Search results for: gene expression datasets

Authors: Artur Matuck, Guilherme F. Nobre

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Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: J. D. Temperman

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Introduction: In particular, in relation to religion, the meaning and scope of freedom of expression have been tested in recent times. This paper investigates the legal justifications for restrictions that have been suggested in this area and asks whether they are sustainable from an international human rights perspective. The universal human rights instruments, particularly the UN International Covenant on Civil and Political Rights (ICCPR), are increasingly geared towards eradicating ‘incitement’ to contingent harms like violence or discrimination, whilst forms of extreme speech that fall short of such incitement are to be protected rather than countered by states. Human Rights Committee’s draft-General Comment on freedom of expression, adopted in 2011, provides another strong indication that this is the envisaged way forward: repealing anti-blasphemy and anti-religious defamation laws, whilst simultaneously increasing efforts to combat ‘incitement’. Within regional human rights frameworks, notably the European Convention system, judgments have in fact supported legal restrictions on both hate speech, holocaust denial, and blasphemy or religious defamation. Major contributions to scholarship: This paper proposes an actus reus for the offense of ‘advocacy of religious hatred that constitutes incitement to discrimination or violence’, as enshrined in Article 20(2) of the UN ICCPR. In underscoring the high threshold of ‘incitement’, the author distinguishes this offense from such notions as ‘blasphemy’ or ‘defamation of religions’. In addition to treating the said provision as a sui generis prohibition, the question is addresses whether a ‘right to be protected against incitement’ may be distilled from the ICCPR. Furthermore, the author will discuss the question of how to judge incitement; notably, is mens rea required to convict someone of incitement, and if so, what degree of mens rea? This analysis also includes the question how to balance content and context factors when addressing alleged instances of incitement, notably what factors make provide for a likelihood that imminent acts of violence or discrimination will ensue from an inciteful speech act? Methodology: This paper takes a double comparative approach: (i) it endeavours to compare and contrast monitoring bodies’ approach to incitement (notably, the UN Human Rights Committee, but also the UN Committee on the Elimination of Racial Discrimination which monitors states’ compliance with Article 4 of ICERD on incitement); and (ii) it endeavours to chart and compare and analyse from an international human rights perspective recent forms of state practice in the field of dealing with incitement (i.e. a comparative legal analysis and vertical human rights analysis of newly emerging incitement legislation in the light of the said international standards). Conclusion: This paper conceptualizes a legal notion – ‘incitement’ – encapsulated in international human rights law that may have a profound bearing on contemporary challenges of radicalization and religious strife.

Keywords: incitement, international human rights law, religious hatred, violence

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Authors: Hanlin Liu, Hua Li, Yintan AI

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Network performance prediction (NPP) is essential for the management and optimization of software-defined networking (SDN) and contributes to improving the quality of service (QoS) in SDN to meet the requirements of users. Although current deep learning-based methods can achieve high effectiveness, they still suffer from some problems, such as difficulty in capturing global information of the network, inefficiency in modeling end-to-end network performance, and inadequate graph feature extraction. To cope with these issues, our proposed Graphormer-based architecture for NPP leverages the powerful graph representation ability of Graphormer to effectively model the graph structure data, and a node-edge transformation algorithm is designed to transfer the feature extraction object from nodes to edges, thereby effectively extracting the end-to-end performance characteristics of the network. Moreover, routing oriented centrality measure coefficient for nodes and edges is proposed respectively to assess their importance and influence within the graph. Based on this coefficient, an enhanced feature extraction method and an advanced centrality encoding strategy are derived to fully extract the structural information of the graph. Experimental results on three public datasets demonstrate that the proposed GraphNPP architecture can achieve state-of-the-art results compared to current NPP methods.

Keywords: software-defined networking, network performance prediction, Graphormer, graph neural network

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Authors: Patricia Jiménez, Rafael Corchuelo

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Nowadays the World Wide Web is the most popular source of information that relies on billions of on-line documents. Web mining is used to crawl through these documents, collect the information of interest and process it by applying data mining tools in order to use the gathered information in the best interest of a business, what enables companies to promote theirs. Unfortunately, it is not easy to extract the information a web site provides automatically when it lacks an API that allows to transform the user-friendly data provided in web documents into a structured format that is machine-readable. Rule-based information extractors are the tools intended to extract the information of interest automatically and offer it in a structured format that allow mining tools to process it. However, the performance of an information extractor strongly depends on the search heuristic employed since bad choices regarding how to learn a rule may easily result in loss of effectiveness and/or efficiency. Improving search heuristics regarding efficiency is of uttermost importance in the field of Web Information Extraction since typical datasets are very large. In this paper, we employ an information extractor based on a classical top-down algorithm that uses the so-called Information Gain heuristic introduced by Quinlan and Cameron-Jones. Unfortunately, the Information Gain relies on some well-known problems so we analyse an intuitive alternative, Termini, that is clearly more efficient; we also analyse other proposals in the literature and conclude that none of them outperforms the previous alternative.

Keywords: information extraction, search heuristics, semi-structured documents, web mining.

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Authors: Ryan D. Martinus

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Inflammation of the endothelium is an important process leading to diabetic atherosclerosis. However, the molecular mechanisms by which diabetes contributes to endothelial inflammation remain to be established. Using In-vitro cultured Human cells and Hsp60 specific ELISA assays, we show that Hsp60 is not only induced in Human monocyte cells under hyperglycaemic conditions but that the Hsp60 is also secreted from these cells. Furthermore, we also demonstrate that the Hsp60 secreted from these monocyte cells is also able to activate Toll-like receptor-4 (TLR4) from Human endothelial cells. This suggests that a potential link may exist between the hyperglycaemia-induced expression of Hsp60 in monocyte cells and vascular inflammation. Circulating levels of Hsp60 due to mitochondrial stress in diabetes patients could, therefore, be an important modulator of inflammation in endothelial cells and thus contribute to the increased incidences of atherosclerosis in diabetes mellitus.

Keywords: mitochondria, Hsp60, inflammation, diabetes mellitus

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Authors: David Jurado, Carlos Ávila

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Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: Noshaba Dilbar, Aisha Tahir, Amer Jamil

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During the last decade, DNA barcoding proved to be an authentic tool for discovery and identification of plants. In the present study, DNA barcoding of two species, Fagonia arabica and Fagonia indica was done for differentiation by using matK region. matK gene is considered as a universal barcode because of its easy alignment and high discrimination ability. In this study, matK yielded 100% sequencing results. The sequences from both plants were aligned at clustal W and observed that there is no nucleotide variation and polymorphism among both sequences. This was further analysed by BLAST which showed the similar sequences from different plants belonging to same family but didn’t find sequence of both species. Considering this, the resulted sequence was submitted by the name of Fagonia arabica with accession number KM276890. In the end, we analysed the results from BOLD which gave us the final conclusion that both plants are same as their matK sequences are 100% identical. In literature, both Fagonia indica and Fagonia arabica names are used for this plant but there is no clear differentiation has been observed in these plants. Results evaluate that Fagonia indica and Fagonia arabica are the alternative names of same plant.

Keywords: DNA barcoding, Fagonia arabica, Fagonia indica, matK

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Authors: Lugyi No

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This research delves into how students from two different backgrounds in a conflict-affected area, one group being internally displaced (IDP) and the other residing in permanent homes, express their emotions through art. Two experiments were conducted involving guided drawing to understand their emotional experiences. In the first experiment, where no specific instructions were given, both groups mostly used dark and dull colors, which suggests feelings of sadness and anxiety. Positive emotions were rarely depicted. In the second experiment, students were asked to express their emotions and provide reasons for their drawings. Here, we observed distinct variations: IDP students leaned towards vibrant colors, reflecting resilience, while town students tended to use monochromatic shades, likely due to their experiences with conflict. This abstract highlights the differing emotional expressions of these groups and the influence of instructions on their artwork.

Keywords: art therapy, conflict-affected areas, education in conflict zones, children's drawings

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Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: Tianqi Yu, Yingnan Ding, Yina Zhang, Yulan Liu, Yahui Li, Jing Lei, Jiyong Zhou, Suquan Song, Boli Hu

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Circular RNAs (circRNAs) play critical roles in various diseases. However, whether and how circular RNA regulates influenza A virus (IAV) infection is unknown. Here, we studied the role of circular RNA GATA Zinc Finger Domain Containing 2A (circ-GATAD2A) in the replication of IAV H1N1 in A549 cells. Circ-GATAD2A was formed upon H1N1 infection. Knockdown of circ-GATAD2A in A549 cells enhanced autophagy and inhibited H1N1 replication. By contrast, overexpression of circ-GATAD2A impaired autophagy and promoted H1N1 replication. Similarly, knockout of vacuolar protein sorting 34 (VPS34) blocked autophagy and increased H1N1 replication. However, the expression of circ-GATAD2A could not further enhance H1N1 replication in VPS34 knockout cells. Collectively, these data indicated that circ-GATAD2A promotes the replication of H1N1 by inhibiting autophagy.

Keywords: autophagy, circ-GATAD2A, H1N1, replication

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Authors: Paúl I. Cornejo

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The elastic energy released through Strombolian explosions has been quite studied, detailing various processes, sources, and precursory events at several volcanoes. We realized an analysis based on the relative partitioning of the elastic energy radiated into the atmosphere and ground by Strombolian-type explosions recorded at El Reventador volcano, using infrasound and seismic signals at high and moderate seismicity episodes during intense eruptive stages of explosive and effusive activity. Our results show that considerable values of Volcano Acoustic-Seismic Ratio (VASR or η) are obtained at high seismicity stages. VASR is a physical diagnostic of explosive degassing that we used to compare eruption mechanisms at El Reventador volcano for two datasets of explosions recorded at a Broad-Band BB seismic and infrasonic station located at ~5 kilometers from the vent. We conclude that the acoustic energy EA released during explosive activity (VASR η = 0.47, standard deviation σ = 0.8) is higher than the EA released during effusive activity; therefore, producing the highest values of η. Furthermore, we realized the analysis and characterization of the eruptive intensity for two episodes at high seismicity, calculating a η three-time higher for an episode of effusive activity with an occasional explosive component (η = 0.32, and σ = 0.42), than a η for an episode of only effusive activity (η = 0.11, and σ = 0.18), but more energetic.

Keywords: effusive, explosion quakes, explosive, Strombolian, VASR

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Authors: Seyedeh Azadeh Johari

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For thousand years, the literature of the world has been mostly composed of men, and in all different forms of it, men have tried to propose their masculine desires, ideologies, and beliefs. What has been less written about or studied, however, was the role that female desire plays in the predominantly masculine society, and mostly the role of male desires was the key point in literature. Male writers have mostly shown their female characters either as stereotypes and void of dynamic characters, images of a meek person who bent to the will of her male superiors or as wicked or villains. The only exception was the kind of strong and courageous women who have mostly been masculinized by their authors, mostly male authors, as showing the valuable or important features of men, instead of women’s. These characters are transgendered by the author and have a gender identity or expression that differs from the sex to which they were assigned. This is the issue that is discussed in this project. We will refer to some examples of female characters who show masculine traits and characteristics.

Keywords: comparative literature, female, masculinized, transgendered

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Authors: Waseem Al Talalwah, Shorok Al Dorazi, Roger Soames

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Persistent sciatic artery is a rare anatomical vascular variation resulting from a lack of regression of the embryonic dorsal axial artery. The axial artery is the main artery supplying the lower limb during development in the first trimester. The current research includes 206 sciatic artery cases in 171 patients between 1864 and 2012. It aims to identify the risk factor of sciatic artery aneurysm in congenital limb anomalies. Sciatic artery aneurysm was diagnosed incidentally in amniotic band syndrome (ABS) existing with no congenital anomaly in 0.7% or with double knee in 0.7%, with the tibia in 0.7% and with hemihypertrophy or soft tissue hypertrophy in 1.4%. Therefore, the current study indicates a relationship the same gene responsible for the congenital limb deformities may be responsible for non-regression of the sciatic artery. Furthermore, pediatricians should refer cases of congenital limb anomalies for vascular evaluation prior to corrective surgical intervention.

Keywords: amniotic band syndrome, congenital limb deformities, double knee, sciatic artery, sciatic artery aneurysm , soft tissue hypertrophy

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Authors: Ouassila Labbani-Narsis, Christophe Nicolle

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Building formal ontologies remains a complex process for companies. In the literature, this process is based on the technical knowledge and expertise of domain experts, without further details on the used methodologies. Possible problems of disagreements between experts, expression of tacit knowledge related to high level know-how rarely verbalized, qualification of results by using cases, or simply adhesion of the group of experts, remain currently unsolved. This paper proposes a methodological approach based on knowledge elicitation for the conception of formal, consensual, and shared ontologies. The proposed approach is experimentally tested on industrial collaboration projects in the field of manufacturing (associating knowledge sources from multinational companies) and in the field of viticulture (associating explicit knowledge and implicit knowledge acquired through observation).

Keywords: collaborative ontology engineering, knowledge elicitation, knowledge engineering, knowledge management

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

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Authors: Tahraoui Boualem

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The International Labor Organization is one of the specialized agencies of the United Nations, and it is the only organization within the United Nations system that is distinguished by its tripartite legitimacy and which simultaneously includes governments, workers' and employers' organizations of its member states in a joint effort to set standards and policies Work to promote decent work in various parts of the world, and the expression of international labor standards basically means two types of documents, namely international labor agreements and international labor recommendations, and so far its general conference, which is held annually, has set a number of standards, the number of which has reached 184 agreements and 192 recommendations so far. For this reason, it is decided to clarify the International Labor Organization and the formulation of international labor standards within two sections. In the first topic, the researcher discusses the concept of the International Labor Organization, and in the second topic, it highlights the legal basis for the authority of the International Labor Organization in protecting the rights of workers.

Keywords: international labor, international labor standards, rights of workers, nation’s system

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: Jamal S. M. Sabir, Edward C. Theriot, Schonna R. Manning, Abdulrahman L. Al-Malki, Mohammad, Mumdooh J. Sabir, Dwight K. Romanovicz, Nahid H. Hajrah, Robert K. Jansen, Matt P. Ashworth

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The diatom Phaeodactylum tricornutum has been used as a model for cell biologists and ecologists for over a century. We have incorporated several new raphid pennates into a three-gene phylogenetic dataset (SSU, rbcL, psbC), and recover Gomphonemopsis sp. as sister to P. tricornutum with 100% BS support. This is the first time a close relative has been identified for P. tricornutum with robust statistical support. We test and reject a succession of hypotheses for other relatives. Our molecular data are statistically significantly incongruent with placement of either or both species among the Cymbellales, an order of diatoms with which both have been associated. We believe that further resolution of the phylogenetic position of P. tricornutum will rely more on increased taxon sampling than increased genetic sampling. Gomphonemopsis is a benthic diatom, and its phylogenetic relationship with P. tricornutum is congruent with the hypothesis that P. tricornutum is a benthic diatom with specific adaptations that lead to active recruitment into the plankton. We hypothesize that other benthic diatoms are likely to have similar adaptations and are not merely passively recruited into the plankton.

Keywords: benthic, diatoms; ecology, Phaeodactylum tricornutum, phylogeny, tychoplankton

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Authors: Kai Chen, Shuguang Cui, Feng Yin

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Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

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Authors: Tatiana Butkova, Nikolai Kibrik, Kristina Malsagova, Alexander Izotov, Alexander Stepanov, Anna Kaysheva

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Relevance. The genetic risk of developing schizophrenia is determined by two factors: single nucleotide polymorphisms and gene copy number variations. The search for serological markers for early diagnosis of schizophrenia is driven by the fact that the first five years of the disease are accompanied by significant biological, psychological, and social changes. It is during this period that pathological processes are most amenable to correction. The aim of this study was to analyze single nucleotide polymorphisms (SNPs) that are hypothesized to potentially influence the onset and development of the endogenous process. Materials and Methods It was analyzed 73 single nucleotide polymorphism variants. The study included 48 patients undergoing inpatient treatment at "Psychiatric Clinical Hospital No. 1" in Moscow, comprising 23 females and 25 males. Inclusion criteria: - Patients aged 18 and above. - Diagnosis according to ICD-10: F20.0, F20.2, F20.8, F21.8, F25.1, F25.2. - Voluntary informed consent from patients. Exclusion criteria included: - The presence of concurrent somatic or neurological pathology, neuroinfections, epilepsy, organic central nervous system damage of any etiology, and regular use of medication. - Substance abuse and alcohol dependence. - Women who were pregnant or breastfeeding. Clinical and psychopathological assessment was complemented by psychometric evaluation using the PANSS scale at the beginning and end of treatment. The duration of observation during therapy was 4-6 weeks. Total DNA extraction was performed using QIAamp DNA. Blood samples were processed on Illumina HiScan and genotyped for 652,297 markers on the Infinium Global Chips Screening Array-24v2.0 using the IMPUTE2 program with parameters Ne=20,000 and k=90. Additional filtration was performed based on INFO>0.5 and genotype probability>0.5. Quality control of the obtained DNA was conducted using agarose gel electrophoresis, with each tested sample having a volume of 100 µL. Results. It was observed that several SNPs exhibited gender dependence. We identified groups of single nucleotide polymorphisms with a membership of 80% or more in either the female or male gender. These SNPs included rs2661319, rs2842030, rs4606, rs11868035, rs518147, rs5993883, and rs6269.Another noteworthy finding was the limited combination of SNPs sufficient to manifest clinical symptoms leading to hospitalization. Among all 48 patients, each of whom was analyzed for deviations in 73 SNPs, it was discovered that the combination of involved SNPs in the manifestation of pronounced clinical symptoms of schizophrenia was 19±3 out of 73 possible. In study, the frequency of occurrence of single nucleotide polymorphisms also varied. The most frequently observed SNPs were rs4849127 (in 90% of cases), rs1150226 (86%), rs1414334 (75%), rs10170310 (73%), rs2857657, and rs4436578 (71%). Conclusion. Thus, the results of this study provide additional evidence that these genes may be associated with the development of schizophrenia spectrum disorders. However, it's impossible cannot rule out the hypothesis that these polymorphisms may be in linkage disequilibrium with other functionally significant polymorphisms that may actually be involved in schizophrenia spectrum disorders. It has been shown that missense SNPs by themselves are likely not causative of the disease but are in strong linkage disequilibrium with non-functional SNPs that may indeed contribute to disease predisposition.

Keywords: gene polymorphisms, genotyping, single nucleotide polymorphisms, schizophrenia.

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Authors: Apichai Sawisit, Sirima Suvarnakuta Jantama, Sunthorn Kanchanatawee, Lonnie O. Ingram, Kaemwich Jantama

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Escherichia coli KJ122 was engineered to produce succinate from glucose using the wild type GalP for glucose uptake instead of the native phosphotransferase system (ptsI mutation). This strain ferments 10% (w/v) xylose poorly. Mutants were selected by serial transfers in AM1 mineral salts medium with 10% (w/v) xylose. Evolved mutants exhibited a similar improvement, co-fermentation of an equal mixture of xylose and glucose. One of these, AS1600a, produced 84.26±1.37 g/L succinate, equivalent to that produced by the parent (KJ122) strain from 10% glucose (85.46±1.78 g/L). AS1600a was sequenced and found to contain a mutation in galactose permease (GalP, G236D). Expressing the galP* mutation gene in KJ122ΔgalP resembled the xylose utilization phenotype of the mutant AS1600a. The strain AS1600a and KJ122ΔgalP (pLOI5746; galP*) also co-fermented a mixture of glucose, xylose, arabinose, and galactose in sugarcane bagasse hydrolysate for succinate production.

Keywords: xylose, furfural, succinat, sugarcane bagasse, E. coli

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Authors: Kim Hyekyoung, Au Yunkyung

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As media plays an increasingly important role in our lives, the age at which media usage begins is getting younger worldwide. Particularly, young children are exposed to media at an early age, making early childhood media literacy education an essential task. However, most existing early childhood media literacy education programs focus solely on teaching children how to use media, and practical implementation and application are challenging. Therefore, this study aims to develop a play-based early childhood media literacy education program utilizing topic-based media content and explore the potential application and impact of this program on young children's media literacy learning. Based on theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perceptions of media literacy education for preschool children, this study developed a media literacy education program for preschool children, considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication). To verify the effectiveness of the program, 20 preschool children aged 5 from C City M Kindergarten were chosen as participants, and the program was implemented from March 28th to July 4th, 2022, once a week for a total of 7 sessions. The program was developed based on Gallenstain's (2003) iterative learning model (participation-exploration-explanation-extension-evaluation). To explore the quantitative changes before and after the program, a repeated measures analysis of variance was conducted, and qualitative analysis was employed to examine the observed process changes. It was found that after the application of the education program, media literacy levels such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication significantly improved. The recursive learning-based early childhood media literacy education program developed in this study can be effectively applied to young children's media literacy education and help enhance their media literacy levels. In terms of observed process changes, it was confirmed that children learned about various topics, expressed their thoughts, and improved their ability to communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can contribute to empowering young children to safely and effectively utilize media in their media environment. The results of this study, exploring the potential application and impact of the recursive learning-based early childhood media literacy education program on young children's media literacy learning, demonstrated positive changes in young children's media literacy levels. These results go beyond teaching children how to use media and can help foster their ability to safely and effectively utilize media in their media environment. Additionally, to enhance young children's media literacy levels and create a safe media environment, diverse content and methodologies are needed, and the continuous development and evaluation of education programs should be conducted.

Keywords: young children, media literacy, recursive learning, education program

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Authors: Li Shuping, Shu Huaping, Yi Chaofan, Tao Jiang

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Equestrian practice is often considered having a unique effect on improving symptoms in children with autism. This study evaluated and measured the changes in daily behavior, morphological, physical function, and fitness indexes of two group children with autism by means of 12 weeks of equestrian and basketball exercises. 19 clinically diagnosed children with moderate/mild autism were randomly divided into equestrian group (9 children, age=10.11±1.90y) and basketball group (10 children, age=10.70±2.16y). Both the equestrian and basketball groups practiced twice a week for 45 to 60 minutes each time. Three scales, the Autism Behavior Checklist (ABC), the Childhood Autism Rating Scale (CARS) and the Clancy Autism Behavior Scale (CABS) were used to assess their human behavior and psychology. Four morphological, seven physical function and fitness indicators were measured to evaluate the effects of the two exercises on the children’s body. The evaluations were taken by every four weeks ( pre-exercise, the 4th week, the 8th week and 12th week (post exercise). The result showed that the total scores of ABC, CARS and CABS, the dimension scores of ABC on the somatic motor, language and life self-care obtained after exercise were significantly lower than those obtained before 12 week exercises in both groups. The ABC feeling dimension scores of equestrian group and ABC communication dimension score of basketball group were significantly lower,and The upper arm circumference, sitting forward flexion, 40 second sit-up, 15s lateral jump, vital capacity, and single foot standing of both groups were significantly higher than that of before exercise.. The BMI of equestrian group was significantly reduced. The handgrip strength of basketball group was significantly increased. In conclusion, both types of exercises could improve daily behavior, morphological, physical function, and fitness indexes of the children with autism. However, the behavioral psychological scores, body morphology and function indicators and time points were different in the middle and back of the two interventions.But the indicators and the timing of the improvement were different. To the group of equestrian, the improvement of the flexibility occurred at week 4, the improvement of the sensory perception, control and use their own body, and promote the development of core strength endurance, coordination and cardiopulmonary function occurred at week 8，and the improvement of core strength endurance, coordination and cardiopulmonary function occurred at week 12. To the group of basketball, the improvement of the hand strength, balance, flexibility and cardiopulmonary function occurred at week 4, the improvement of the self-care ability and language expression ability, and core strength endurance and coordination occurred at week 8, the improvement of the control and use of their own body and social interaction ability occurred at week 12. In comparison of the exercise effects, the equestrian exercise improved the physical control and application ability appeared earlier than that of basketball group. Basketball exercise improved the language expression ability, self-care ability, balance ability and cardiopulmonary function of autistic children appeared earlier than that of equestrian group.

Keywords: intervention, children with autism, equestrain, basketball

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Authors: John N. Idenyi, Hadimundeen Abdallah, Abigeal D. Adeyemi, Jonathan C. Eya

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Gut microbiomes play a significant role in the growth, metabolism, and health of fish. However, we know very little about the interactive effects of variations in dietary composition and temperature on rainbow trout gut microbiota. Exactly 288 rainbow trout weighing 45.6g ± 0.05 (average ± SD) were fed four isocaloric, isolipidic, and isonitrogenous diets comprising 40% crude protein and 20% crude lipid and formulated as 100 % animal-based protein (AP) and a blend of 50 fish oil (FO)/50 camelina oil (CO), 100 % AP and100 % CO, 100 % plant-based protein (PP) and a blend of 50FO/50CO or 100 % PP and 100 % CO in 14 or 18°C for 150 days. Gut content was analyzed using 16S rRNA gene and shotgun sequencing. The most abundant phyla identified regardless of diet were Tenericutes, Firmicutes, Proteobacteria, Spirochaetes, Bacteroidetes, and Actinobacteria, while Aeromonadaceae and Enterobacteriaceae were dominant families in 18°C. Moreover, gut microbes were dominated by genes relating to an amino acid, carbohydrate, fat, and energy metabolisms and influenced by temperature. The shared functional profiles for all the diets suggest that plant protein sources in combination with CO could be as good as the fish meal with 50/50 FO & CO in rainbow trout farming.

Keywords: aquafeed, aquaculture, microbiome, rainbow trout

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

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Authors: E. L. Albuquerque, U. L. Fulco, G. S. Ourique

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The focus of this work is on the numerical investigation of the charge transport properties of the de novo-designed alpha3 polypeptide, as well as in its variants, all of them probed by gene engineering. The theoretical framework makes use of a tight-binding model Hamiltonian, together with ab-initio calculations within quantum chemistry simulation. The alpha3 polypeptide is a 21-residue with three repeats of the seven-residue amino acid sequence Leu-Glu-Thr-Leu-Ala-Lys-Ala, forming an alpha–helical bundle structure. Its variants are obtained by Ala→Gln substitution at the e (5th) and g (7th) position, respectively, of the alpha3 polypeptide amino acid sequence. Using transmission electron microscopy and atomic force microscopy, it was observed that the alpha3 polypeptide and one of its variant do have the ability to form fibrous assemblies, while the other does not. Our main aim is to investigate whether or not the biased alpha3 polypeptide and its variants can be also identified by quantum charge transport measurements through current-voltage (IxV) curves as a pattern to characterize their fibrous assemblies. It was observed that each peptide has a characteristic current pattern, which may be distinguished by charge transport measurements, suggesting that it might be a useful tool for the development of biosensors.

Keywords: charge transport properties, electronic transmittance, current-voltage characteristics, biological sensor

Procedia PDF Downloads 661

Authors: Robert Birkholc

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One of the basic issues related to the creation of characters in media, such as literature and film, is the representation of the characters' thoughts, emotions, and perceptions. This paper is devoted to the social perspective (or the focalization) expressed in film narration. The aim of the paper is to show how social point of view of the hero –conditioned by his origin and the environment from which he comes– can be created by using non-verbal, purely audiovisual means of expression. The issue will be considered on the example of the little-known polish movie The Dancing Hawk (1977) by Grzegorz Królikiewicz, based on the novel by Julian Kawalec. The thesis of the paper is that the polish director uses a narrative figure, which is somewhat analogous to literary form of free indirect discourse. In literature, free indirect discourse is formally ‘spoken’ by the external narrator, but the narration is clearly filtered through the language and thoughts of the character. According to some scholars (such as Roy Pascal), the narrator in this form of speech does not cite the character's words, but uses his way of thinking and imitates his perspective – sometimes with a deep irony. Free indirect discourse is frequently used in Julian Kawalec’s novel. Through the linguistic stylization, the author tries to convey the socially determined perspective of a peasant who migrates to the big city after the Second World War. Grzegorz Królikiewicz expresses the same social experience by pure cinematic form in the adaptation of the book. Both Kawalec and Królikiewicz show the consequences of so-called ‘social advancement’ in Poland after 1945, when the communist party took over political power. On the example of the fate of the main character, Michał Toporny, the director presents the experience of peasants who left their villages and had to adapt to new, urban space. However, the paper is not focused on the historical topic itself, but on the audiovisual form of the movie. Although Królikiewicz doesn’t use frequently POV shots, the narration of The Dancing Hawk is filtered through the sensations of the main character, who feels uprooted and alienated in the new social space. The director captures the hero's feelings through very complex audiovisual procedures – high or low points of view (representing the ‘social position’), grotesque soundtrack, expressionist scenery, and associative editing. In this way, he manages to create the world from the perspective of a socially maladjusted and internally split subject. The Dancing Hawk is a successful attempt to adapt the subjective narration of the book to the ‘language’ of the cinema. Mieke Bal’s notion of focalization helps to describe ‘free indirect discourse’ as a transmedial figure of representing of the characters’ perceptions. However, the polysemiotic medium of the film also significantly transforms this figure of representation. The paper shows both the similarities and differences between literary and cinematic ‘free indirect discourse.’

Keywords: film and literature, free indirect discourse, social experience, subjective narration

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

Procedia PDF Downloads 124

Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: Nouredine Benouzza, Ahmed Hamida Boudinar, Azeddine Bendiabdellah

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An algorithm for Eccentricity Fault Detection (EFD) applied to a squirrel cage induction machine is proposed in this paper. This algorithm employs the behavior of the stator current spectral analysis and the localization of the Rotor Slot Harmonic (RSH) frequency to detect eccentricity faults in three phase induction machine. The RHS frequency once obtained is used as a key parameter into a simple developed expression to directly compute the eccentricity fault frequencies in the induction machine. Experimental tests performed for both a healthy motor and a faulty motor with different eccentricity fault severities illustrate the effectiveness and merits of the proposed EFD algorithm.

Keywords: squirrel cage motor, diagnosis, eccentricity faults, current spectral analysis, rotor slot harmonic

Procedia PDF Downloads 471