Search results for: feature extraction

Authors: Yelena Mazour-Matusevich, Jean-Robert Ancheta

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This study is based on more than fifteen years of experience of teaching a foreign language, in my case French, to the English-speaking students. It represents a qualitative research on foreign language learners’ reaction and their gains in terms of vocabulary and listening comprehension through repeatedly viewing foreign feature films with the original sountrack but without English subtitles. The initial idea emerged upon realization that the first challenge faced by my students when they find themselves in a francophone environment has been their lack of listening comprehension. Their inability to understand colloquial speech affects not only their academic performance, but their psychological health as well. To remedy this problem, I have designed and applied for many years my own teaching method based on one particular French film, exceptionally suited, for the reasons described in detail in the paper, for the intermediate-advanced level foreign language learners. This project, conducted together with my undergraduate assistant and mentoree J-R Ancheta, aims at showing how the paralinguistic features, such as characters’ facial expressions, settings, music, historical background, images provided before the actual viewing, etc., offer crucial support and enhance students’ listening comprehension. The study, based on students’ interviews, also offers special pedagogical techniques, such as ‘anticipatory’ vocabulary lists and exercises, drills, quizzes and composition topics that have proven to boost students’ performance. For this study, only the listening proficiency and vocabulary gains of the interviewed participants were assessed.

Keywords: comprehension, film, listening, subtitles, vocabulary

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Authors: J. C. Akan, F. I. Abdulrahman, Z. M. Chellube

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The aim of this study was to determine the levels of some organochlorine (o, p-DDE, p,p’-DDD, o,p’-DDD, p,p’-DDT, p,p’-DDT, α-BHC, γ-BHC, lindane, Endosulfan sulphate, dieldrin and aldrin and organophosphorus (Dichlorvos, Diazinon, Chlorpyrifos, fenitrothion and Fenitrothion) pesticide residues in the gills, liver, stomach, kidney and flesh of four fish species (Tilapia zilli, Clarias anguillaris Hetrotis niloticus and Oreochronmis niloticus) between the periods of September 2010 to October, 2011. Samples were collected from Kwantan turare in Lake Chad, Baga, Borno State, Nigeria. Extraction of the fish samples and de-fattening of the fish sample extracts were performed using standard procedures. Analysis of the fish samples for pesticide residues were carried out using Shimadzu GC/MS (GC – 17A), equipped with fluorescence detector. Large differences in the levels of pesticide residues were observed between tissues within each fish. The concentrations of all the organophosphorus pesticides were higher in the organs of Oreochronmis niloticus, while Hetrotis niloticus shows the lowest. For organochlorine pesticides, the organs of Tilapia zilli showed the highest concentrations, while Hetrotis niloticus shows the lowest. The highest pesticide concentrations were observed in gills and liver tissues of all the species of fish study, while the lowest concentrations were observed in flesh. Based on the above results, it can therefore be concluded that the concentrations of pesticide in the four fish species study did exceed the permissible limits set by FAO and FEPA.

Keywords: organochlorine, organophosphorus, pesticides, accumulation, fish, lake chad

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Authors: Francesco Scarpati

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Because of their long history, ranging from ancient times to the present day, European cities feature many historical layers, whose single identities are represented by traces surviving in the urban design. However, urban transformations, in particular, the ones that have been produced by the property speculation phenomena of the 20th century, often compromised the readability of these traces, resulting in a loss of the historical identities of the single layers. The purpose of this research is, therefore, a reflection on the theme of the reenactment of the historical memory in the stratified European contexts and on how contemporary architecture can help to reveal past signs of the cities. The research work starts from an analysis of a series of emblematic examples that have already provided an original solution to the described problem, going from the architectural detail scale to the urban and landscape scale. The results of these analyses are then applied to the case study of the city of Naples, as an emblematic example of a stratified city, with an ancient Greek origin; a city where it is possible to read most of the traces of its transformations. Particular consideration is given to the trace of the medieval walls of the city, which a long time ago clearly divided the city itself from the outer fields, and that is no longer readable at the current time. Finally, solutions and methods of intervention are proposed to ensure that the trace of the walls, read as a boundary, can be revealed through the contemporary project.

Keywords: contemporary project, historic memory, historic urban contexts, medieval walls, naples, stratified cities, urban traces

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Authors: Ogbonnaya O. Iroanya, Samson T. Fakorede, Osamudiamen J. Edosa, Hadiat A. Azeez

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The human mitochondrial DNA (mtDNA) is about 17 kbp circular DNA fragments found within the mitochondria together with smaller fragments of 1200 bp known as the control region. Knowledge of variation within populations has been employed in forensic and molecular anthropology studies. The study was aimed at investigating the polymorphic nature of the two hypervariable segments (HVS) of the mtDNA, i.e., HVS1 and HVS2, and to determine the haplogroup distribution among individuals resident in Lagos, Southwestern Nigeria. Peripheral blood samples were obtained from sixty individuals who are not related maternally, followed by DNA extraction and amplification of the extracted DNA using primers specific for the regions under investigation. DNA amplicons were sequenced, and sequenced data were aligned and compared to the revised Cambridge Reference Sequence (rCRS) GenBank Accession number: NC_012920.1) using BioEdit software. Results obtained showed 61 and 52 polymorphic nucleotide positions for HVS1 and HVS2, respectively. While a total of three indels mutation were recorded for HVS1, there were seven for HVS2. Also, transition mutations predominate nucleotide change observed in the study. Genetic diversity (GD) values for HVS1 and HVS2 were estimated to be 84.21 and 90.4%, respectively, while random match probability was 0.17% for HVS1 and 0.89% for HVS2. The study also revealed mixed haplogroups specific to the African (L1-L3) and the Eurasians (U and H) lineages. New polymorphic sites obtained from the study are promising for human identification purposes.

Keywords: hypervariable region, indels, mitochondrial DNA, polymorphism, random match probability

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Authors: Junjie Wu, Hongjuan Hou, Eric Hu, Yongping Yang

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Solar aided power generation (SAPG) technology has been proven as an efficient way to make use of solar energy for power generation purpose. In an SAPG plant, a solar field consisting of parabolic solar collectors is normally used to supply the solar heat in order to displace the high pressure/temperature extraction steam. To understand the performance of such a SAPG plant, a new simulation model was developed by the authors recently, in which the boiler was treated, as a series of heat exchangers unlike other previous models. Through the simulations using the new model, it was found the outlet properties of reheated steam, e.g. temperature, would decrease due to the introduction of the solar heat. The changes make the (lower stage) turbines work under off-design condition. As a result, the whole plant’s performance may not be optimal. In this paper, the second solar filed was proposed to increase the inlet temperature of steam to be reheated, in order to bring the outlet temperature of reheated steam back to the designed condition. A 600MW SAPG plant was simulated as a case study using the new model to understand the impact of the second solar field on the plant performance. It was found in the study, the 2nd solar field would improve the plant’s performance in terms of cycle efficiency and solar-to-electricity efficiency by 1.91% and 6.01%. The solar-generated electricity produced by per aperture area under the design condition was 187.96W/m2, which was 26.14% higher than the previous design.

Keywords: solar-aided power generation system, off-design performance, coal-saving performance, boiler modelling, integration schemes

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Authors: N. H. Harun, A. S. Abdul Nasir, M. Y. Mashor, R. Hassan

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Leukaemia is a blood cancer disease that contributes to the increment of mortality rate in Malaysia each year. There are two main categories for leukaemia, which are acute and chronic leukaemia. The production and development of acute leukaemia cells occurs rapidly and uncontrollable. Therefore, if the identification of acute leukaemia cells could be done fast and effectively, proper treatment and medicine could be delivered. Due to the requirement of prompt and accurate diagnosis of leukaemia, the current study has proposed unsupervised pixel segmentation based on clustering algorithm in order to obtain a fully segmented abnormal white blood cell (blast) in acute leukaemia image. In order to obtain the segmented blast, the current study proposed three clustering algorithms which are k-means, fuzzy c-means and moving k-means algorithms have been applied on the saturation component image. Then, median filter and seeded region growing area extraction algorithms have been applied, to smooth the region of segmented blast and to remove the large unwanted regions from the image, respectively. Comparisons among the three clustering algorithms are made in order to measure the performance of each clustering algorithm on segmenting the blast area. Based on the good sensitivity value that has been obtained, the results indicate that moving k-means clustering algorithm has successfully produced the fully segmented blast region in acute leukaemia image. Hence, indicating that the resultant images could be helpful to haematologists for further analysis of acute leukaemia.

Keywords: acute leukaemia images, clustering algorithms, image segmentation, moving k-means

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Premjit K. Sanjram, Gagan Jakhotiya, Apoorv Goyal, Shanu Shukla

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In psychological research, laboratory experiments often face the trade-off issue between experimental control and mundane realism. With the advent of Immersive Virtual Environment Technology (IVET), this issue seems to be at bay. However there is a growing challenge within the IVET itself to design and develop system or software that captures the psychological phenomenon of everyday lives. One such phenomena that is of growing interest is ‘media-multitasking’ To aid laboratory researches in media-multitasking this paper introduces Query Task Modulator (QTM), a computerized experimentation system to study media-multitasking behavior in a controlled laboratory environment. The system provides a computerized platform in conducting an experiment for experimenters to study media-multitasking in which participants will be involved in a query task. The system has Instant Messaging, E-mail, and Voice Call features. The answers to queries are provided on the left hand side information panel where participants have to search for it and feed the information in the respective communication media blocks as fast as possible. On the whole the system will collect multitasking behavioral data. To analyze performance there is a separate output table that records the reaction times and responses of the participants individually. Information panel and all the media blocks will appear on a single window in order to ensure multi-modality feature in media-multitasking and equal emphasis on all the tasks (thus avoiding prioritization to a particular task). The paper discusses the development of QTM in the light of current techniques of studying media-multitasking.

Keywords: experimentation system, human performance, media-multitasking, query-task

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Authors: Priyanka Gupta, Bipin Kumar

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Recent developments in smart materials motivate researchers to create novel textile products for innovative and functional applications, which have several potential uses beyond the conventional. This study investigates the memory behavior of shape memory filaments integrated into a knitted textile structure. The research advances the knowledge of how these intelligent materials respond within textile structures. This integration may also open new avenues for developing smart fabrics with unique sensing and actuation capabilities. A shape memory filament and polyester yarn were knitted to produce a shape memory knitted fabric (SMF). Thermo-mechanical tensile test was carried out to quantify the memory behavior of SMF under different conditions. The experimental findings demonstrate excellent shape recovery (100%) and shape fixity up to 88% at different strains (20% and 60%) and temperatures (30 ℃ and 50 ℃). Experimental results reveal that memory filament behaves differently in a fabric structure than in its pristine condition at various temperatures and strains. The cycle test of SMF under different thermo-mechanical conditions indicated complete shape recovery with an increase in shape fixity. So, the utterly recoverable textile structure was achieved after a few initial cycles. These intelligent textiles are beneficial for the development of novel, innovative, and functional fabrics like elegant curtains, pressure garments, compression stockings, etc. In addition to fashion and medical uses, this unique feature may also be leveraged to build textile-based sensors and actuators.

Keywords: knitting, memory filament, shape memory, smart textiles, thermo-mechanical cycle

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Authors: M. Al-Majidi, A. Lampropoulos, A. Cundy

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Geopolymer (cement-free) concrete is the most promising green alternative to ordinary Portland cement concrete and other cementitious materials. While a range of different geopolymer concretes have been produced, a common feature of these concretes is heat curing treatment which is essential in order to provide sufficient mechanical properties in the early age. However, there are several practical issues with the application of heat curing in large-scale structures. The purpose of this study is to develop cement-free concrete without heat curing treatment. Experimental investigations were carried out in two phases. In the first phase (Phase A), the optimum content of water, polycarboxylate based superplasticizer contents and potassium silicate activator in the mix was determined. In the second stage (Phase B), the effect of ground granulated blast furnace slag (GGBFS) incorporation on the compressive strength of fly ash (FA) and Slag based geopolymer mixtures was evaluated. Setting time and workability were also conducted alongside with compressive tests. The results showed that as the slag content was increased the setting time was reduced while the compressive strength was improved. The obtained compressive strength was in the range of 40-50 MPa for 50% slag replacement mixtures. Furthermore, the results indicated that increment of water and superplasticizer content resulted to retarding of the setting time and slight reduction of the compressive strength. The compressive strength of the examined mixes was considerably increased as potassium silicate content was increased.

Keywords: fly ash, geopolymer, potassium silicate, slag

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Authors: Zohreh Fallah, Edward P. L. Roberts

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One of the big challenges for produced water treatment is removing oil from water in the form of emulsified droplets which are not easily separated. An attractive approach is adsorption, as it is a simple and effective process. However, adsorbents must be regenerated in order to make the process cost effective. Several sorbents have been tested for treating oily wastewater. However, some issues such as high energy consumption for activated carbon thermal regeneration have been reported. Due to their significant electrical conductivity, Graphite Intercalation Compounds (GIC) were found to be suitable to be regenerated electrochemically. They are non-porous materials with low surface area and fast adsorptive capacity which are useful for removal of low concentration of organics. An innovative adsorption/regeneration process has been developed at the University of Manchester in which adsorption of organics are done by using a patented GIC adsorbent coupled with subsequent electrochemical regeneration. The oxidation of adsorbed organics enables 100% regeneration so that the adsorbent can be reused over multiple adsorption cycles. GIC adsorbents are capable of removing a wide range of organics and pollutants; however, no comparable report is available for removal of emulsified oil in produced water using abovementioned process. In this study the performance of this technology for the removal of emulsified oil in wastewater was evaluated. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for both real produced water and model emulsions. The amount of oil in wastewater was measured by using the toluene extraction/fluorescence analysis before and after adsorption and electrochemical regeneration cycles. It was found that oil in water emulsion could be successfully treated by the treatment process and More than 70% of oil was removed.

Keywords: adsorption, electrochemical regeneration, emulsified oil, produced water

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Cora Bulmău

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Soil polluted with hydrocarbons spills is a major global concern today. As a response to this issue, our experimental study tries to put in evidence the option to choose for one environmentally friendly method: use of the biochar, despite to a classical procedure; incineration of contaminated soil. Biochar represents the solid product obtained through the pyrolysis of biomass, its additional use being as an additive intended to improve the quality of the soil. The positive effect of biochar addition to soil is represented by its capacity to adsorb and contain petroleum products within its pores. Taking into consideration the capacity of the biochar to interact with organic contaminants, the purpose of the present study was to experimentally establish the effects of the addition of wooden biomass-derived biochar on a soil contaminated with oil. So, the contaminated soil was amended with biochar (10%) produced by pyrolysis in different operational conditions of the thermochemical process. After 25 days, the concentration of petroleum hydrocarbons from soil treated with biochar was measured. An analytical method as Soxhlet extraction was adopted to estimate the concentrations of total petroleum products (TPH) in the soil samples: This technique was applied to contaminated soil, also to soils remediated by incineration/adding biochar. The treatment of soil using biochar obtained from pyrolysis of the Birchwood led to a considerable decrease in the concentrations of petroleum products. The incineration treatments conducted under experimental stage to clean up the same soil, contaminated with petroleum products, involved specific parameters: temperature of about 600°C, 800°C and 1000°C and treatment time 30 and 60 minutes. The experimental results revealed that the method using biochar has registered values of efficiency up to those of all incineration processes applied for the shortest time.

Keywords: biochar, biomass, remediaton, soil, TPH

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Authors: Tianhao Zhang, Cen Chen, Dawei Cheng, Yuqi Liang, Yuanyuan Liang

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Dealing with anomalies is a crucial preprocessing step for multivariate time series prediction. However, existing methods that separate anomaly preprocessing and model training into two stages have certain limitations. Specifically, these methods fail to leverage auxiliary information necessary to distinguish latent anomalies related to spatiotemporal factors during the preprocessing stage. Instead, they solely rely on data distribution for detection which may lead to incorrect processing of many samples that are beneficial for training. To address this, we propose STTS-EAD, an end-to-end method that seamlessly integrates anomaly detection into the training process of multivariate time series forecasting and aims to improve Spatio-Temporal learning based Time Series prediction via Embedded Anomaly Detection. Our proposed STTS-EAD leverages spatio-temporal information for forecasting and anomaly detection, with the two parts alternately executed and optimized for each other. To the best of our knowledge, STTS-EAD is the first to integrate anomaly detection and forecasting tasks in the training phase for improving the accuracy of multivariate time series forecasting. Extensive experiments on a public stock dataset and two real-world sales datasets from a renowned coffee chain enterprise show that our proposed method can effectively process detected anomalies in the training stage to improve forecasting performance in the inference stage and significantly outperform baselines.

Keywords: multivariate time series, anomaly detection, time series forecasting, spatiotemporal feature learning

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Authors: Haruo Okabayashi

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The mutual understanding in conversation is very important for human relations. This study investigates the mental function of the formation of mutual understanding between two people in conversation using the embodied approach. Forty people participated in this study. They are divided into pairs randomly. Four conversation situations between two (make/listen to fun or pleasant talk, make/listen to regrettable talk) are set for four minutes each, and the finger plethysmogram (200 Hz) of each participant is measured. As a result, the attractors of the participants who reported “I did not understand my partner” show the collapsed shape, which means the fluctuation of their rhythm is too small to match their partner’s rhythm, and their cross correlation is low. The autonomic balance of both persons tends to resonate during conversation, and both LLEs tend to resonate, too. In human history, in order for human beings as weak mammals to live, they may have been with others; that is, they have brought about resonating characteristics, which is called self-organization. However, the resonant feature sometimes collapses, depending on the lifestyle that the person was formed by himself after birth. It is difficult for people who do not have a lifestyle of mutual gaze to resonate their biological signal waves with others’. These people have features such as anxiety, fatigue, and confusion tendency. Mutual understanding is thought to be formed as a result of cooperation between the features of self-organization of the persons who are talking and the lifestyle indicated by mutual gaze. Such an entanglement phenomenon is called a nonlinear relation. By this research, it is found that the formation of mutual understanding is expressed by the rhythm of a biological signal showing a nonlinear relationship.

Keywords: embodied approach, finger plethysmogram, mutual understanding, nonlinear phenomenon

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Authors: Kenia Martínez, Geniel Talavera, Juan Alonso

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Moringa oleifera is a plant containing many nutrients that are mostly concentrated within the leaves. Commonly, the separation process of these nutrients involves solid-liquid extraction followed by evaporation and drying to obtain a concentrated extract, which is rich in proteins, vitamins, carbohydrates, and other essential nutrients that can be used in the food industry. In this work, three drying methods were used, which involved very different temperature and pressure conditions, to evaluate the effect of each method on the vitamin C content and the antioxidant efficiency of the extracts. Solid-liquid extractions of Moringa leaf (LE) were carried out by employing an ethanol solution (35% v/v) at 50 °C for 2 hours. The resulting extracts were then dried i) in a convective oven (CO) at 100 °C and at an atmospheric pressure of 750 mbar for 8 hours, ii) in a vacuum evaporator (VE) at 50 °C and at 300 mbar for 2 hours, and iii) in a freeze-drier (FD) at -40 °C and at 0.050 mbar for 36 hours. The antioxidant capacity (EC₅₀, mg solids/g DPPH) of the dry solids was calculated by the free radical inhibition method employing DPPH˙ at 517 nm, resulting in a value of 2902.5 ± 14.8 for LE, 3433.1 ± 85.2 for FD, 3980.1 ± 37.2 for VE, and 8123.5 ± 263.3 for CO. The calculated antioxidant efficiency (AE, g DPPH/(mg solids·min)) was 2.920 × 10^-5 for LE, 2.884 × 10^-5 for FD, 2.512 × 10^-5 for VE, and 1.009 × 10^-5 for CO. Further, the content of vitamin C (mg/L) determined by HPLC was 59.0 ± 0.3 for LE, 49.7 ± 0.6 for FD, 45.0 ± 0.4 for VE, and 23.6 ± 0.7 for CO. The results indicate that the convective drying preserves vitamin C and antioxidant efficiency to 40% and 34% of the initial value, respectively, while vacuum drying to 76% and 86%, and freeze-drying to 84% and 98%, respectively.

Keywords: antioxidant efficiency, convective drying, freeze-drying, Moringa oleifera, vacuum drying, vitamin C content

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Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

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Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

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Authors: Harold Mauricio Díaz-Vargas, Cristian Alfonso Jimenez-Castaño, David Augusto Cárdenas-Peña, Guillermo Alberto Ortiz-Gómez, Alvaro Angel Orozco-Gutierrez

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Precise identification of the nerves is a crucial task performed by anesthesiologists for an effective Peripheral Nerve Blocking (PNB). Now, anesthesiologists use ultrasound imaging equipment to guide the PNB and detect nervous structures. However, visual identification of the nerves from ultrasound images is difficult, even for trained specialists, due to artifacts and low contrast. The recent advances in deep learning make neural networks a potential tool for accurate nerve segmentation systems, so addressing the above issues from raw data. The most widely spread U-Net network yields pixel-by-pixel segmentation by encoding the input image and decoding the attained feature vector into a semantic image. This work proposes a conditioning approach and encoder pre-training to enhance the nerve segmentation of traditional U-Nets. Conditioning is achieved by the one-hot encoding of the kind of target nerve a the network input, while the pre-training considers five well-known deep networks for image classification. The proposed approach is tested in a collection of 619 US images, where the best C-UNet architecture yields an 81% Dice coefficient, outperforming the 74% of the best traditional U-Net. Results prove that pre-trained models with the conditional approach outperform their equivalent baseline by supporting learning new features and enriching the discriminant capability of the tested networks.

Keywords: nerve segmentation, U-Net, deep learning, ultrasound imaging, peripheral nerve blocking

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Authors: Guilherme Henrique Gabriel, Lucí Hidalgo Nunes

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An important feature of rainfall regimes is the variability, which is subject to the atmosphere’s general and regional dynamics, geographical position and relief. Despite being inherent to the climate system, it can harshly impact virtually all human activities. In turn, global climate change has the ability to significantly affect smaller-scale rainfall regimes by altering their current variability patterns. In this regard, it is useful to know if regional climates are changing over time and whether it is possible to link these variations to climate change trends observed globally. This study is part of an international project (Metropole-FAPESP, Proc. 2012/51876-0 and Proc. 2015/11035-5) and the objective was to identify and evaluate possible changes in rainfall behavior in the state of São Paulo, southeastern Brazil, using rainfall data from 79 rain gauges for the last forty years. Cluster analysis and gamma distribution parameters were used for evaluating spatial and temporal trends, and the outcomes are presented by means of geographic information systems tools. Results show remarkable changes in rainfall distribution patterns in São Paulo over the years: changes in shape and scale parameters of gamma distribution indicate both an increase in the irregularity of rainfall distribution and the probability of occurrence of extreme events. Additionally, the spatial outcome of cluster analysis along with the gamma distribution parameters suggest that changes occurred simultaneously over the whole area, indicating that they could be related to remote causes beyond the local and regional ones, especially in a current global climate change scenario.

Keywords: climate change, cluster analysis, gamma distribution, rainfall

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Authors: Muhammad S. Sajid, A. Iqbal, A. Kausar, M. Jawad-ul-Hassan, Z. Iqbal, Hafiz M. Rizwan, M. Saqib

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Among the ixodid ticks, species of genus Hyalomma are of prime importance as they can survive in harsh conditions better than those of other species. Similarly, among various tick-borne pathogens, Theileria (T.) annulata, the causative agent of tropical theileriosis in large ruminants, is responsible for reduced productivity and ultimately substantial economic losses due to morbidity and mortality. The present study was planned to screening of vector ticks through molecular techniques for determination of tick-borne theileriosis in district Toba Tek Singh (T. T. Singh), Punjab, Pakistan. For this purpose, among the collected ticks (n = 2252) from livestock and their microclimate, Hyalomma spp. were subjected to dissection for procurement of salivary glands (SGs) and formation of pool (averaged 8 acini in each pool). Each pool of acini was used for DNA extraction, quantification and primer-specific amplification of 18S rRNA of Theileria (T.) annulata. The amplicons were electrophoresed using 1.8% agarose gel following by imaging to identify the band specific for T. annulata. For confirmation, the positive amplicons were subjected to sequencing, BLAST analysis and homology search using NCBI software. The number of Theileria-infected acini was significantly higher (P < 0.05) in female ticks vs male ticks, infesting ticks vs questing ticks and riverine-collected vs non-riverine collected. The data provides first attempt to quantify the vectoral capacity of ixodid ticks in Pakistan for T. annulata which can be helpful in estimation of risk analysis of theileriosis to the domestic livestock population of the country.

Keywords: Hyalomma anatolicum, ixodids, PCR, Theileria annulata

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Authors: Baoshan Wang

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The present study investigates how music theory has developed across different countries due to their diverse histories, religions, and cultural differences. It is unknown how these various factors may contribute to differences in music theory across countries. Therefore, we examine the differences between China and Greece, which have developed unique music theories over time. Specifically, our analysis looks at musical notation and scales. For example, Tonal music originates from Greece, which harbors quite complex notation and scaling. There exist seven notes in each scale within seven modes of scales. Each mode of the diatonic scale has a unique temperament, two of which are most commonly used in modern music. In contrast, we find that Chinese music has only five notes in its scales. Interestingly, a unique feature of Chinese music theory is that there is no half-step, resulting in a highly divergent and culture-specific sound. Fascinatingly, these differences may arise from the contrasting ways that Western and Eastern musicians perceive music. While Western musicians tend to believe in music “without borders,” Eastern musicians generally embrace differing perspectives. Yet, the vast majority of colleges or music conservatories teach the borderless theory of Western music, which renders the music educational system incomplete. This is critically important because learning music is not simply a profession for musicians. Rather, it is an intermediary to facilitate understanding and appreciation for different countries’ cultures and religions. Education is undoubtedly the optimal mode to promote different countries’ music theory so people across the world can learn more about music and, in turn, each other. Even though Western music theory is predominantly taught, it is crucial we also pursue an understanding of other countries’ music because their unique aspects contribute to the systematic completeness of Music Theory in its entirety.

Keywords: culture, development, music theory, music history, religion, western music

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Authors: Nour Daoud

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Patriarchy continues to thrive in Jordan where male-controlled values are still entrenched in a society that is suffering from upsetting percentages of Gender-based Violence (GBV). This paper is a systematic review of the literature with an attempt to evaluate and interpret all available research evidence relevant to determining the extent to which patriarchy contributes to the occurrence, re-occurrence, and continuation of GBV in Jordan. Twenty-one (21) full-text articles were selected for the in-depth review due to meeting the established criteria for inclusion. 81 percent of articles included primary data while 19 percent included secondary data. Analysis of data was based on a specific extraction form that was developed using the ‘Excel’ to respond to the main goal of the paper. Interpretation of data was in light of the theorization of different feminism schools on the relationship between patriarchy and gender-based violence. Findings show that 33 percent of the selected articles affirm that the patriarchal standpoint best explains the role of patriarchy in the incidence of gender-based violence in Jordan under its three main themes (Honor-based Violence, Intimate Partner Violence and Street Harassment). Apart from the limited number of articles that were found debating this argument and the low percentage of articles that acknowledged the role of patriarchy in the incidence of gender-based violence in Jordan, this paper breaks the ice to implement future empirical studies on this subject. Also, it is an invitation for all Jordanian women to unite their efforts in order to eradicate all forms of victimization against them.

Keywords: honor-based violence, intimate partner violence, middle-east, street harassment

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Authors: Mounia El Jaouhari, Mira Goral, Samir Diouny

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Introduction: Previous research has indicated that language impairments are recognized as a feature of many neurodegenerative disorders, including non-language-led dementia subtypes such as Alzheimer´s disease (AD). In this preliminary study, the focal aim is to quantify the semantic content of naming and connected speech samples of Moroccan patients diagnosed with AD using two tasks taken from the culturally adapted and validated Moroccan version of the Boston Diagnostic Aphasia Examination. Methods: Five individuals with AD and five neurologically healthy individuals matched for age, gender, and education will participate in the study. Participants with AD will be diagnosed on the basis of the Moroccan version of the Diagnostic and Statistial Manual of Mental Disorders (DSM-4) screening test, the Moroccan version of the Mini Mental State Examination (MMSE) test scores, and neuroimaging analyses. The participants will engage in two tasks taken from the MDAE-SF: 1) Picture description and 2) Naming. Expected findings: Consistent with previous studies conducted on English speaking AD patients, we expect to find significant word production and retrieval impairments in AD patients in all measures. Moreover, we expect to find category fluency impairments that further endorse semantic breakdown accounts. In sum, not only will the findings of the current study shed more light on the locus of word retrieval impairments noted in AD, but also reflect the nature of Arabic morphology. In addition, the error patterns are expected to be similar to those found in previous AD studies in other languages.

Keywords: alzheimer's disease, anomia, connected speech, semantic impairments, moroccan arabic

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Authors: Jacintha Menezes, Ramalingam Dharmalingam, Palaiahnakote Shivakumara

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In the recent years, Omani acid lime cultivation and production has been affected by Citrus greening or Huanglongbing (HLB) disease. HLB disease is one of the most destructive diseases for citrus, with no remedies or countermeasures to stop the disease. Currently used Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA) HLB detection tests require lengthy and labor-intensive laboratory procedures. Furthermore, the equipment and staff needed to carry out the laboratory procedures are frequently specialized hence making them a less optimal solution for the detection of the disease. The current research uses hyperspectral imaging technology for automatic detection of citrus trees with HLB disease. Omani citrus tree leaf images were captured through portable Specim IQ hyperspectral camera. The research considered healthy, nutrition deficient, and HLB infected leaf samples based on the Polymerase chain reaction (PCR) test. The highresolution image samples were sliced to into sub cubes. The sub cubes were further processed to obtain RGB images with spatial features. Similarly, RGB spectral slices were obtained through a moving window on the wavelength. The resized spectral-Spatial RGB images were given to Convolution Neural Networks for deep features extraction. The current research was able to classify a given sample to the appropriate class with 92.86% accuracy indicating the effectiveness of the proposed techniques. The significant bands with a difference in three types of leaves are found to be 560nm, 678nm, 726 nm and 750nm.

Keywords: huanglongbing (HLB), hyperspectral imaging (HSI), · omani citrus, CNN

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Authors: S. B. Bhandare, K. S. Laddha

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Podphyllum hexandrum belonging to family berberidaceae has gained attention in phytochemical and pharmacological research as it shows excellent anticancer activity and has been used in treatment of skin diseases, sunburns and radioprotection. Chemically it contains lignans and flavonoids such as kaempferol, quercetin and their glycosides. Objective: To isolate and identify Kaempferol and Quercetin from Podophyllum rhizome. Method: The powdered rhizome of Podophyllum hexandrum was subjected to soxhlet extraction with methanol. This methanolic extract is used to obtain podophyllin. Podohyllin was extracted with ethyl acetate and this extract was then concentrated and subjected to column chromatography to obtain purified kaempferol and quercetin. Result: Isolated kaempferol, quercetin were light yellow and dark yellow in colour respectively. TLC of the isolated compounds was performed using chloroform: methanol (9:1) which showed single band on silica plate at Rf 0.6 and 0.4 for kaempferol and quercetin. UV spectrometric studies showed UV maxima (methanol) at 259, 360 nm and 260, 370 nm which are identical with standard kaempferol and quercetin respectively. Both IR spectra exhibited prominent absorption bands for free phenolic OH at 3277 and 3296.2 cm-1 and for conjugated C=O at 1597 and 1659.7 cm-1 respectively. The mass spectrum of kaempferol and quercetin showed (M+1) peak at m/z 287 and 303.09 respectively. 1H NMR analysis of both isolated compounds exhibited typical four-peak pattern of two doublets at δ 6.86 and δ 8.01 which was assigned to H-3’,5’ and H-2’,6’ respectively. Absence of signals less than δ 6.81 in the 1H NMR spectrum supported the aromatic nature of compound. Kaempferol and Quercetin showed 98.1% and 97% purity by HPLC at UV 370 nm. Conclusion: Easy and simple method for isolation of Kaempferol and Quercetin was developed and their structures were confirmed by UV, IR, NMR and mass studies. Method has shown good reproducibility, yield and purity.

Keywords: flavonoids, kaempferol, podophyllum rhizome, quercetin

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Authors: Adrien Pyskir, Manuel Collet, Zoran Dimitrijevic, Claude-Henri Lamarque

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During the last decades, great efforts have been made to reduce acoustic and vibrational disturbances in transportations, as it has become a key feature for comfort. Today, isolation and design have neutralized most of the troublesome vibrations, so that cars are quieter and more comfortable than ever. However, some problems remain unsolved, in particular concerning low-frequency isolation and the frequency-dependent stiffening of materials like rubber. To sum it up, a balance has to be found between a high static stiffness to sustain the vibration source’s mass, and low dynamic stiffness, as wideband as possible. Systems meeting these criteria are yet to be designed. We thus investigated solutions inspired by metamaterials to control efficiently low-frequency wave propagation. Structures exhibiting a negative Poisson ratio, also called auxetic structures, are known to influence the propagation of waves through beaming or damping. However, their stiffness can be quite peculiar as well, as they can present regions of zero stiffness on the stress-strain curve for compression. In addition, auxetic materials can be easily adapted in many ways, inducing great tuning potential. Using finite element software COMSOL Multiphysics, a resonant design has been tested through statics and dynamics simulations. These results are compared to experimental results. In particular, the bandgaps featured by these structures are analyzed as a function of design parameters. Great stiffness properties can be observed, including low-frequency dynamic stiffness loss and broadband transmission loss. Such features are very promising for practical isolation purpose, and we hope to adopt this kind of metamaterial into an effective industrial damper.

Keywords: auxetics, metamaterials, structural dynamics, vibration isolation

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Authors: Carolyn Whyte, Tina Halai, Sonita Koshal

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Aim: There are many methods available to assess the potential difficulty of third molar surgery. This study investigated various factors to assess whether they had a bearing on the difficulties encountered. Study design: A retrospective study was completed of 62 single mandibular third molar teeth removed under day case general anaesthesia between May 2016 and August 2016 by 3 consultant oral surgeons. Method: Data collection was by examining the OPG radiographs of each tooth and recording the necessary data. This was depth of impaction, angulation, bony impaction, point of application in relation to second molar, root morphology, Pell and Gregory classification and Winters Lines. This was completed by one assessor and verified by another. Information on medical history, anxiety, ethnicity and age were recorded. Case notes and surgical entries were examined for any difficulties encountered. Results: There were 5 cases which encountered surgical difficulties which included fracture of root apices (3) which were left in situ, prolonged bleeding (1) and post-operative numbness >6 months(1). Four of the 5 cases had Pell and Gregory classification as (B) where the occlusal plane of the impacted tooth is between the occlusal plane and the cervical line of the adjacent tooth. 80% of cases had the point of application as either coronal or apical one third (1/3) in relation to the second molar. However, there was variability in all other aspects of assessment in predicting difficulty of removal. Conclusions: Of the cases which encountered difficulties they all had at least one predictor of potential complexity but these varied case by case.

Keywords: impaction, mandibular third molar, radiographic assessment, surgical removal

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Authors: Kyung-Tae Lee, Li Li Wang, Kwang-Woo Jung, Yong-Sun Bahn

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Microtubules are involved in mechanical support, cytoplasmic organization as well as in a number of cellular processes by interacting with diverse microtubule-associated proteins (MAPs), such as plus-end tracking proteins, motor proteins, and tubulin-folding cofactors. A common feature of these proteins is the presence of a cytoskeleton-associated protein-glycine-rich (CAP-Gly) domain, which is evolutionarily conserved and generally considered to bind to α-tubulin to regulate functions of microtubules. However, there has been a dearth of research on CAP-Gly proteins in fungal pathogens, including Cryptococcus neoformans, which causes fatal meningoencephalitis globally. In this study, we identified five CAP-Gly proteins encoding genes in C. neoformans. Among these, Cgp1, encoded by CNAG_06352, has a unique domain structure that has not been reported before in other eukaryotes. Supporting the role of Cpg1 in microtubule-related functions, we demonstrate that deletion or overexpression of CGP1 alters cellular susceptibility to thiabendazole, a microtubule destabilizer, and Cgp1 is co-localized with cytoplasmic microtubules. Related to the cellular functions of microtubules, Cgp1 also governs maintenance of membrane stability and genotoxic stress responses. Furthermore, we demonstrate that Cgp1 uniquely regulates sexual differentiation of C. neoformans with distinct roles in the early and late stage of mating. Our domain analysis reveals that the CAP-Gly domain plays major roles in all the functions of Cgp1. Finally, the cgp1Δ mutant is attenuated in virulence. In conclusion, this novel CAP-Gly protein, Cgp1, has pleotropic roles in regulating growth, stress responses, differentiation and pathogenicity of C. neoformans.

Keywords: human fungal pathogen, CAP-Glycine protein, microtubule, meningoencephalitis

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Authors: Mahmoud S Gewaily, Atif Hasan, Mohamed Kassab, Ali A. Mansour

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The current study was carried out on the nose of seventeenth healthy adult camels. Specimens were collected from slaughter houses then fixed, dissected and photographed. For ultra structural studies, fresh samples were fixed in different fixatives and prepared for examination by light, scanning and electron microscopes. Grossly, nose of the camel had narrow nostrils, slit like in outline. In the nasal cavity, the nasal vestibule was narrow and has scanty dorsal and lateral cartilaginous support. The Nasal conchae (dorsal, middle and ventral) enclosed the dorsal, middle conchal sinuses and no ventral conchal sinus; instead there was recess and bull a. The ethmoidal conchae (8 in number) were noticeably fewer than in the other domestic animals like ox and horse. The olfactory mucosa was restricted to a small area covering the caudal parts of the ethmoidal conchae. The lining epithelium of the nasal cavity changes gradually from stratified squamous epithelium in the nasal vestibule to pseudo stratified columnar ciliated in the respiratory region and finally, olfactory epithelium covering the caudal parts of the ethmoidal conchae. In the dromedary camel, a special feature was the presence of dense and relatively long hair covering the nostrils and the rostral part of the nasal vestibule. In conclusion, the anatomical features of the nose of the dromedary camel, especially in its rostral parts enable this animal to breathe properly in the sandy dry weather.

Keywords: camel nose, anatomy, dromedary camel, nasal vestibule

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Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

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In this work, we use machine learning and novel data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. To the best of our knowledge, this is the first work to apply modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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