Search results for: DNA sequences classification

Authors: Mira Kadric

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The proposed paper deals with a new developed approach for interpreting teaching, combining traditional didactics with a new element. The fundamental principle of the approach is taken from the theatre pedagogy (Augusto Boal`s Theatre of the Oppressed) and includes the discussion on social power relations. From the point of view of education sociology this implies strengthening students’ individual potential for self-determination on a number of levels, especially in view of the present increase in social responsibility. This knowledge constitutes a starting point and basis for the process of self-determined action. This takes place in the context of a creative didactic policy which identifies didactic goals, provides clear sequences of content, specifies interdisciplinary methods and examines their practical adequacy and ultimately serves not only individual translators and interpreters, but all parties involved. The goal of the presented didactic model is to promote independent work and problem-solving strategies; this helps to develop creative potential and self-confident behaviour. It also conveys realistic knowledge of professional reality and thus also of the real socio-political and professional parameters involved. As well as providing a discussion of fundamental questions relevant to Translation and Interpreting Studies, this also serves to improve this interdisciplinary didactic approach which simulates interpreting reality and illustrates processes and strategies which (can) take place in real life. This idea is illustrated in more detail with methods taken from the Theatre of the Oppressed created by Augusto Boal. This includes examples from (dialogue) interpreting teaching based on documentation from recordings made in a seminar in the summer term 2014.

Keywords: augusto boal, didactic model, interpreting teaching, theatre of the oppressed

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Authors: Sa`ad M. Ismail, Hung-Hsun Yen, Christina M. Murray, Helen M. S. Davies

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The lumbosacral junction (where the 7th lumbar vertebra (L7) articulates with the sacrum) is a clinically important area in the dog. The 7th lumbar vertebra (L7) is normally shorter than other lumbar vertebrae, and it has been reported that variations in the L7 length may be associated with other abnormal anatomical findings. These variations included the reduction or absence of the portion of the median sacral crest. In this study, 53 greyhound cadavers were placed in right lateral recumbency, and two lateral radiographs were taken of the lumbosacral region for each greyhound. The length of the 6th lumbar (L6) vertebra and L7 were measured using radiographic measurement software and was defined to be the mean of three lines drawn from the caudal to the cranial edge of the L6 and L7 vertebrae (a dorsal, middle, and ventral line) between specific landmarks. Sacrocaudal fusion was found in 41.5% of the greyhounds. The mean values of the length of L6, L7, and the ratio of the L6/L7 length of the greyhounds with sacrocaudal fusion were all greater than those with standard sacrums (three sacral vertebrae). There was a significant difference (P < 0.05) in the mean values of the length of L7 between the greyhounds without sacrocaudal fusion (mean = 29.64, SD ± 2.07) and those with sacrocaudal fusion (mean = 30.86, SD ± 1.80), but, there was no significant difference in the mean value of the length of the L6 measurement. Among different types of sacrocaudal fusion, the longest L7 was found in greyhounds with sacrum type D, intermediate length in those with sacrum type B, and the shortest was found in those with sacrums type C, and the mean values of the ratio of the L6/L7 were 1.11 (SD ± 0.043), 1.15, (SD ± 0.025), and 1.15 (SD ± 0.011) for the types B, C, and D respectively. No significant differences in the mean values of the length of L6 or L7 were found among the different types of sacrocaudal fusion. The occurrence of sacrocaudal fusion might affect direct anatomically connected structures such as the L7. The variation in the length of L7 between greyhounds with sacrocaudal fusion and those without may reflect the possible sequences of the process of fusion. Variations in the length of the L7 vertebra in greyhounds may be associated with the occurrence of sacrocaudal fusion. The variation in the vertebral length may affect the alignment and biomechanical properties of the sacrum and may alter the loading. We concluded that any variations in the sacrum anatomical features might change the function of the sacrum or the surrounding anatomical structures.

Keywords: biomechanics, Greyhound, sacrocaudal fusion, locomotion, 6th Lumbar (L6) Vertebra, 7th Lumbar (L7) Vertebra, ratio of the L6/L7 length

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Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

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This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: neural network, self-organizing map, rule extraction, rule insertion

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Authors: Umairah Natasya Binti Mohd Omeershffudin, Suresh Kumar

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Klebsiella pneumoniae, a Gram-negative enteric bacterium that causes nosocomial and urinary tract infections. Particular concern is the global emergence of multidrug-resistant (MDR) strains of Klebsiella pneumoniae. Characterization of antibiotic resistance determinants at the genomic level plays a critical role in understanding, and potentially controlling, the spread of multidrug-resistant (MDR) pathogens. In this study, drug-resistant Klebsiella pneumoniae strain 825795-1 was investigated with extensive computational approaches aimed at identifying novel drug targets among hypothetical proteins. We have analyzed 1099 hypothetical proteins available in genome. We have used in-silico genome subtraction methodology to design potential and pathogen-specific drug targets against Klebsiella pneumoniae. We employed bioinformatics tools to subtract the strain-specific paralogous and host-specific homologous sequences from the bacterial proteome. The sorted 645 proteins were further refined to identify the essential genes in the pathogenic bacterium using the database of essential genes (DEG). We found 135 unique essential proteins in the target proteome that could be utilized as novel targets to design newer drugs. Further, we identified 49 cytoplasmic protein as potential drug targets through sub-cellular localization prediction. Further, we investigated these proteins in the DrugBank databases, and 11 of the unique essential proteins showed druggability according to the FDA approved drug bank databases with diverse broad-spectrum property. The results of this study will facilitate discovery of new drugs against Klebsiella pneumoniae.

Keywords: pneumonia, drug target, hypothetical protein, subtractive genomics

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Authors: Kakali Bhadra

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Binding of small molecules to DNA and recently to RNA, continues to attract considerable attention for developing effective therapeutic agents for control of gene expression. This work focuses towards understanding interaction of harmalol, a dihydro beta-carboline alkaloid, with different nucleic acid motifs viz. double stranded CT DNA, single stranded A-form poly(A), double-stranded A-form of poly(C)·poly(G) and clover leaf tRNAphe by different spectroscopic, calorimetric and molecular modeling techniques. Results of this study converge to suggest that (i) binding constant varied in the order of CT DNA > poly(C)·poly(G) > tRNAphe > poly(A), (ii) non-cooperative binding of harmalol to poly(C)·poly(G) and poly(A) and cooperative binding with CT DNA and tRNAphe, (iii) significant structural changes of CT DNA, poly(C)·poly(G) and tRNAphe with concomitant induction of optical activity in the bound achiral alkaloid molecules, while with poly(A) no intrinsic CD perturbation was observed, (iv) the binding was predominantly exothermic, enthalpy driven, entropy favoured with CT DNA and poly(C)·poly(G) while it was entropy driven with tRNAphe and poly(A), (v) a hydrophobic contribution and comparatively large role of non-polyelectrolytic forces to Gibbs energy changes with CT DNA, poly(C)·poly(G) and tRNAphe, and (vi) intercalated state of harmalol with CT DNA and poly(C)·poly(G) structure as revealed from molecular docking and supported by the viscometric data. Furthermore, with competition dialysis assay it was shown that harmalol prefers hetero GC sequences. All these findings unequivocally pointed out that harmalol prefers binding with ds CT DNA followed by ds poly(C)·poly(G), clover leaf tRNAphe and least with ss poly(A). The results highlight the importance of structural elements in these natural beta-carboline alkaloids in stabilizing different DNA and RNA of various motifs for developing nucleic acid based better therapeutic agents.

Keywords: calorimetry, docking, DNA/RNA-alkaloid interaction, harmalol, spectroscopy

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Authors: Andrew Anis Fakhrey Mosaad

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Introduction: There are many different types of sleep disorders, each with serious implications for a person's health and a large financial burden on society. Method: This review offers a framework based on the International Classification of Sleep Disorders to aid in the diagnosis and treatment of sleep disorders. Differentiating between primary and secondary insomnia is covered, along with pharmacological and nonpharmacological therapy options. Common abnormalities of the circadian rhythm are mentioned along with their therapies, such as light therapy and chronotherapy. This article discusses the identification and management of periodic limb movement disorder and restless legs syndrome. The therapy of upper airway resistance syndrome and obstructive sleep apnea are the main topics of discussion. Conclusion: The range of narcolepsy symptoms and results, as well as diagnostic procedures and treatment, are discussed. The causes, outcomes, and treatments of many types of insomnias, such as sleep terrors, somnambulism, and rapid eye movement (REM) behavior sleep disorders, are discussed.

Keywords: diagnosis, treatment, sleep disorders, insomnia

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Dinh Ha, Tran, Chung-Ruey Yen

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This study explored the morphological characteristics and effects of pollination methods on fruit set and characteristics in four red pitaya (Hylocereus spp.) clones. The distinctive morphological recognition and classification among pitaya clones were confirmed by the stem, flower and fruit features. The fruit production season was indicated from the beginning of May to the end of August, the beginning of September with 6-7 flowering cycles per year. The floral stage took from 15-19 days and fruit duration spent 30–32 days. VN White, fully self-compatible, obtained high fruit set rates (80.0-90.5 %) in all pollination treatments and the maximum fruit weight (402.6 g) in hand self- and (403.4 g) in open-pollination. Chaozhou 5 was partially self-compatible while Orejona and F11 were completely self-incompatible. Hand cross-pollination increased significantly fruit set (95.8; 88.4 and 90.2 %) and fruit weight (374.2; 281.8 and 416.3 g) in Chaozhou 5, Orejona, and F11, respectively. TSS contents were not much influenced by pollination methods.

Keywords: Hylocereus spp., morphology, floral phenology, pollination requirement

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Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

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Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

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Authors: Ben Hadj Hassen Sameh, Gaillard Corentin, Andrew Parker, Kristine Krug

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Perceptual decisions about sequences of sensory stimuli often show serial dependence. The behavioural choice on one trial is often affected by the choice on previous trials. We investigated whether the neuronal signals in extrastriate visual area V5/MT on preceding trials might influence choice on the current trial and thereby reveal the neuronal mechanisms of sequential choice effects. We analysed data from 30 single neurons recorded from V5/MT in three Rhesus monkeys making sequential choices about the direction of rotation of a three-dimensional cylinder. We focused exclusively on the responses of neurons that showed significant choice-related firing (mean choice probability =0.73) while the monkey viewed perceptually ambiguous stimuli. Application of a wavelet transform to the choice-related firing revealed differences in the frequency band of neuronal activity that depended on whether the previous trial resulted in a correct choice for an unambiguous stimulus that was in the neuron’s preferred direction (low alpha and high beta and gamma) or non-preferred direction (high alpha and low beta and gamma). To probe this in further detail, we applied a regularized linear decoder to predict the choice for an ambiguous trial by referencing the neuronal activity of the preceding unambiguous trial. Neuronal activity on a previous trial provided a significant prediction of the current choice (61% correc, 95%Cl~52%t), even when limiting analysis to preceding trials that were correct and rewarded. These findings provide a potential neuronal signature of sequential choice effects in the primate visual cortex.

Keywords: perception, decision making, attention, decoding, visual system

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Authors: Pranita Shivankar, Devashree Hardas, Prabodhachandra Deshmukh, Arun Suryavanshi

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Bhimbetka Rock Shelters is the UNESCO World Heritage Site located about 45 kilometers south of Bhopal in the state of Madhya Pradesh, India. Rapid changes in land use land cover (LULC) adversely affect the environment. In recent past, significant changes are found in the cultural landscape over a period of time. The objective of the paper was to study the changes in land use land cover (LULC) of Bhimbetka and its peripheral region. For this purpose, the supervised classification was carried out by using satellite images of Landsat and IRS LISS III for the year 2000 and 2013. Use of remote sensing in combination with geographic information system is one of the effective information technology tools to generate land use land cover (LULC) change information.

Keywords: IRS LISS III, Landsat, LULC, UNESCO, World Heritage Site

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Authors: Diego Aguirre, Olac Fuentes

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In this paper, we present a taxonomy of weight initialization schemes used in deep learning. We survey the most representative techniques in each class and compare them in terms of overhead cost, convergence rate, and applicability. We also introduce a new weight initialization scheme. In this technique, we perform an initial feedforward pass through the network using an initialization mini-batch. Using statistics obtained from this pass, we initialize the weights of the network, so the following properties are met: 1) weight matrices are orthogonal; 2) ReLU layers produce a predetermined number of non-zero activations; 3) the output produced by each internal layer has a unit variance; 4) weights in the last layer are chosen to minimize the error in the initial mini-batch. We evaluate our method on three popular architectures, and a faster converge rates are achieved on the MNIST, CIFAR-10/100, and ImageNet datasets when compared to state-of-the-art initialization techniques.

Keywords: deep learning, image classification, supervised learning, weight initialization

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Authors: Annet Namusoke, Annet Namayanja, Peter Wasswa, Shakirah Nampijja

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Common bean cultivar G2333 which offers broad resistance for anthracnose has been widely used as a source of resistance in breeding for anthracnose resistance. The cultivar is pyramided with three genes namely CO-4, CO-5 and CO-7 and of these three genes, the CO-4 gene has been found to offer the broadest resistance. The main aim of this work was to identify and validate easily assayable PCR based co-dominant molecular markers for selection of the CO-4 gene in segregating populations derived from crosses of G2333 with RWR 1946 and RWR 2075, two commercial Andean cultivars highly susceptible to anthracnose. Marker sequences for the study were obtained by blasting the sequence of the COK-4 gene in the Phaseolus gene database. Primer sequence pairs that were not provided from the Phaseolus gene database were designed by the use of Primer3 software. PCR conditions were optimized and the PCR products were run on 6% HPAGE gel. Results of the polymorphism test indicated that out of 18 identified markers, only two markers namely BM588 and BM211 behaved co-dominantly. Phenotypic evaluation for reaction to anthracnose disease was done by inoculating 21days old seedlings of three parents, F1 and F2 populations with race 7 of Colletotrichum lindemuthianum in the humid chamber. DNA testing of the BM588 marker onto the F2 segregating population of the crosses RWR 1946 x G 2333 and RWR 2075 x G2333 further revealed that the marker BM588 co-segregated with disease resistance with co-dominance of two alleles of 200bp and 400bp, fitting the expected segregation ratio of 1:2:1. The BM588 marker was significantly associated with disease resistance and gave promising results for marker assisted selection of the CO-4 gene in the breeding lines. Activities to validate the BM211 marker are also underway.

Keywords: codominant, Colletotrichum lindemuthianum, MAS, Phaseolus vulgaris

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Authors: Jacques Barnard, Magda Huisman, Gunther R. Drevin

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Rapid expansion and development in die mobile technology market has created an opportunity for users to participate in location based games. As a consequence of this fast expanding market and new technology, it is important to be aware of the implications this has on security. This paper measures the impact on the security awareness of games’ participants, as well as on that of students at university level with regards to their various stages of input in years of studying and gamer classification. This serves to provide insight into the matter as to discernible differences in the awareness of the security implications concerning these technologies. The data was accumulated via a web questionnaire that was to be completed yearly by students from respective year groups. Results signify a meaningful disparity in security awareness among students completing the varying study years and research. This awareness, however, does not always impact on gamers.

Keywords: gamer classifications, location based games, location based data, security awareness

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Ishu Surender, M. Amez Khair, Ishan Singh

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Urbanization is a multidimensional phenomenon. It is an indication of the long-term process for the shift of economics to industrial from rural. The significance of urbanization in modernization, socio-economic development, and poverty eradication is relevant in modern times. This paper aims to study the urbanization index model in the capital of India, Delhi using aspects such as demographic aspect, infrastructural development aspect, and economic development aspect. The urbanization index of all the nine districts of Delhi will be determined using multiple parameters such as population density and the availability of health and education facilities. The definition of the urban area varies from city to city and requires periodic classification which makes direct comparisons difficult. The urbanization index calculated in this paper can be employed to measure the urbanization of a district and compare the level of urbanization in different districts.

Keywords: multiparameter, population density, multiple regression, normalized urbanization index

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Authors: Fabienne Fel, Eric Griette

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Reshoring, whether concerning back-reshoring or near-reshoring, is a quite recent phenomenon. Despite the economic and political interest of this topic, academic research questioning determinants of reshoring remains rare. Our paper aims at contributing to fill this gap. In order to better understand the reasons for reshoring, we conducted a study among 280 French firms during spring 2016, three-quarters of which sourced, or source, in China. 105 firms in the sample have reshored all or part of their Chinese production or supply in recent years, and we aimed to establish a typology of the motives that drove them to this decision. We asked our respondents about the history of their Chinese supplies, their current reshoring strategies, and their motivations. Statistical analysis was performed with SPSS 22 and SPAD 8. Our results show that change in commercial and financial terms with China is the first motive explaining the current reshoring movement from this country (it applies to 54% of our respondents). A change in corporate strategy is the second motive (30% of our respondents); the reshoring decision follows a change in companies’ strategies (upgrading, implementation of a CSR policy, or a 'lean management' strategy). The third motive (14% of our sample) is a mere correction of the initial offshoring decision, considered as a mistake (under-estimation of hidden costs, non-quality and non-responsiveness problems). Some authors emphasize that developing a short supply chain, involving geographic proximity between design and production, gives a competitive advantage to companies wishing to offer innovative products. Admittedly 40% of our respondents indicate that this motive could have played a part in their decision to reshore, but this reason was not enough for any of them and is not an intrinsic motive leading to leaving Chinese suppliers. Having questioned our respondents about the importance given to various problems leading them to reshore, we then performed a Principal Components Analysis (PCA), associated with an Ascending Hierarchical Classification (AHC), based on Ward criterion, so as to point out more specific motivations. Three main classes of companies should be distinguished: -The 'Cost Killers' (23% of the sample), which reshore their supplies from China only because of higher procurement costs and so as to find lower costs elsewhere. -The 'Realists' (50% of the sample), giving equal weight or importance to increasing procurement costs in China and to the quality of their supplies (to a large extend). Companies being part of this class tend to take advantage of this changing environment to change their procurement strategy, seeking suppliers offering better quality and responsiveness. - The 'Voluntarists' (26% of the sample), which choose to reshore their Chinese supplies regardless of higher Chinese costs, to obtain better quality and greater responsiveness. We emphasize that if the main driver for reshoring from China is indeed higher local costs, it is should not be regarded as an exclusive motivation; 77% of the companies in the sample, are also seeking, sometimes exclusively, more reactive suppliers, liable to quality, respect for the environment and intellectual property.

Keywords: China, procurement, reshoring, strategy, supplies

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Authors: Pamita Awasthi, Kirna, Shilpa Dogra, Manu Vatsal, Ritu Barthwal

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Doxorubicin, also known as adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemias, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhoea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, anti-inflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilino-ethyl)benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 µM where as for doxorubicin is 7.2 µ.

Keywords: Doxorubicin, auto dock, in silco, in vitro

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Authors: Victor Siahaan

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Coal still become the most important energy source for electricity generation known for its contribution which take the biggest portion of energy mix that a country has, for example Indonesia. The low cost of electricity generation and quite a lot of resources make this energy still be the first choice to fill the portion of base load power. To realize its significance to produce electricity, it is necessary to know the amount of coal (volume) needed to ensure that all coal power plants (CPP) in a country can operate properly. To secure the volume of coal, in this study, discussion was carried out regarding the identification of coal mining sources in Indonesia, classification of coal typical from each coal mining sources, and determination of the port of loading. By using data above, the sources of coal mining are then selected to feed certain CPP based on the compatibility of the coal typical and the lowest transport cost.

Keywords: merit order, Indonesian coal mine, electricity, power plant

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Authors: Sheeraz Memon, Namunu C. Maddage, Margaret Lech, Nicholas Allen

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The effect of a clinical environment on the accuracy of the speaker verification was tested. The speaker verification tests were performed within homogeneous environments containing clinically depressed speakers only, and non-depresses speakers only, as well as within mixed environments containing different mixtures of both climatically depressed and non-depressed speakers. The speaker verification framework included the MFCCs features and the GMM modeling and classification method. The speaker verification experiments within homogeneous environments showed 5.1% increase of the EER within the clinically depressed environment when compared to the non-depressed environment. It indicated that the clinical depression increases the intra-speaker variability and makes the speaker verification task more challenging. Experiments with mixed environments indicated that the increase of the percentage of the depressed individuals within a mixed environment increases the speaker verification equal error rates.

Keywords: speaker verification, GMM, EM, clinical environment, clinical depression

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Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

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Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

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The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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Authors: Hadi Farhadian, Homayoon Katibeh

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In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above-mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm the high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occurred in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: water Seepage, Amirkabir Tunnel, analytical method, DEM, SGR

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Authors: Selin Küçük

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Pre-industrial architecture is integration of natural and subsequent properties by intelligence and experience. Since various settlements relatively industrialized or non-industrialized at any time, ‘pre-industrial’ term does not refer to a definite time. Natural properties, which are existent conditions and materials in natural local environment, are climate, geomorphology and local materials. Subsequent properties, which are all anthropological comparatives, are culture of societies, requirements of people and construction techniques that people use. Yet, after industrialization, technology took technique’s place, cultural effects are manipulated, requirements are changed and local/natural properties are almost disappeared in architecture. Technology is universal, global and expands simply; conversely technique is time and experience dependent and should has a considerable cultural background. This research is about construction techniques according to natural properties of a region and classification of these techniques. Understanding local architecture is only possible by searching its background which is hard to reach. There are always changes in positive and negative in architectural techniques through the time. Archaeological layers of a region sometimes give more accurate information about transformation of architecture. However, natural properties of any region are the most helpful elements to perceive construction techniques. Many international sources from different cultures are interested in local architecture by mentioning natural properties separately. Unfortunately, there is no literature deals with this subject as far as systematically in the correct way. This research aims to improve a clear perspective of local architecture existence by categorizing archetypes according to natural properties. The ultimate goal of this research is generating a clear classification of local architecture independent from subsequent (anthropological) properties over the world such like a handbook. Since local architecture is the most sustainable architecture with refer to its economic, ecologic and sociological properties, there should be an excessive information about construction techniques to be learned from. Constructing the same buildings in all over the world is one of the main criticism of modern architectural system. While this critics going on, the same buildings without identity increase incrementally. In post-industrial term, technology widely took technique’s place, yet cultural effects are manipulated, requirements are changed and natural local properties are almost disappeared in architecture. These study does not offer architects to use local techniques, but it indicates the progress of pre-industrial architectural evolution which is healthier, cheaper and natural. Immigration from rural areas to developing/developed cities should be prohibited, thus culture and construction techniques can be preserved. Since big cities have psychological, sensational and sociological impact on people, rural settlers can be convinced to not to immigrate by providing new buildings designed according to natural properties and maintaining their settlements. Improving rural conditions would remove the economical and sociological gulf between cities and rural. What result desired to arrived in, is if there is no deformation (adaptation process of another traditional buildings because of immigration) or assimilation in a climatic region, there should be very similar solutions in the same climatic regions of the world even if there is no relationship (trade, communication etc.) among them.

Keywords: climate zones, geomorphology, local architecture, local materials

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

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Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: Paraskevi Theodorou, Apostolos Meliones

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In the context of the development process of two assistive navigation mobile apps for blind and visually impaired people (BVI) an extensive qualitative analysis of the requirements of potential users has been conducted. The analysis was based on interviews with BVIs and aimed to elicit not only their needs with respect to autonomous navigation but also their preferences on specific features of the apps under development. The elicited requirements were structured into four main categories, namely, requirements concerning the capabilities, functionality and usability of the apps, as well as compatibility requirements with respect to other apps and services. The main categories were then further divided into nine sub-categories. This classification, along with its content, aims to become a useful tool for the researcher or the developer who is involved in the development of digital services for BVI.

Keywords: accessibility, assistive mobile apps, blind and visually impaired people, user requirements analysis

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Authors: Ziyue Zeng

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Bacteriophages are viruses which infect bacteria specifically. Over the past decades, phage λ has been extensively studied, especially its interaction with the Escherichia coli LamB (EcLamB) protein receptor. Nonetheless, despite the enormous numbers and near-ubiquity of environmental phages, aside from phage λ, there is a paucity of information on other phages which target EcLamB as a receptor. In this study, to answer the question of whether there are other EcLamB-targeting phages in the natural environment, a simple and convenient method was developed and used for isolating environmental phages which target a particular surface structure of a particular bacterium; in this case, the EcLamB outer membrane protein. From the enrichments with the engineered bacterial hosts, a collection of EcLamB-targeting phages (ΦZZ phages) were easily isolated. Intriguingly, unlike phage λ, an obligate EcLamB-dependent phage in the Siphoviridae family, the newly isolated ΦZZ phages alternatively recognised EcLamB or E. coli OmpC (EcOmpC) as a receptor when infecting E. coli. Furthermore, ΦZZ phages were suggested to represent new species in the Tequatrovirus genus in the Myoviridae family, based on phage morphology and genomic sequences. Most phages are thought to have a narrow host range due to their exquisite specificity in receptor recognition. With the ability to optionally recognise two receptors, ΦZZ phages were considered relatively promiscuous. Via the heterologous expression of EcLamB on the bacterial cell surface, the host range of ΦZZ phages was further extended to three different enterobacterial genera. Besides, an interesting selection of evolved phage mutants with a broader host range was isolated, and the key mutations involved in their evolution to adapt to new hosts were investigated by genomic analysis. Finally, and importantly, two ΦZZ phages were found to be putative generalised transducers, which could be exploited as tools for DNA manipulations.

Keywords: environmental microbiology, phage, microbe-host interactions, microbial ecology

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Authors: Andrey V. Khromov, Antonida V. Makhotenko, Ekaterina A. Snigir, Svetlana S. Makarova, Natalia O. Kalinina, Valentin V. Makarov, Mikhail E. Taliansky

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Due to its simplicity, CRISPR/Cas9 has become widely used and capable of inducing mutations in the genes of organisms of various kingdoms. The aim of this work was to develop applications for the efficient modification of DNA coding sequences of phytoene desaturase (PDS), coilin and vacuolar invertase (Solanum tuberosum) genes, and to develop a new nanoparticles carrier efficient technology to deliver the CRISPR/Cas9 system for editing the plant genome. For each of the genes - coilin, PDS and vacuolar invertase, five single RNA guide (sgRNAs) were synthesized. To determine the most suitable nanoplatform, two types of NP platforms were used: magnetic NPs (MNPS) and gold NPs (AuNPs). To test the penetration efficiency, they were functionalized with fluorescent agents - BSA * FITS and GFP, as well as labeled Cy3 small-sized RNA. To measure the efficiency, a fluorescence and confocal microscopy were used. It was shown that the best of these options were AuNP - both in the case of proteins and in the case of RNA. The next step was to check the possibility of delivering components of the CRISPR/Cas9 system to plant cells for editing target genes. AuNPs were functionalized with a ribonucleoprotein complex consisting of Cas9 and corresponding to target genes sgRNAs, and they were biolistically bombarded to axillary buds and apical meristems of potato plants. After the treatment by the best NP carrier, potato meristems were grown to adult plants. DNA isolated from this plants was sent to a preliminary fragment of the analysis to screen out the non-transformed samples, and then to the NGS. The present work was carried out with the financial support from the Russian Science Foundation (grant No. 16-16-04019).

Keywords: biobombardment, coilin, CRISPR/Cas9, nanoparticles, NPs, PDS, sgRNA, vacuolar invertase

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Authors: Hongyun Li, Zhibin Jiang

Abstract:

The travel of passengers in the urban rail transit network is influenced by changes in network structure and operational status, and the response of individual travel preferences to these changes also varies. Firstly, the influence of the suspension of urban rail transit line sections on passenger travel along the line is analyzed. Secondly, passenger travel trajectories containing multi-dimensional semantics are described based on network UD data. Next, passenger panel data based on spatio-temporal sequences is constructed to achieve frequent passenger clustering. Then, the Graph Convolutional Network (GCN) is used to model and identify the changes in travel modes of different types of frequent passengers. Finally, taking Shanghai Metro Line 11 as an example, the travel behavior patterns of frequent passengers after the Huaqiao section shutdown during the COVID-19 epidemic are analyzed. The results showed that after the section shutdown, most passengers would transfer to the nearest Anting station for boarding, while some passengers would transfer to other stations for boarding or cancel their travels directly. Among the passengers who transferred to Anting station for boarding, most of passengers maintained the original normalized travel mode, a small number of passengers waited for a few days before transferring to Anting station for boarding, and only a few number of passengers stopped traveling at Anting station or transferred to other stations after a few days of boarding on Anting station. The results can provide a basis for understanding urban rail transit passenger travel patterns and improving the accuracy of passenger flow prediction in abnormal operation scenarios.

Keywords: urban rail transit, section shutdown, frequent passenger, travel behavior pattern

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