Search results for: gene name recognition

Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

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During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: Artificial intelligence, depression detection, facial emotion recognition, natural language processing, mental disorder.

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores, Valentin Soloiu

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This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

Keywords: Biosensors, electromyography, Artificial Neural Network, Arduino, drone flight control, machine learning.

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Authors: M. A. Okezue, K. L. Clase, S. R. Byrn, P. Shivanand

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Medicines regulatory authorities expect pharmaceutical companies and contract research organizations to seek ways to certify that their laboratory control measurements are reliable. Establishing and maintaining laboratory quality standards are essential in ensuring the accuracy of test results. ‘ISO/IEC 17025:2017’ and ‘WHO Good Practices for Pharmaceutical Quality Control Laboratories (GPPQCL)’ are two quality standards commonly employed in developing laboratory quality systems. A review was conducted on the two standards to elaborate on areas on convergence and divergence. The goal was to understand how differences in each standard's requirements may influence laboratories' choices as to which document is easier to adopt for quality systems. A qualitative review method compared similar items in the two standards while mapping out areas where there were specific differences in the requirements of the two documents. The review also provided a detailed description of the clauses and parts covering management and technical requirements in these laboratory standards. The review showed that both documents share requirements for over ten critical areas covering objectives, infrastructure, management systems, and laboratory processes. There were, however, differences in standard expectations where GPPQCL emphasizes system procedures for planning and future budgets that will ensure continuity. Conversely, ISO 17025 was more focused on the risk management approach to establish laboratory quality systems. Elements in the two documents form common standard requirements to assure the validity of laboratory test results that promote mutual recognition. The ISO standard currently has more global patronage than GPPQCL.

Keywords: ISO/IEC 17025:2017, laboratory standards, quality control, WHO GPPQCL

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Authors: Giani Gradinaru

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Biodiversity crisis is one of the many crises that started at the turn of the millennia. Concrete form of expression is still disputed, but there is a relatively high consensus regarding the high rate of degradation and the urgent need for action. The strategy of action outlines a strong economic component, together with the recognition of market mechanisms as the most effective policies to protect biodiversity. In this context, biodiversity and ecosystem services are natural assets that play a key role in economic strategies and technological development to promote development and prosperity. Developing and strengthening policies for transition to an economy based on efficient use of resources is the way forward. To emphasize the co-viability specific to the connection economyecosystem services, scientific approach aimed on one hand how to implement policies for nature conservation and on the other hand, the concepts underlying the economic expression of ecosystem services- value, in the context of current technology. Following the analysis of business opportunities associated with changes in ecosystem services was concluded that development of market mechanisms for nature conservation is a trend that is increasingly stronger individualized within recent years. Although there are still many controversial issues that have already given rise to an obvious bias, international organizations and national governments have initiated and implemented in cooperation or independently such mechanisms. Consequently, they created the conditions for convergence between private interests and social interests of nature conservation, so there are opportunities for ongoing business development which leads, among other things, the positive effects on biodiversity. Finally, points out that markets fail to quantify the value of most ecosystem services. Existing price signals reflect at best, only a proportion of the total amount corresponding provision of food, water or fuel.

Keywords: ecosystem services, economic evaluation, nature conservation

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Authors: Achitphol Chookaew, Paramee Thongsukhsai, Patamarerk Engsontia, Narongwit Nakwan, Pritsana Raugrut

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Lung cancer is one of the most common malignancies and primary cause of death due to cancer worldwide. Non-small cell lung cancer (NSCLC) is the main subtype in which majority of patients present with advanced-stage disease. Herein, we analyzed differentially expressed genes to find potential biomarkers for lung cancer diagnosis as well as prognostic markers. We used transcriptome data from our 2 NSCLC patients and public data (GSE81089) composing of 8 NSCLC and 10 normal lung tissues. Differentially expressed genes (DEGs) between NSCLC and normal tissue and between early-stage and late-stage NSCLC were analyzed by the DESeq2. Pairwise correlation was used to find the DEGs with false discovery rate (FDR) adjusted p-value £ 0.05 and |log2 fold change| ³ 4 for NSCLC versus normal and FDR adjusted p-value £ 0.05 with |log2 fold change| ³ 2 for early versus late-stage NSCLC. Bioinformatic tools were used for functional and pathway analysis. Moreover, the top ten genes in each comparison group were verified the expression and survival analysis via GEPIA. We found 150 up-regulated and 45 down-regulated genes in NSCLC compared to normal tissues. Many immnunoglobulin-related genes e.g., IGHV4-4, IGHV5-10-1, IGHV4-31, IGHV4-61, and IGHV1-69D were significantly up-regulated. 22 genes were up-regulated, and five genes were down-regulated in late-stage compared to early-stage NSCLC. The top five DEGs genes were KRT6B, SPRR1A, KRT13, KRT6A and KRT5. Keratin 6B (KRT6B) was the most significantly increased gene in the late-stage NSCLC. From GEPIA analysis, we concluded that IGHV4-31 and IGKV1-9 might be used as diagnostic biomarkers, while KRT6B and KRT6A might be used as prognostic biomarkers. However, further clinical validation is needed.

Keywords: Bioinformatics, differentially expressed genes, non-small cell lung cancer, transcriptomics.

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Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Dusik Oh, Jaemin Kim, Seongwon Cho

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Eye localization is necessary for face recognition and related application areas. Most of eye localization algorithms reported so far still need to be improved about precision and computational time for successful applications. In this paper, we propose an eye location method based on multi-scale Gabor feature vectors, which is more robust with respect to initial points. The eye localization based on Gabor feature vectors first needs to constructs an Eye Model Bunch for each eye (left or right eye) which consists of n Gabor jets and average eye coordinates of each eyes obtained from n model face images, and then tries to localize eyes in an incoming face image by utilizing the fact that the true eye coordinates is most likely to be very close to the position where the Gabor jet will have the best Gabor jet similarity matching with a Gabor jet in the Eye Model Bunch. Similar ideas have been already proposed in such as EBGM (Elastic Bunch Graph Matching). However, the method used in EBGM is known to be not robust with respect to initial values and may need extensive search range for achieving the required performance, but extensive search ranges will cause much more computational burden. In this paper, we propose a multi-scale approach with a little increased computational burden where one first tries to localize eyes based on Gabor feature vectors in a coarse face image obtained from down sampling of the original face image, and then localize eyes based on Gabor feature vectors in the original resolution face image by using the eye coordinates localized in the coarse scaled image as initial points. Several experiments and comparisons with other eye localization methods reported in the other papers show the efficiency of our proposed method.

Keywords: Eye Localization, Gabor features, Multi-scale, Gabor wavelets.

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Authors: Norsakinah Mohammad Osman, Ali Etemad, Patimah Ismail

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Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder that characterized by the presence of high glucose in blood that cause from insulin resistance and insufficiency due to deterioration β-cell Langerhans functions. T2DM is commonly caused by the combination of inherited genetic variations as well as our own lifestyle. Metallothionein (MT) is a known cysteine-rich protein responsible in helping zinc homeostasis which is important in insulin signaling and secretion as well as protection our body from reactive oxygen species (ROS). MT scavenged ROS and free radicals in our body happen to be one of the reasons of T2DM and its complications. The objective of this study was to investigate the association of MT1A and MT2A polymorphisms between T2DM and control subjects among Malay populations. This study involved 150 T2DM and 120 Healthy individuals of Malay ethnic with mixed genders. The genomic DNA was extracted from buccal cells and amplified for MT1A and MT2A loci; the 347bp and 238bp banding patterns were respectively produced by mean of the Polymerase Chain Reaction (PCR). The PCR products were digested with Mlucl and Tsp451 restriction enzymes respectively and producing fragments lengths of (158/189/347bp) and (103/135/238bp) respectively. The ANOVA test was conducted and it shown that there was a significant difference between diabetic and control subjects for age, BMI, WHR, SBP, FPG, HBA1C, LDL, TG, TC and family history with (P<0.05). While the HDL, CVD risk ratio and DBP does not show any significant difference with (P>0.05). The genotype frequency for AA, AG and GG of MT1A polymorphisms was 72.7%, 22.7% and 4.7% in cases and 15%, 55% and 30% in control respectively. As for MT2A, genotype frequency of GG, GC and CC was 42.7%, 27.3% and 30% in case and 5%, 40% and 55% for control respectively. Both polymorphisms show significant difference between two investigated groups with (P=0.000). The Post hoc test was conducted and shows a significant difference between the genotypes within each polymorphism (P=0. 000). The MT1A and MT2A polymorphisms were believed to be the reliable molecular markers to distinguish the T2DM subjects from healthy individuals in Malay populations.

Keywords: Type 2 Diabetes Mellitus (T2DM), Metallothionein (MT), MT1A (rs11076161), MT2A (rs10636), Malay, Genetic Polymorphism.

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Authors: Olivier Adam, Maciej Lopatka, Christophe Laplanche, Jean-François Motsch

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This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns non-stationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: Auto Regressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a real-time system.

Keywords: Autoregressive model, Daubechies Wavelet, Fourier Transform, marine mammals, signal processing, spectrogram, sperm whale, Wavelet Transform.

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: Authentication, key-session, security, wireless sensors.

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Authors: Nida Rizvi, Deeksha Katyal, Varun Joshi

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River Hindon is an important river catering the demand of highly populated rural and industrial cluster of western Uttar Pradesh, India. Water quality of river Hindon is deteriorating at an alarming rate due to various industrial, municipal and agricultural activities. The present study aimed at identifying the pollution sources and quantifying the degree to which these sources are responsible for the deteriorating water quality of the river. Various water quality parameters, like pH, temperature, electrical conductivity, total dissolved solids, total hardness, calcium, chloride, nitrate, sulphate, biological oxygen demand, chemical oxygen demand, and total alkalinity were assessed. Water quality data obtained from eight study sites for one year has been subjected to the two multivariate techniques, namely, principal component analysis and cluster analysis. Principal component analysis was applied with the aim to find out spatial variability and to identify the sources responsible for the water quality of the river. Three Varifactors were obtained after varimax rotation of initial principal components using principal component analysis. Cluster analysis was carried out to classify sampling stations of certain similarity, which grouped eight different sites into two clusters. The study reveals that the anthropogenic influence (municipal, industrial, waste water and agricultural runoff) was the major source of river water pollution. Thus, this study illustrates the utility of multivariate statistical techniques for analysis and elucidation of multifaceted data sets, recognition of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.

Keywords: Cluster analysis, multivariate statistical technique, river Hindon, water Quality.

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Authors: M. R. Homaeinezhad, E. Tavakkoli, M. Habibi, S. A. Atyabi, A. Ghaffari

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This paper describes a new supervised fusion (hybrid) electrocardiogram (ECG) classification solution consisting of a new QRS complex geometrical feature extraction as well as a new version of the learning vector quantization (LVQ) classification algorithm aimed for overcoming the stability-plasticity dilemma. Toward this objective, after detection and delineation of the major events of ECG signal via an appropriate algorithm, each QRS region and also its corresponding discrete wavelet transform (DWT) are supposed as virtual images and each of them is divided into eight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposed classification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structure consisting of five different classifiers namely as Support Vector Machine (SVM), Modified Learning Vector Quantization (MLVQ) and three Multi Layer Perceptron-Back Propagation (MLP–BP) neural networks with different topologies were designed and implemented. The new proposed algorithm was applied to all 48 MIT–BIH Arrhythmia Database records (within–record analysis) and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result, the average accuracy value Acc=98.51% was obtained. Also, the proposed method was applied to 6 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, PB) belonging to 20 different records of the aforementioned database (between– record analysis) and the average value of Acc=95.6% was achieved. To evaluate performance quality of the new proposed hybrid learning machine, the obtained results were compared with similar peer– reviewed studies in this area.

Keywords: Feature Extraction, Curve Length Method, SupportVector Machine, Learning Vector Quantization, Multi Layer Perceptron, Fusion (Hybrid) Classification, Arrhythmia Classification, Supervised Learning Machine.

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Authors: Kaznah Alshammari, Thomas Beach, Yacine Rezgui

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Technological advances in the construction sector are helping to make smart cities a reality by means of Cyber-Physical Systems (CPS). CPS integrate information and the physical world through the use of Information Communication Technologies (ICT). An increasingly common goal in the built environment is to integrate Building Information Models (BIM) with Internet of Things (IoT) and sensor technologies using CPS. Future advances could see the adoption of digital twins, creating new opportunities for CPS using monitoring, simulation and optimisation technologies. However, researchers often fail to fully consider the security implications. To date, it is not widely possible to assimilate BIM data and cybersecurity concepts and, therefore, security has thus far been overlooked. This paper reviews the empirical literature concerning IoT applications in the built environment and discusses real-world applications of the IoT intended to enhance construction practices, people’s lives and bolster cybersecurity. Specifically, this research addresses two research questions: (a) How suitable are the current IoT and CPS security stacks to address the cybersecurity threats facing digital twins in the context of smart buildings and districts? and (b) What are the current obstacles to tackling cybersecurity threats to the built environment CPS? To answer these questions, this paper reviews the current state-of-the-art research concerning digital twins in the built environment, the IoT, BIM, urban cities and cybersecurity. The results of the findings of this study confirmed the importance of using digital twins in both IoT and BIM. Also, eight reference zones across Europe have gained special recognition for their contributions to the advancement of IoT science. Therefore, this paper evaluates the use of digital twins in CPS to arrive at recommendations for expanding BIM specifications to facilitate IoT compliance, bolster cybersecurity and integrate digital twin and city standards in the smart cities of the future.

Keywords: BIM, cybersecurity, digital twins, IoT, urban cities.

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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Authors: Eryati Darwin, Eka Fithra Elfi, Indria Hafizah

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Background: Physical exercise induces a pattern of hormonal and immunological responses that prevent endothelial dysfunction by maintaining the availability of nitric oxide (NO). Regular and moderate exercise stimulates NO release, that can be considered as protective factor of cardiovascular diseases, while strenuous exercise induces increased levels in a number of pro-inflammatory and anti-inflammatory cytokines. Pro-inflammatory cytokines tumor necrosis factor-α (TNF-α) triggers endothelial activation which results in an increased vascular permeability. Nuclear gene factor kappa B (NF-κB) activates biological effect of TNF-α. Aim of Study: To determine the effect of physical exercise on the endothelial and skeletal muscle, we measured the level of NF-κB on rats’ serum, macrophages, and myocytes after strenuous physical exercise. Methods: 30 male Rattus norvegicus in the age of eight weeks were randomly divided into five groups (each containing six), and there were treated groups (T) and control group (C). The treated groups obtain strenuous physical exercise by ran on treadmill at 32 m/minutes for 1 hour or until exhaustion. Blood samples, myocytes of gastrocnemius muscle, and intraperitoneal macrophages were collected sequentially. There were investigated immediately, 2 hours, 6 hours, and 24 hours (T1, T2, T3, and T4) after sacrifice. The levels of NF-κB were measured by ELISA methods. Results: From our study, we found that the levels of NF-κB on myocytes in treated group from which its specimen was taken immediately (T1), 2 hours after treadmill (T2), and 6 hours after treadmill (T3) were significantly higher than control group (p<0.05), while the group from which its specimen was taken 24 hours after treadmill, was no significantly different (p>0.05). Also on macrophages, NF-κB in treated groups T1, T2, and T3 was significantly higher than control group (p<0.05), but there was no difference between T4 and control group (p>0.05). The level of serum NF-κB was not significantly different between treatment group as well as compared to control group (p>0.05). Serum NF-κB was significantly higher than the level on macrophages and myocytes (p<0.05). Conclusion: This study demonstrated that strenuous physical exercise stimulates the activation of NF-κB that plays a role in vascular inflammation and muscular damage, and may be recovered after resting period.

Keywords: Endothelial function, inflammation, NF-κB, physical exercise.

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Authors: Pooja Jain

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Art education is often ignored in syllabus of developing countries like India and in educational planning for development but now days Indian Art with a global recognition is becoming an integral part of the education at all levels. The term art, widely used in all parts of the modern world, carried varied significance in India as its meaning was continuously being extended, covering the many varieties of creative expression such as painting, sculpture, commercial art, design, poetry, music, dance, and architecture. Over the last 100 years Indian artists of all forms have evolved a wide variety of expressive styles. With the recommendations and initiatives by Government of India, Art Education has subsequently gained pace at the school level as a mandatory subject for all making a path way for students with a creative bend of mind. This paper investigates curriculum in various schools of the country at secondary and senior secondary levels along with some eminent institutions running the program. Findings depicted the role of art education and justified its importance primarily with commercial art being perceived to be essential for students learning skills for economic gain in their career ahead. With so many art colleges spread across India, emerging artists and designers are being trained and are creating art of infinite variety and style and have opened up many career avenues. Commercial Art being a plethora of artistic expressions has confidently come of age wherein a creative perception is mixed with an introspective imagination to bring out multi faceted career options with a significant future enveloped in art. Visual arts in education thus is an expanding field of result assured research.

Keywords: Modern art, commercial art, introspective imagination, career.

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Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: Modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition.

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Authors: Ilona Copik

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The aim of this study is to analyze the representation of memories of the forced displacement of Poles and Germans from the eastern territories in 1945 as depicted by Polish and German feature films between the years 1945-1960. The aftermath of World War II and the Allied agreements concluded at Yalta and Potsdam (1945) resulted in changes in national borders in Central and Eastern Europe and the large-scale transfer of civilians. The westward migration became a symbol of the new post-war division of Europe, new spheres of influence separated by the Iron Curtain. For years it was a controversial topic in both Poland and Germany due to the geopolitical alignment (the socialist East and capitalist West of Europe), as well as the unfinished debate between the victims and perpetrators of the war. The research premise is to take a comparative view of the conflicted cultures of Polish and German memory, to reflect on the possibility of an international dialogue about the past recorded in film images, and to discover the potential of film as a narrative warning against totalitarian inclinations. Until now, films made between 1945 and 1960 in Poland and the German occupation zones have been analyzed mainly in the context of artistic strategies subordinated to ideology and historical politics. In this study, the intention is to take a critical approach leading to the recognition of how films work as collective memory media, how they reveal the mechanisms of memory/ forgetting, and what settlement topoi and migration myths they contain. The main hypothesis is that feature films about forced displacement, in addition to the politics of history - separate in each country - reveal comparable transnational individual experiences: the chaos of migration, the trauma of losing one's home, the conflicts accompanying the familiar/foreign, the difficulty of cultural adaptation, the problem of lost identity, etc.

Keywords: Forced displacement, Polish and German cinema, war victims, World War II.

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Authors: N. Umasuthan, S. D. N. K. Bathige, W. S. Thulasitha, I. Whang, J. Lee

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The MyD88 is an evolutionarily conserved host-expressed adaptor protein that is essential for proper TLR/ IL1R immune-response signaling. A previously identified complete cDNA (1626 bp) of OfMyD88 comprised an ORF of 867 bp encoding a protein of 288 amino acids (32.9 kDa). The gDNA (3761 bp) of OfMyD88 revealed a quinquepartite genome organization composed of 5 exons (with the sizes of 310, 132, 178, 92 and 155 bp) separated by 4 introns. All the introns displayed splice signals consistent with the consensus GT/AG rule. A bipartite domain structure with two domains namely death domain (24-103) coded by 1^st exon, and TIR domain (151-288) coded by last 3 exons were identified through in silico analysis. Moreover, homology modeling of these two domains revealed a similar quaternary folding nature between human and rock bream homologs. A comprehensive comparison of vertebrate MyD88 genes showed that they possess a 5-exonic structure.In this structure, the last three exons were strongly conserved, and this suggests that a rigid structure has been maintained during vertebrate evolution.A cluster of TATA box-like sequences were found 0.25 kb upstream of cDNA starting position. In addition, putative 5'-flanking region of OfMyD88 was predicted to have TFBS implicated with TLR signaling, including copies of NFkB1, APRF/ STAT3, Sp1, IRF1 and 2 and Stat1/2. Using qPCR technique, a ubiquitous mRNA expression was detected in liver and blood. Furthermore, a significantly up-regulated transcriptional expression of OfMyD88 was detected in head kidney (12-24 h; >2-fold), spleen (6 h; 1.5-fold), liver (3 h; 1.9-fold) and intestine (24 h; ~2-fold) post-Fla challenge. These data suggest a crucial role for MyD88 in antibacterial immunity of teleosts.

Keywords: MyD88, Innate immunity, Flagellin, Genomic analysis.

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Authors: A. El Harraj, N. Raissouni

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes invariance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: Video surveillance, background subtraction, Contrast Limited Histogram Equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes.

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Authors: C. S. Quah, S. P. L. Sim

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This study examined how individuals in their respective teams contributed to innovation performance besides defining the term of innovation in their own respective views. This study also identified factors that motivated University staff to contribute to the innovation products. In addition, it examined whether there is a significant relationship between professional training level and the length of service among university staff towards innovation and to what extent do the two variables contributed towards innovative products. The significance of this study is that it revealed the strengths and weaknesses of the university staff when contributing to innovation performance. Stratified-random sampling was employed to determine the samples representing the population of lecturers in the study, involving 123 lecturers in one of the local universities in Malaysia. The method employed to analyze the data is through categorizing into themes for the open-ended questions besides using descriptive and inferential statistics for the quantitative data. This study revealed that two types of definition for the term “innovation” exist among the university staff, namely, creation of new product or new approach to do things as well as value-added creative way to upgrade or improve existing process and service to be more efficient. This study found that the most prominent factor that propels them towards innovation is to improve the product in order to benefit users, followed by selfsatisfaction and recognition. This implies that the staff in the organization viewed the creation of innovative products as a process of growth to fulfill the needs of others and also to realize their personal potential. This study also found that there was only a significant relationship between the professional training level and the length of service of 4 - 6 years among the university staff. The rest of the groups based on the length of service showed that there was no significant relationship with the professional training level towards innovation. Moreover, results of the study on directional measures depicted that the relationship for the length of service of 4- 6 years with professional training level among the university staff is quite weak. This implies that good organization management lies on the shoulders of the key leaders who enlighten the path to be followed by the staff.

Keywords: Innovation, length of service, performance, professional training level, motivation.

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: Transportation networks, freight delivery, data flow, monitoring, e-services.

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Authors: Érica Lima

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In the digital era, in which we have an avalanche of information, it is not new that the Internet has brought new modes of communication and knowledge access. Characterized by the multiplicity of discourses, opinions, beliefs and cultures, the web is a space of political-ideological dimensions where people (who often do not know each other) interact and create representations, deconstruct stereotypes, and redefine identities. Currently, the translator needs to be able to deal with digital spaces ranging from specific software to social media, which inevitably impact on his professional life. One of the most impactful ways of being seen in cyberspace is the participation in social networking groups. In addition to its ability to disseminate information among participants, social networking groups allow a significant personal and social exposure. Such exposure is due to the visibility of each participant achieved not only on its personal profile page, but also in each comment or post the person makes in the groups. The objective of this paper is to study the representations of translators and translation process on the Internet, more specifically in publications in two Brazilian groups of great influence on the Facebook: "Translators/Interpreters" and "Translators, Interpreters and Curious". These chosen groups represent the changes the network has brought to the profession, including the way translators are seen and see themselves. The analyzed posts allowed a reading of what common sense seems to think about the translator as opposed to what the translators seem to think about themselves as a professional class. The results of the analysis lead to the conclusion that these two positions are antagonistic and sometimes represent conflict of interests: on the one hand, the society in general consider the translator’s work something easy, therefore it is not necessary to be well remunerated; on the other hand, the translators who know how complex a translation process is and how much it takes to be a good professional. The results also reveal that social networking sites such as Facebook provide more visibility, but it takes a more active role from the translator to achieve a greater appreciation of the profession and more recognition of the role of the translator, especially in face of increasingly development of automatic translation programs.

Keywords: Facebook, social representation, translation, translator.

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Authors: Ticijana Prijon, Branko Ermenc

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Background: Blunt aortic trauma (BAT) includes various morphological changes that occur during deceleration, acceleration and/or body compression in traffic accidents. The various forms of BAT, from limited laceration of the intima to complete transection of the aorta, depends on the force acting on the vessel wall and the tolerance of the aorta to injury. The force depends on the change in velocity, the dynamics of the accident and of the seating position in the car. Tolerance to aortic injury depends on the anatomy, histological structure and pathomorphological alterations due to aging or disease of the aortic wall. An overview of the literature and medical documentation reveals that different terms are used to describe certain forms of BAT, which can lead to misinterpretation of findings or diagnoses. We therefore, propose a classification that would enable uniform systematic screening of all forms of BAT. We have classified BAT into three morphologycal types: TYPE I (intramural), TYPE II (transmural) and TYPE III (multiple) aortic ruptures with appropriate subtypes. Methods: All car accident casualties examined at the Institute of Forensic Medicine from 2001 to 2009 were included in this retrospective study. Autopsy reports were used to determine the occurrence of each morphological type of BAT in deceased drivers, front seat passengers and other passengers in cars and to define the morphology of BAT in relation to the accident dynamics and the age of the fatalities. Results: A total of 391 fatalities in car accidents were included in the study. TYPE I, TYPE II and TYPE III BAT were observed in 10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in drivers, front seat and other passengers was 36,7%, 43,1% and 28,6%, respectively. In frontal collisions, the incidence of BAT was 32,7%, in lateral collisions 54,2%, and in other traffic accidents 29,3%. The average age of fatalities with BAT was 42,8 years and of those without BAT 39,1 years. Conclusion: Identification and early recognition of the risk factors of BAT following a traffic accident is crucial for successful treatment of patients with BAT. Front seat passengers over 50 years of age who have been injured in a lateral collision are the most at risk of BAT.

Keywords: Aorta, blunt trauma, car accidents, morphology, risk factors.

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Authors: Manuel A. Alonso-Tarajano, Roberto Mosca, Patrick Aloy

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Protein kinases participate in a myriad of cellular processes of major biomedical interest. The in vivo substrate specificity of these enzymes is a process determined by several factors, and despite several years of research on the topic, is still far from being totally understood. In the present work, we have quantified the contributions to the kinase substrate specificity of i) the phosphorylation sites and their surrounding residues in the sequence and of ii) the association of kinases to adaptor or scaffold proteins. We have used position-specific scoring matrices (PSSMs), to represent the stretches of sequences phosphorylated by 93 families of kinases. We have found negative correlations between the number of sequences from which a PSSM is generated and the statistical significance and the performance of that PSSM. Using a subset of 22 statistically significant PSSMs, we have identified specificity determinant residues (SDRs) for 86% of the corresponding kinase families. Our results suggest that different SDRs can function as positive or negative elements of substrate recognition by the different families of kinases. Additionally, we have found that human proteins with known function as adaptors or scaffolds (kAS) tend to interact with a significantly large fraction of the substrates of the kinases to which they associate. Based on this characteristic we have identified a set of 279 potential adaptors/scaffolds (pAS) for human kinases, which is enriched in Pfam domains and functional terms tightly related to the proposed function. Moreover, our results show that for 74.6% of the kinase–pAS association found, the pAS colocalize with the substrates of the kinases they are associated to. Finally, we have found evidence suggesting that the association of kinases to adaptors and scaffolds, may contribute significantly to diminish the in vivo substrate crossed-specificity of protein kinases. In general, our results indicate the relevance of several SDRs for both the positive and negative selection of phosphorylation sites by kinase families and also suggest that the association of kinases to pAS proteins may be an important factor for the localization of the enzymes with their set of substrates.

Keywords: Kinase, phosphorylation, substrate specificity, adaptors, scaffolds, cellular colocalization.

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Authors: Helene Eller

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The aim of non-profit organizations (NPO) is to provide services and goods for its clientele, with profit being a minor objective. By having this definition as the basic purpose of doing business, it is obvious that the goal of an organisation is to serve several bottom lines and not only the financial one. This approach is underpinned by the non-distribution constraint which means that NPO are allowed to make profits to a certain extent, but not to distribute them. The advantage is that there are no single shareholders who might have an interest in the prosperity of the organisation: there is no pie to divide. The gained profits remain within the organisation and will be reinvested in purposeful projects. Good governance is mandatory to support the aim of NPOs. Looking for a measure of good governance the principals of corporate governance (CG) will come in mind. The purpose of CG is direction and control, and in the field of NPO, CG is enlarged to consider the relationship to all important stakeholders who have an impact on the organisation. The recognition of more relevant parties than the shareholder is the link to corporate social responsibility (CSR). It supports a broader view of the bottom line: It is no longer enough to know how profits are used but rather how they are made. Besides, CSR addresses the responsibility of organisations for their impact on society. When transferring the concept of CSR to the non-profit area it will become obvious that CSR with its distinctive features will match the aims of NPOs. As a consequence, NPOs who apply CG apply also CSR to a certain extent. The research is designed as a comprehensive theoretical and empirical analysis. First, the investigation focuses on the theoretical basis of both concepts. Second, the similarities and differences are outlined and as a result the interconnection of both concepts will show up. The contribution of this research is manifold: The interconnection of both concepts when applied to NPOs has not got any attention in science yet. CSR and governance as integrated concept provides a lot of advantages for NPOs compared to for-profit organisations which are in a steady justification to show the impact they might have on the society. NPOs, however, integrate economic and social aspects as starting point. For NPOs CG is not a mere concept of compliance but rather an enhanced concept integrating a lot of aspects of CSR. There is no “either-nor” between the concepts for NPOs.

Keywords: Business ethics, corporate governance, corporate social responsibility, non-profit organisations, stakeholder theory.

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Authors: Maryam Memarian, Mahmood Naghizadeh

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Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.

Keywords: Creativity, deconstruction, event.

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Authors: Mariam Vardiashvili

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The economic value of the asset impairment process is quite large. Impairment reflects the reduction of future economic benefits or service potentials itemized in the asset. The assets owned by public sector entities bring economic benefits or are used for delivery of the free-of-charge services. Consequently, they are classified as cash-generating and non-cash-generating assets. IPSAS 21 - Impairment of non-cash-generating assets, and IPSAS 26 - Impairment of cash-generating assets, have been designed considering this specificity.  When measuring impairment of assets, it is important to select the relevant methods. For measurement of the impaired Non-Cash-Generating Assets, IPSAS 21 recommends three methods: Depreciated Replacement Cost Approach, Restoration Cost Approach, and  Service Units Approach. Impairment of Value in Use of Cash-Generating Assets (according to IPSAS 26) is measured by discounted value of the money sources to be received in future. Value in use of the cash-generating asserts (as per IPSAS 26) is measured by the discounted value of the money sources to be received in the future. The article provides classification of the assets in the public sector  as non-cash-generating assets and cash-generating assets and, deals also with the factors which should be considered when evaluating  impairment of assets. An essence of impairment of the non-financial assets and the methods of measurement thereof evaluation are formulated according to IPSAS 21 and IPSAS 26. The main emphasis is put on different methods of measurement of the value in use of the impaired Cash-Generating Assets and Non-Cash-Generation Assets and the methods of their selection. The traditional and the expected cash flow approaches for calculation of the discounted value are reviewed. The article also discusses the issues of recognition of impairment loss and its reflection in the financial reporting. The article concludes that despite a functional purpose of the impaired asset, whichever method is used for measuring the asset, presentation of realistic information regarding the value of the assets should be ensured in the financial reporting. In the theoretical development of the issue, the methods of scientific abstraction, analysis and synthesis were used. The research was carried out with a systemic approach. The research process uses international standards of accounting, theoretical researches and publications of Georgian and foreign scientists.

Keywords: Non-cash-generating assets, cash-generating assets, recoverable value, recoverable service amount, value in use.

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Authors: Elif Gencturk, Ekin Yurdakul, Ahmet Y. Celik, Senol Mutlu, Kutlu O. Ulgen

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Yeast cells are generally used as a model system of eukaryotes due to their complex genetic structure, rapid growth ability in optimum conditions, easy replication and well-defined genetic system properties. Thus, yeast cells increased the knowledge of the principal pathways in humans. During fermentation, carbohydrates (hexoses and pentoses) degrade into some toxic by-products such as 5-hydroxymethylfurfural (5-HMF or HMF) and furfural. HMF influences the ethanol yield, and ethanol productivity; it interferes with microbial growth and is considered as a potent inhibitor of bioethanol production. In this study, yeast single cell behavior under HMF application was monitored by using a continuous flow single phase microfluidic platform. Microfluidic device in operation is fabricated by hot embossing and thermo-compression techniques from cyclo-olefin polymer (COP). COP is biocompatible, transparent and rigid material and it is suitable for observing fluorescence of cells considering its low auto-fluorescence characteristic. The response of yeast cells was recorded through Red Fluorescent Protein (RFP) tagged Nop56 gene product, which is an essential evolutionary-conserved nucleolar protein, and also a member of the box C/D snoRNP complexes. With the application of HMF, yeast cell proliferation continued but HMF slowed down the cell growth, and after HMF treatment the cell proliferation stopped. By the addition of fresh nutrient medium, the yeast cells recovered after 6 hours of HMF exposure. Thus, HMF application suppresses normal functioning of cell cycle but it does not cause cells to die. The monitoring of Nop56 expression phases of the individual cells shed light on the protein and ribosome synthesis cycles along with their link to growth. Further computational study revealed that the mechanisms underlying the inhibitory or inductive effects of HMF on growth are enriched in functional categories of protein degradation, protein processing, DNA repair and multidrug resistance. The present microfluidic device can successfully be used for studying the effects of inhibitory agents on growth by single cell tracking, thus capturing cell to cell variations. By metabolic engineering techniques, engineered strains can be developed, and the metabolic network of the microorganism can thus be manipulated such that chemical overproduction of target metabolite is achieved along with the maximum growth/biomass yield.  

Keywords: COP, HMF, ribosome biogenesis, thermoplastic microbioreactor, yeast.

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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Authors: Lee Bih Ni, Zulfhikar Rabe, Nurul Asyikin Hassan

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The Ministry of Education Malaysia dynamically and drastically made the subject of History mandatory to be in force in 2013. This is in recognition of the nation's heritage and treasures in maintaining true facts and information for future generations of the State. History reveals the civilization of a nation and the fact of national cultural heritage. Civilization needs to be preserved as a legacy of sovereign heritage. Today's generation is the catalyst for future heirs who will support the principle and direction of the country. In line with the National Education Philosophy that aims to shape the potential development of individuals holistically and uniquely in order to produce a balanced and harmonious student in terms of intellectual, spiritual, emotional and physical. Hence, understanding the importance of studying the history subject as a pillar of identity and the history of nationhood is to be a priority in the pursuit of knowledge and empowering the spirit of statehood that is nurtured through continuous learning at school. Judging from the aspect of teacher leadership role in integrating history in a combined way based on Teacher Education Philosophy. It empowers the teaching profession towards the teacher to support noble character. It also supports progressive and scientific views. Teachers are willing to uphold the State's aspirations and celebrate the country's cultural heritage. They guarantee individual development and maintain a united, democratic, progressive and disciplined society. Teacher's role as a change and leadership agent in education begins in the classroom through formal or informal educational processes. This situation is expanded in schools, communities and countries. The focus of this paper is on the role of teacher leadership influencing the effectiveness of teaching and learning history in the classroom environment. Leadership guides to teachers' perceptions on the role of teacher leadership, teaching leadership, and the teacher leadership role and effective teacher leadership role. Discussions give emphasis on aspects of factors affecting the classroom environment, forming the classroom agenda, effective classroom implementation methods, suitable climate for historical learning and teacher challenges in implicating the effectiveness of teaching and learning processes.

Keywords: Teacher leadership, leadership lessons, effective classroom, effective teacher.

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