concepts in official curriculum programs, starting from the third year of primary education onwards. In the first years of schooling, children learn to use a certain type of (specific) vocabulary, such as never, always, rarely, perhaps, likely, and unlikely, to help them to perceive and understand the probability of some events. These are keywords of crucial importance for their perception and understanding of probabilities. The development of the probabilistic concepts comes from facts and cause-effect sequences resulting from the subject's actions, as well as the notion of chance and intuitive estimates based on everyday experiences. As part of a junior summer school program, which took place at a Portuguese university, a non-formal learning experiment was carried out with 18 children in the 5th and 6th grades. This experience was designed to be implemented in a dynamic of a serious ice-breaking game, to assess their levels of probabilistic, critical, and creative thinking in understanding impossible, certain, equally probable, likely, and unlikely events, and also to gain insight into how the non-formal learning context influenced their achievements. The criteria used to evaluate probabilistic thinking included the creative ability to conceive events classified in the specified categories, the ability to properly justify the categorization, the ability to critically assess the events classified by other children, and the ability to make predictions based on a given probability. The data analysis employs a qualitative, descriptive, and interpretative-methods approach based on students' written productions, audio recordings, and researchers' field notes. This methodology allowed us to conclude that such an approach is an appropriate and helpful formative assessment tool. The promising results of this initial exploratory study require a future research study with children from these levels of education, from different regions, attending public or private schools, to validate and expand our findings.

Keywords: critical and creative thinking, non-formal mathematics learning, probabilistic thinking, serious game

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Authors: Ming-Jyh Chen, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang

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Introduction: Social responsibility is the key to sustainable organizational development. Under the ground Green Health Hospital Declaration signed by our superintendent, we have launched comprehensive energy conservation management in medical services, the community, and the staff’s life. To execute environment-friendly promotion with robust strategies, we build up a low-carbon medical system and community with smart green public construction promotion as well as intensifying energy conservation education and communication. Purpose/Methods: With the support of the board and the superintendent, we construct an energy management team, commencing with an environment-friendly system, management, education, and ISO 50001 energy management system; we have ameliorated energy performance and energy efficiency and continuing. Results: In the year 2021, we have achieved multiple goals. The energy management system efficiently controls diesel, natural gas, and electricity usage. About 5% of the consumption is saved when compared to the numbers from 2018 and 2021. Our company develops intelligent services and promotes various paperless electronic operations to provide people with a vibrant and environmentally friendly lifestyle. The goal is to save 68.6% on printing and photocopying by reducing 35.15 million sheets of paper yearly. We strengthen the concept of environmental protection classification among colleagues. In the past two years, the amount of resource recycling has reached more than 650 tons, and the resource recycling rate has reached 70%. The annual growth rate of waste recycling is about 28 metric tons. Conclusions: To build a green medical system with “high efficacy, high value, low carbon, low reliance,” energy stewardship, economic prosperity, and social responsibility are our principles when it comes to formulation of energy conservation management strategies, converting limited sources to efficient usage, developing clean energy, and continuing with sustainable energy.

Keywords: energy efficiency, environmental education, green hospital, sustainable development

Procedia PDF Downloads 75

Authors: Vanessa Bennemann, Gabriela Laste, Márcia Inês Goettert

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The gestational period is a phase in which the pregnant woman undergoes constant physiological and hormonal changes, which are part of the woman’s biological cycle, the development of the fetus, childbirth, and lactation. These are factors of response to the immunological adaptation of the human reproductive process that is directly related to the pregnancy’s well-being and development. Although most pregnancies occur without complications, about 15% of pregnant women will develop potentially fatal complications, implying maternal and fetal risk. Therefore, requiring specialized care for high-risk pregnant women (HRPW) with obstetric interventions for the survival of the mother and/or fetus. Among the risk factors that characterize HRPW are the women's age, gestational diabetes mellitus (GDM), autoimmune diseases, infectious diseases such as syphilis and HIV, hypertension (SAH), preeclampsia, eclampsia, HELLP syndrome, uterine contraction abnormalities, and premature placental detachment (PPD), thyroid disorders, among others. Thus, pregnancy has an impact on the thyroid gland causing changes in the functioning of the mother's thyroid gland, altering the thyroid hormone (TH) profiles and production as pregnancy progresses. Considering, throughout the gestational period, the interpretation of the results of the tests to evaluate the thyroid functioning depends on the stage in which the pregnancy is. Thyroid disorders are directly related to adverse obstetric outcomes and in child development. Therefore, the adequate release of TH is important for a pregnancy without complications and optimal fetal growth and development. Objective: Investigate the physiological effects caused by thyroid disorders in the gestational period. Methods: A search for articles indexed in PubMed, Scielo, and MDPI databases, was performed using the term “AND”, with the descriptors: Pregnancy, Thyroid. With several combinations that included: Melatonin, Thyroidopathy, Inflammatory processes, Cytokines, Anti-inflammatory, Antioxidant, High-risk pregnancy. Subsequently, the screening was performed through the analysis of titles and/or abstracts. The criteria were: including clinical studies in general, randomized or not, in the period of 10 years prior to the research, in the English literature; excluded: experimental studies, case reports, research in the development phase. Results: In the preliminary results, a total of studies (n=183) were found, (n=57) excluded, such as studies of cancer, diabetes, obesity, and skin diseases. Conclusion: To date, it has been identified that thyroid diseases can impair the fetus’s brain development. Further research is suggested on this matter to identify new substances that may have a potential therapeutic effect to aid the gestational period with thyroid diseases.

Keywords: pregnancy, thyroid, melatonin, high-risk pregnancy

Procedia PDF Downloads 134

Authors: Yuli Hou, Jianping Sun, Mengdan Gao, Hui Liu, Ling Qin, Ang Li, Dongfu Li, Yonghong Zhang, Yan Zhao

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Background and Aims: Interferon-induced transmembrane protein 3 (IFITM3) is a component of ISG (Interferon-Stimulated Gene) family. IFITM3 has been recognized as a key signal molecule regulating cell growth in some tumors. However, the function of IFITM3 rs12252-CC genotype in the hepatocellular carcinoma (HCC) remains unknown to author’s best knowledge. A cohort study was employed to clarify the relationship between IFITM3 rs12252-CC genotype and HCC progression, and cellular experiments were used to investigate the correlation of function of IFITM3 and the progress of HCC. Methods: 336 candidates were enrolled in study, including 156 with HBV related HCC and 180 with chronic Hepatitis B infections or liver cirrhosis. Polymerase chain reaction (PCR) was employed to determine the gene polymorphism of IFITM3. The functions of IFITM3 were detected in PLC/PRF/5 cell with different treated:LV-IFITM3 transfected with lentivirus to knockdown the expression of IFITM3 and LV-NC transfected with empty lentivirus as negative control. The IFITM3 expression, proliferation and migration were detected by Quantitative reverse transcription polymerase chain reaction (qRT-PCR), QuantiGene Plex 2.0 assay, western blotting, immunohistochemistry, Cell Counting Kit(CCK)-8 and wound healing respectively. Six samples (three infected with empty lentiviral as control; three infected with LV-IFITM3 vector lentiviral as experimental group ) of PLC/PRF/5 were sequenced at BGI (Beijing Genomics Institute, Shenzhen,China) using RNA-seq technology to identify the IFITM3-related signaling pathways and chose PI3K/AKT pathway as related signaling to verify. Results: The patients with HCC had a significantly higher proportion of IFITM3 rs12252-CC compared with the patients with chronic HBV infection or liver cirrhosis. The distribution of CC genotype in HCC patients with low differentiation was significantly higher than that in those with high differentiation. Patients with CC genotype found with bigger tumor size, higher percentage of vascular thrombosis, higher distribution of low differentiation and higher 5-year relapse rate than those with CT/TT genotypes. The expression of IFITM3 was higher in HCC tissues than adjacent normal tissues, and the level of IFITM3 was higher in HCC tissues with low differentiation and metastatic than high/medium differentiation and without metastatic. Higher RNA level of IFITM3 was found in CC genotype than TT genotype. In PLC/PRF/5 cell with knockdown, the ability of cell proliferation and migration was inhibited. Analysis RNA sequencing and verification of RT-PCR found out the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin(PI3K/AKT/mTOR) pathway was associated with knockdown IFITM3.With the inhibition of IFITM3, the expression of PI3K/AKT/mTOR signaling pathway was blocked and the expression of vimentin was decreased. Conclusions: IFITM3 rs12252-CC with the higher expression plays a vital role in the progress of HCC by regulating HCC cell proliferation and migration. These effects are associated with PI3K/AKT/mTOR signaling pathway.

Keywords: IFITM3, interferon-induced transmembrane protein 3, HCC, hepatocellular carcinoma, PI3K/ AKT/mTOR, phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

Procedia PDF Downloads 92

Authors: Fausto Morais

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Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.

Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning

Procedia PDF Downloads 139

Authors: Georgia Saxami, Evangelia N. Kerezoudi, Evdokia K. Mitsou, Marigoula Vlassopoulou, Georgios Zervakis, Adamantini Kyriacou

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Autism Spectrum Disorder (ASD) is a complex group of developmental disorders of the brain, characterized by social and communication dysfunctions, stereotypes and repetitive behaviors. The potential interaction between gut microbiota (GM) and autism has not been fully elucidated. Children with autism often suffer gastrointestinal dysfunctions, while alterations or dysbiosis of GM have also been observed. Treatment with dietary components has been postulated to regulate GM and improve gastrointestinal symptoms, but there is a lack of evidence for such approaches in autism, especially for prebiotics. This study assessed the effects of Pleurotus eryngii mushroom (candidate prebiotic) and inulin (known prebiotic compound) on gut microbial composition, using faecal samples from autistic children in an in vitro batch culture fermentation system. Selected members of GM were enumerated at baseline (0 h) and after 24 h fermentation by quantitative PCR. After 24 h fermentation, inulin and P. eryngii mushroom induced a significant increase in total bacteria and Faecalibacterium prausnitzii compared to the negative control (gut microbiota of each autistic donor with no carbohydrate source), whereas both treatments induced a significant increase in levels of total bacteria, Bifidobacterium spp. and Prevotella spp. compared to baseline (t=0h) (p for all <0.05). Furthermore, this study evaluated the impact of fermentation supernatants (FSs), derived from P. eryngii mushroom or inulin, on the expression levels of tight junctions’ genes (zonulin-1, occludin and claudin-1) in Caco-2 cells stimulated by bacterial lipopolysaccharides (LPS). Pre-incubation of Caco-2 cells with FS from P. eryngii mushroom led to a significant increase in the expression levels of zonulin-1, occludin and claudin-1 genes compared to the untreated cells, the cells that were subjected to LPS and the cells that were challenged with FS from negative control (p for all <0.05). In addition, incubation with FS from P. eryngii mushroom led to the highest mean expression values for zonulin-1 and claudin-1 genes, which differed significantly compared to inulin (p for all <0.05). Overall, this research highlighted the beneficial in vitro effects of P. eryngii mushroom on the composition of GM of autistic children after 24 h of fermentation. Also, our data highlighted the potential preventive effect of P. eryngii FSs against dysregulation of the intestinal barrier, through upregulation of tight junctions’ genes associated with the integrity and function of the intestinal barrier. This research has been financed by "Supporting Researchers with Emphasis on Young Researchers - Round B", Operational Program "Human Resource Development, Education and Lifelong Learning."

Keywords: gut microbiota, intestinal barrier, autism spectrum disorders, Pleurotus Eryngii

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Authors: Mustafa M. Donma, Orkide Donma

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Metabolic syndrome (MetS) is a disease associated with obesity. It is a complicated clinical problem possibly affecting body composition as well as macrominerals. These parameters gain further attention, particularly in the pediatric population. The aim of this study is to investigate the amount of discrete body composition fractions in groups that differ in the severity of obesity. Also, the possible associations with calcium (Ca), phosphorus (P), magnesium (Mg) will be examined. The study population was divided into four groups. Twenty-eight, 29, 34, and 34 children were involved in Group 1 (healthy), 2 (obese), 3 (morbid obese), and 4 (MetS), respectively. Institutional Ethical Committee approved the study protocol. Informed consent forms were obtained from the participants. The classification of obese groups was performed based upon the recommendations of the World Health Organization. Metabolic syndrome components were defined. Serum Ca, P, Mg concentrations were measured. Within the scope of body composition, fat mass, fat-free mass, protein mass, mineral mass were determined by a body composition monitor using bioelectrical impedance analysis technology. Weight, height, waist circumference, hip circumference, head circumference, and neck circumference values were recorded. Body mass index, diagnostic obesity notation model assessment index, fat mass index, and fat-free mass index values were calculated. Data were statistically evaluated and interpreted. There was no statistically significant difference among the groups in terms of Ca and P concentrations. Magnesium concentrations differed between Group 1 and Group 4. Strong negative correlations were detected between P as well as Mg and fat mass index as well as diagnostic obesity notation model assessment index in Group 4, the group, which comprised morbid obese children with MetS. This study emphasized unique associations of P and Mg minerals with diagnostic obesity notation model assessment index and fat mass index during the evaluation of morbid obese children with MetS. It was also concluded that diagnostic obesity notation model assessment index and fat mass index were more proper indices in comparison with body mass index and fat-free mass index for the purpose of defining body composition in children.

Keywords: children, fat mass, fat-free mass, macrominerals, obesity

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Authors: Umamaheswari Shanmugam, Silvia Ronchi

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Software, artificial intelligence, and machine learning can improve healthcare through innovative and advanced technologies that can use the large amount and variety of data generated during healthcare services every day; one of the significant advantages of these new technologies is the ability to get experience and knowledge from real-world use and to improve their performance continuously. Healthcare systems and institutions can significantly benefit because the use of advanced technologies improves the efficiency and efficacy of healthcare. Software-defined as a medical device, is stand-alone software that is intended to be used for patients for one or more of these specific medical intended uses: - diagnosis, prevention, monitoring, prediction, prognosis, treatment or alleviation of a disease, any other health conditions, replacing or modifying any part of a physiological or pathological process–manage the received information from in vitro specimens derived from the human samples (body) and without principal main action of its principal intended use by pharmacological, immunological or metabolic definition. Software qualified as medical devices must comply with the general safety and performance requirements applicable to medical devices. These requirements are necessary to ensure high performance and quality and protect patients' safety. The evolution and the continuous improvement of software used in healthcare must consider the increase in regulatory requirements, which are becoming more complex in each market. The gap between these advanced technologies and the new regulations is the biggest challenge for medical device manufacturers. Regulatory requirements can be considered a market barrier, as they can delay or obstacle the device's approval. Still, they are necessary to ensure performance, quality, and safety. At the same time, they can be a business opportunity if the manufacturer can define the appropriate regulatory strategy in advance. The abstract will provide an overview of the current regulatory framework, the evolution of the international requirements, and the standards applicable to medical device software in the potential market all over the world.

Keywords: artificial intelligence, machine learning, SaMD, regulatory, clinical evaluation, classification, international requirements, MDR, 510k, PMA, IMDRF, cyber security, health care systems

Procedia PDF Downloads 83

Authors: Imbesat Daudi

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Islamophobia, which is a billion-dollar industry, is widespread, especially in the United States, Europe, India, Israel, and countries that have Muslim minorities at odds with their governmental policies. Hatred of Islam in the West did not evolve spontaneously; it was methodically created. Islamophobia's current format has been designed to spread on its own, find a space in the Western psyche, and resist its eradication. Hatred has been sustained by neoconservative ideologues and their allies, which are supported by the mainstream media. Social scientists have evaluated how ideas spread, why any idea can go viral, and where new ideas find space in our brains. This was possible because of the advances in the computational power of software and computers. Spreading of ideas, including Islamophobia, follows a sine curve; it has three phases: An initial exploratory phase with a long lag period, an explosive phase if ideas go viral, and the final phase when ideas find space in the human psyche. In the initial phase, the ideas are quickly examined in a center in the prefrontal lobe. When it is deemed relevant, it is sent for evaluation to another center of the prefrontal lobe; there, it is critically examined. Once it takes a final shape, the idea is sent as a final product to a center in the occipital lobe. This center cannot critically evaluate ideas; it can only defend them from its critics. Counterarguments, no matter how scientific, are automatically rejected. Therefore, arguments that could be highly effective in the early phases are counterproductive once they are stored in the occipital lobe. Anti-Islamophobic intellectuals have done a very good job of countering Islamophobic arguments. However, they have not been as effective as neoconservative ideologues who have promoted anti-Muslim rhetoric that was based on half-truths, misinformation, or outright lies. The failure is partly due to the support pro-war activists receive from the mainstream media, state institutions, mega-corporations engaged in violent conflicts, and think tanks that provide Islamophobic arguments. However, there are also scientific reasons why anti-Islamophobic thinkers have been less effective. There are different dynamics of spreading ideas once they are stored in the occipital lobe. The human brain is incapable of evaluating further once it accepts ideas as its own; therefore, a different strategy is required to be effective. This paper examines 1) why anti-Islamophobic intellectuals have failed in changing the minds of non-Muslims and 2) the steps of countering hatred. Simply put, a new strategy is needed that can effectively counteract hatred of Islam and Muslims. Islamophobia is a disease that requires strong measures. Fighting hatred is always a challenge, but if we understand why Islamophobia is taking root in the twenty-first century, one can succeed in challenging Islamophobic arguments. That will need a coordinated effort of Intellectuals, writers and the media.

Keywords: islamophobia, Islam and violence, anti-islamophobia, demonization of Islam

Procedia PDF Downloads 44

Authors: Zeinab Farhat, Nicolas Errien, Romuald Wernert, Véronique Verriele, Frédéric Amiard, Philippe Daniel

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Ovarian cancer, also known as the silent killer, is the fifth most common cancer among women worldwide, and its death rate is higher than that of other gynecological cancers. The low survival rate of women with high-grade serous ovarian carcinoma highlights the critical need for the development of new methods for early detection and diagnosis of the disease. The aim of this study was to evaluate if Raman spectroscopy combined with chemometric methods such as Principal Component Analysis (PCA) could differentiate between cancerous and normal tissues from different types of samples, such as paraffin embedding, chemical deparaffinized, formalin-fixed and fresh samples of the same normal and malignant ovarian tissue. The method was applied specifically to two critical spectral regions: the signature region (860-1000 〖cm〗^(-1)) and the high-frequency region (2800-3100 〖cm〗^(-1) ). The mean spectra of paraffin-embedded in normal and malignant tissues showed almost similar intensity. On the other hand, the mean spectra of normal and cancer tissues from chemical deparaffinized, formalin-fixed, and fresh samples show significant intensity differences. These spectral differences reflect variations in the molecular composition of the tissues, particularly lipids and proteins. PCA, which was applied to distinguish between cancer and normal tissues, was performed on whole spectra and on selected regions—the PCA score plot of paraffin-embedded shows considerable overlap between the two groups. However, the PCA score of chemicals deparaffinized, formalin-fixed, and fresh samples showed a good discrimination of tissue types. Our findings were validated by analyses of a set of samples whose status (normal and cancerous) was not previously known. The results of this study suggest that Raman Spectroscopy associated with PCA methods has the capacity to provide clinically significant differentiation between normal and cancerous ovarian tissues.

Keywords: Raman spectroscopy, ovarian cancer, signal processing, Principal Component Analysis, classification

Procedia PDF Downloads 11