Search results for: ordinal response models

Authors: Abdul Qadir Qadis, Satoru Goya, Minoru Yatsu, Yu-uki Yoshida, Toshihiro Ichijo, Shigeru Sato

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Bacterial probiotics are known to modulate the gut-associated lymphoid and epithelial tissue response to enhance the activities of intestinal and systemic immune system in human and animals. In cattle, the immune-stimulatory effects of probiotics have been evaluated during intestinal disorders. To investigate the effects of probiotic on the function of peripheral blood mononuclear cells, eight healthy Holstein calves (10 ± 3 weeks) were assigned to a 4 × 2 experimental design. The probiotic, consisting of Lactobacillus plantarum, Enterococcus faecium and Clostridium butyricum, was administered orally at 3.0 g/100 kg body weight to calves once daily for 5 consecutive days. Calves given no probiotic served as the control. In the treatment group, increases in numbers of CD282+ monocytes, CD3+ T-cells and CD4+, CD8+ and WC1+ γδ T- cell subsets were noted on day 7 post-placement compared to pre-dose day and the control group. Expression of interleukin-6, interferon-gamma and tumor necrosis factor-alpha was elevated in peripheral leukocytes on days 7 and 14. These results suggest that peripheral blood leukocytes in healthy calves may be stimulated via the gastrointestinal microbiota, which was increased by the oral probiotic treatment. The 5-day repeated administration of a bacterial probiotic may enhance cellular immune function in weaned calves.

Keywords: bacterial-probiotic, calf, interleukin, leukocyte

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Authors: Marta Fernández Olmos, Jorge Fleta, Talia Gómez

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This article shares the results of a temporal analysis of the literature on imports of intermediate inputs based on review techniques. The aim of this paper is to identify the main lines of research, their trends, topics, and the research agenda. The internationalization field has attracted considerable scholars and practitioners’ attention in recent years and has grown, rapidly, resulting in a large body of knowledge scattered in different areas of specialization. However, there are no studies that are entirely restricted to imports, intermediate inputs and innovation performance. The performance analysis provided an updated overview of the evolution of the importing literature from 1970 to 2022 and quantitatively identified the most productive and influential journals, articles, authors, and countries. The results show that the current topics are mainly based on modes of importing, innovation performance of importing intermediate imports and collaborations. Future lines of research are identified from topics with lower co-occurrence, such as artificial intelligence, entrepreneurship, and alternative business models such as multinational enterprises (MNEs) versus non-MNEs.

Keywords: imports, intermediate inputs, innovation performance, review

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Authors: Shidvash Vakilipour, Mehdi Habibnia, Rouzbeh Riazi, Masoud Mohammadi, Mohammad H. Sabour

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The flow field passing through a highly loaded low pressure (LP) turbine cascade is numerically investigated at design and off-design conditions. The Field Operation And Manipulation (OpenFOAM) platform is used as the computational Fluid Dynamics (CFD) tool. Firstly, the influences of grid resolution on the results of k-ε, k-ω, and LES turbulence models are investigated and compared with those of experimental measurements. A numerical pressure under-shoot is appeared near the end of blade pressure surface which is sensitive to grid resolution and flow turbulence modeling. The LES model is able to resolve separation on a coarse and fine grid resolutions. Secondly, the off-design flow condition is modeled by negative and positive inflow incidence angles. The numerical experiments show that a separation bubble generated on blade pressure side is predicted by LES. The total pressure drop is also been calculated at incidence angle between -20◦ and +8◦. The minimum total pressure drop is obtained by k-ω and LES at the design point.

Keywords: low pressure turbine, off-design performance, openFOAM, turbulence modeling, flow separation

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Authors: Yuan Li, Yitao Han, Zhao Zhu

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In this paper, the effect of blasting loads on steel-concrete composite bridges has been investigated considering the slope reflection effect. Reasonable values of girder size, plate thickness, stiffening rib, and other design parameters were selected according to design specifications. Modified RHT (Riedel-Hiermaier-Thoma) was used as constitutive relation in analyses. In order to simulate the slope reflection effect, the slope of the bridge was precisely built in the model. Different blasting conditions, including top, middle, and bottom explosions, were simulated. The multi-Euler domain method based on fully coupled Lagrange and Euler models was adopted for the structural analysis of the explosion process using commercial software AUTODYN. The obtained results showed that explosion overpressure was increased by 3006, 879, and 449kPa, corresponding to explosions occurring at the top, middle, and bottom of the slope, respectively. At the same time, due to energy accumulation and transmission dissipation caused by slope reflection, the corresponding yield lengths of steel beams were increased by 8, 0, and 5m, respectively.

Keywords: steel-concrete composite bridge, explosion damage, slope reflection, blasting loads, RHT

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Oluwaseun Amusa

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The online space has continued to be a platform for not only private and mundane discussions but also a tribune for voicing critical political and national opinions. Nigerians and the international community have employed the online media, as well as other media platforms to articulate their thoughts on the claims which favour possibilities of the demise of the incumbent president of Nigeria, President Muhammadu Buhari, after a prolonged illness in year 2007 and the ploy of a Jubril of Sudan clone in his place. This study thus examines the pragmatic strategies employed in the online articles on the national dilemma caused by the Buhari/Jubril claims and refutals, in response to the lacuna in the literature on such analytical investigations on the subject. Two online articles titled, 'Buhari: The real, the fake and the dead' and 'Taking the Buhari/Jubril story seriously', authored by two Nigerian writers, Tunde Odesola and Abimbola Adelakun, respectively and retrieved online from 360nobs.com and Nairaland blogs, on December 3, 2018, and December 7, 2018, respectively, served as data for the study. The data were analysed using the Stance Theory and the Pragmatic Act Theory. Findings showed that the writers employed stance acts, rhetorical questions, metaphors, histo-political allusions, name-calling, and derogatives, in achieving the pragmeme of disabusing. This results in a pragmatic reconstruction of readers' views on the issue.

Keywords: Buhari/Jubril claims, online articles, pragmatic strategies, stance theory

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Authors: Khurram Munir, Cuie Wen, Yuncang Li

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Magnesium (Mg) metal matrix composites (MMCs) reinforced with graphene nanoplatelets (GNPs) have been developed by powder metallurgy (PM). In this study, GNPs with different concentrations (0.1-0.3 wt.%) were dispersed into Mg powders by high-energy ball-milling processes. The microstructure and resultant mechanical properties of the fabricated nanocomposites were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Raman spectroscopy (RS), compression and nano-wear tests. The corrosion resistance of the fabricated composites was evaluated by electrochemical tests and hydrogen evolution measurements. Finally, the biological response of Mg-GNPs composites was assessed using osteoblast-like SaOS2 cells. The results indicate that GNPs are excellent candidates as reinforcements in Mg matrices for the manufacture of biodegradable Mg-based composite implants. GNP addition improved the mechanical properties of Mg via synergetic strengthening modes. Moreover, retaining the structural integrity of GNPs during PM processing improved the ductility, compressive strength, and corrosion resistance of the Mg-GNP composites as compared to monolithic Mg. Cytotoxicity assessments did not reveal any significant toxicity with the addition of GNPs to Mg matrices. This study demonstrates that Mg-xGNPs with x < 0.3 wt.%, may constitute novel biodegradable implant materials for load-bearing applications.

Keywords: magnesium-graphene composites, strengthening mechanisms, In vitro cytotoxicity, biocorrosion

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Authors: C. Soh, S. Muktar, C. M. Malata, J. R. Benson

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Introduction Reasons for requesting CPM include prevention of recurrence, peace of mind and moving on after breast cancer. Some women seek CPM as a delayed procedure but factors influencing this are poorly understood. Methods A retrospective analysis examined patients undergoing CPM as either an immediate or delayed procedure with or without breast reconstruction (BR) between January 2009 and December 2019. A cross-sectional survey based on validated questionnaires (5 point Likert scale) explored patients’ decision-making process in terms of timing of CPM and any BR. Results A total of 123 patients with unilateral breast cancer underwent CPM with 39 (32.5%) delayed procedures with or without BR. The response rate amongst patients receiving questionnaires (n=33) was 22/33 (66%). Within this delayed CPM cohort were three reconstructive scenarios 1) unilateral immediate BR with CPM (n=12); 2) delayed CPM with concomitant bilateral BR (n=22); 3) delayed bilateral BR after delayed CPM (n=3). Two patients had delayed CPM without BR. The most common reason for delayed CPM was to complete all cancer treatments (including radiotherapy) before surgery on the unaffected breast (score 2.91). The second reason was unavailability of genetic test results at the time of therapeutic mastectomy (score 2.64) whilst the third most cited reason was a subsequent change in family cancer history. Conclusion Factors for delayed CPM are patient-driven with few women spontaneously changing their mind having initially decided against immediate CPM for reasons also including surgical duration. CPM should be offered as a potentially delayed option with informed discussion of risks and benefits.

Keywords: Breast Cancer, CPM, Prophylactic, Rationale

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Authors: Majdi Al Shdifat, Juan Chiachio, Esther Puertas, María L. Jalón, Álvaro Blanca-Hoyos

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In recent years, the world has begun to adopt more sustainable practices in response to today's environmental and climate challenges. The construction sector is one of the most resource-intensive among others, so researchers are testing different types of materials with different processes and methodologies to achieve more environmentally and sustainably friendly buildings. Plastic is one of the most harmful materials for the environment. The global production of plastics has increased dramatically in recent decades, and it is one of the most widely used materials. However, plastic waste is not biodegradable and has a chemical composition that is stable for many years in the environment, both on land and in water bodies. Recycled plastics have been tested to be used in construction in many ways to reduce the amount of plastic in the environment and the use of raw materials in construction. In this context, the main objective of this research is to test the use of plastic fibers with one of the most promising materials to replace cement, which is rammed earth. In fact, rammed earth is considered one of the most environmentally friendly materials due to its use of local raw materials, recyclability, and low embodied energy. In this research, three different types of plastic fibers were used. Then, the blends were evaluated by considering their mechanical properties, including compressive strength and tensile strength. In addition, the non-destructive ultrasonic wave velocity was measured. The result shows excellent potential for the use of plastic fibers in rammed earth, especially in terms of compressive strength.

Keywords: mechanical characterization, plastic fibers reinforcement, rammed earth, sustainable material

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Authors: Nima Mahmoudi, Hamzeh Khazaei

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Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

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Authors: Mengqiu Deng, Xiao Peng, Yang Zhao

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The development of local energy systems requires the collective involvement of different actors from various levels of society. However, the stakeholder analysis of local energy systems still has been under-developed. This paper proposes an multi-agent system (MAS) framework to facilitate the development of stakeholder analysis of local energy systems. The framework takes into account the most influencing stakeholders, including prosumers/consumers, system operators, energy companies and government bodies. Different stakeholders are modeled based on agent architectures for example the belief-desire-intention (BDI) to better reflect their motivations and interests in participating in local energy systems. The agent models of different stakeholders are then integrated in one model of the whole energy system. An illustrative case study is provided to elaborate how to develop a quantitative agent model for different stakeholders, as well as to demonstrate the practicability of the proposed framework. The findings from the case study indicate that the suggested framework and agent model can serve as analytical instruments for enhancing the government’s policy-making process by offering a systematic view of stakeholder interconnections in local energy systems.

Keywords: multi-agent system, BDI agent, local energy systems, stakeholders

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Authors: Kittipong Tripetch, Nobuhiko Nakano

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This paper proposes one stage and two stage CMOS Complementary Regulated Cascode Distributed Amplifier (CRCDA) design based on Inductive and Transformer coupling techniques. Usually, Distributed amplifier is based on inductor coupling between gate and gate of MOSFET and between drain and drain of MOSFET. But this paper propose some new idea, by coupling with differential primary windings of transformer between gate and gate of MOSFET first stage and second stage of regulated cascade amplifier and by coupling with differential secondary windings transformer of MOSFET between drain and drain of MOSFET first stage and second stage of regulated cascade amplifier. This paper also proposes polynomial modeling of Silicon Transformer passive equivalent circuit from Nanyang Technological University which is used to extract frequency response of transformer. Cadence simulation results are used to verify validity of transformer polynomial modeling which can be used to design distributed amplifier without Cadence. 4 parameters of scattering matrix of 2 port of the propose circuit is derived as a function of 4 parameters of impedance matrix.

Keywords: CMOS regulated cascode distributed amplifier, silicon transformer modeling with polynomial, low power consumption, distribute amplification technique

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Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: Yuguang Wang, Chuanjun Wang

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At present, many coastal areas around the world suffer from seawater intrusion. Seawater intrusion is the superimposed result of two factors which are nature and human social economical activities in particular area. In recent years, due to excessive exploitation of groundwater, the seawater intrusion phenomenon aggravate in coastal zone of the Bohai and Huanghai seas in our country. Moreover, with sea-level rising, the original hydrodynamic equilibrium between saltwater and freshwater has been damaged to a certain extent, and it will further aggravate seawater intrusion in the land plains. In addition, overexploitation of groundwater declined groundwater level and increase saltwater intrusion in coastal areas. Therefore, in view of the sensitivity and vulnerability of the impact of sea-level rise in the future, the risk of sea-level rise in coastal zone should be considered, reasonable exploitation, utilization and management of coastal zone’s groundwater should be formulated. The response mechanism of sea-level rise should be studied to prevent and reduce the harm of seawater intrusion, which has important theoretical and realistic significances. In this paper, through the long-term monitoring of groundwater level and conductibility in the transition region of seawater intrusion for the sand coast area, realtimely master the situation of seawater intrusion. Combined with the seasonal exploitation station of groundwater and sea level variation, early alert the seawater intrusion to prevent and reduce the harm of seawater intrusion.

Keywords: groundwater level, sea level, seawater intrusion, sand coast

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Authors: Allmin Susaiyah, Aki Härmä, Milan Petković

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Automatic generation of insights from data using insight mining systems (IMS) is useful in many applications, such as personal health tracking, patient monitoring, and business process management. Existing IMS face challenges in controlling insight extraction, scaling to large databases, and generalising to unseen domains. In this work, we propose a hybrid approach consisting of rule-based and neural components for generating insights from data while overcoming the aforementioned challenges. Firstly, a rule-based data 2CNL component is used to extract statistically significant insights from data and represent them in a controlled natural language (CNL). Secondly, a BERTSum-based CNL2NL component is used to convert these CNLs into natural language texts. We improve the model using task-specific and domain-specific fine-tuning. Our approach has been evaluated using statistical techniques and standard evaluation metrics. We overcame the aforementioned challenges and observed significant improvement with domain-specific fine-tuning.

Keywords: data mining, insight mining, natural language generation, pre-trained language models

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Authors: Najah Kalifah Almazmomi

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In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

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Authors: Ana Carolina Hecht, Noelia Enriz, Mariana Garcia Palacios

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The South American anthropology has been recently focused to research with children in different contexts. In our researches with children from indigenous communities in the lowlands and highlands of South America (Qom and Mbyá), we especially considered social categories that define the different ways of being a boy and a girl. In this way, we built an approach to disrupt monolithic models of childhood. The aim of this paper is to tackle the first stage of life, demarcated from their nominal references and from the upbringing and formative experiences in which children participate. So, we will focus on the network of social relations in the period of childhood, making especial focus on language develops, religion, schooling and games. The crossing of our different thematic interests allows us to consider the complexity of knowledge and skills that come into play during the development of children. Methodologically, this text is based on an ethnographic approach, with frequent visits and periods of cohabitation, for more than a decade with Mbyá and Qom people, who lives within indigenous communities in the provinces of Chaco, Buenos Aires and Misiones, in Argentina. We made participant observation and interviews with children and their families, with the objective to include children's voices in our researches about the whole community.

Keywords: chidhood, indigenous people, schooling, upbringing

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Authors: Ali Hojati Najafabadi, Mohamad Hosein Rahmati, Seyed Ali Madanizadeh

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Governments execute energy subsidy reforms by either increasing energy prices or reducing energy price dispersion. These policies make less use of energy per plant (intensive margin), vary the total number of firms (extensive margin), promote technological progress (technology channel), and make additional resources to redistribute (resource channel). We estimate a structural dynamic firm model with endogenous technology adaptation using data from the manufacturing firms in Iran and a country ranked the second-largest energy subsidy plan by the IMF. The findings show significant dynamics and distributional effects due to an energy reform plan. The price elasticity of energy consumption in the industrial sector is about -2.34, while it is -3.98 for large firms. The dispersion elasticity, defined as the amounts of changes in energy consumption by a one-percent reduction in the standard error of energy price distribution, is about 1.43, suggesting significant room for a distributional policy. We show that the intensive margin is the main driver of energy price elasticity, whereas the other channels mostly offset it. In contrast, the labor response is mainly through the extensive margin. Total factor productivity slightly improves in light of the reduction in energy consumption if, at the same time, the redistribution policy boosts the aggregate demands.

Keywords: energy reform, firm dynamics, structural estimation, subsidy policy

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Authors: Sang-Sun Yoon, Yea-Hyun Leem, Sangmee Ahn Jo

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The N-acetylated-alpha-linked-acidic (NAAG) peptidase inhibitor 2-phosphonomethyl pentanedioic acid (2-PMPA) has demonstrated to be neuroprotective against glutamate-mediated neuron degeneration and neurological disorders such as ischemia. Several studies have demonstrated impaired psychiatric function by altered glutamate carboxypeptidase II expression, although 2-PMPA has not yet been studied. Thus, we investigated effect of 2-PMPA on depressive-like phenotype using C57BL/6 mice. Treatment of 2-PMPA (10 mg/kg for 6 days/daily, ip injection) on C57BL/6 naïve mice showed depressive-like symptoms such as decreased social preference, but did not affect the immobility measured by tail suspension test. Reduction of phosphorylated cAMP-responsive element binding (p-CREB) known as a representative marker of depressive-like behavior was observed in layer 1 and piriform cortex subregions of the prefrontal cortex of 2-PMPA-treated mice. The immunoreactivity of metabotropic glutamate receptors 5 (mGluR5) that mediate phosphorylation of CREB was also decreased in layer 1 and piriform cortex subregions of the prefrontal cortex of 2-PMPA injected mice. Thus, our results suggest that dysregulation of the GCPII or NAAG by 2-PMPA treatment is likely to be associated with pathogenesis of depression and further studies are needed to understand whether the reduced NAAG level or enhanced glutamate level in the brain is involved in this response.

Keywords: depression, GCPII, 2-PMPA, p-CREB, mGluR5

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: E. A. Tkachenko, E. M. Rogova, V. V. Klimov

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One of the basic issues of development management is connected with performance measurement as a prerequisite for identifying the achievement of development objectives. The aim of our research is to develop an improved model of assessing a company’s development results. The model should take into account the cyclical nature of development and the high degree of uncertainty in dealing with numerous management tasks. Our hypotheses may be formulated as follows: Hypothesis 1. The cycle of a company’s development may be studied from the standpoint of a project cycle. To do that, methods and tools of project analysis are to be used. Hypothesis 2. The problem of the uncertainty when justifying managerial decisions within the framework of a company’s development cycle can be solved through the use of the mathematical apparatus of fuzzy logic. The reasoned justification of the validity of the hypotheses made is given in the suggested article. The fuzzy logic toolkit applies to the case of technology shift within an enterprise. It is proven that some restrictions in performance measurement that are incurred to conventional methods could be eliminated by implementation of the fuzzy logic apparatus in performance measurement models.

Keywords: logic, fuzzy sets, performance measurement, project analysis

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Authors: Jie Liu, Wei Wei, Chun-Ping Chang

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Using a sample of 110 countries over the period 1984-2013, this paper examines the impacts of country risks on choosing a specific exchange rate regime (first by utilizing the Levy-Yeyati and Sturzenegger de facto classification and then robusting it by the IMF de jure measurement) relative to other regimes via the panel multinomial logit approach. Empirical findings are as follows. First, in the full samples case we provide evidence that government is more likely to implement a flexible regime, but less likely to adopt a fixed regime, under a low level of composite and financial risk. Second, we find that Eurozone countries are more likely to choose a fixed exchange rate regime with a decrease in the level of country risk and favor a flexible regime in response to a shock from an increase of risk, which is opposite to non-Eurozone countries. Third, we note that high-risk countries are more likely to choose a fixed regime with a low level of composite and political risk in the government, but do not adjust the exchange rate regime as a shock absorber when facing economic and financial risks. It is interesting to see that those countries with relatively low risk display almost opposite results versus high-risk economies. Overall, we believe that it is critically important to account for political economy variables in a government’s exchange rate policy decisions, especially for country risks. All results are robust to the panel ordered probit model.

Keywords: country risk, political economy, exchange rate regimes, shock absorber

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Authors: Mustafa Abu Ghalia, Yaser Dahman

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A new class of polyurethane (PU) reinforced with green bacterial cellulose nanofibers (BC) were prepared using a solvent casting method, with the goal of fabricating green nanocomposites. Four series classes of BC (1, 2.5, 5, and 10 wt%) were reinforced into PU matrices via BC surface modification and subsequently BC-grafted into PU throughout silane coupling agent to improve BC dispersion and its interfacial interaction. The experiment results from the tensile tester were evaluated according to the response surface method (RSM) for optimizing the impacts of variable parameters, pore size, porosity, and BC contents on the mechanical properties. The compressive strength for PU-5 BC wt% was about 9.8 MPa, and decrease when being generated prosperity to recorded at 4.9 MPa. Nielson model was applied to investigate the BC stress concentration on the PU matrices. Likewise, krenche and Hapli-Tasi model were employed to evaluate the BC nanofiber reinforcement potential and BC orientation into PU matrices. The analysis of variance (ANOVA) demonstrated that only BC loading has a significant effect in increases tensile strength, young’s modulus, and a flexural modulus of the PU-BC nanocomposites. The optimal factors of the variables experiment confirmed to be 5 wt% for BC, 230 for pore size, and 80 % for porosity. Scanning electron microscopy (SEM) micrographs showed that the uniform distribution of nanofibers in the PU matrices with the addition of BC 5 wt %. Hydrolytic degradation revealed that the weight loss in PU-BC scaffold is higher than PU-BC wt %.

Keywords: polyurethane scaffold, mechanical properties, tissue engineering, polyurethane

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Authors: Khaled M. Alhawiti

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Reading capability is a major segment of language competency. On the other hand, discovering topical writings at a fitting level for outside and second language learners is a test for educators. We address this issue utilizing natural language preparing innovation to survey reading level and streamline content. In the connection of outside and second-language learning, existing measures of reading level are not appropriate to this errand. Related work has demonstrated the profit of utilizing measurable language preparing procedures; we expand these thoughts and incorporate other potential peculiarities to measure intelligibility. In the first piece of this examination, we join characteristics from measurable language models, customary reading level measures and other language preparing apparatuses to deliver a finer technique for recognizing reading level. We examine the execution of human annotators and assess results for our finders concerning human appraisals. A key commitment is that our identifiers are trainable; with preparing and test information from the same space, our finders beat more general reading level instruments (Flesch-Kincaid and Lexile). Trainability will permit execution to be tuned to address the needs of specific gatherings or understudies.

Keywords: natural language processing, trainability, syntactic simplification tools, education

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Authors: Pham Quang Huy

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State budget is considered as an effective tool for controlling, adjusting and regulating the market economy of any countries. To ensure that the activities of the state in the fields of politics, economy and society has been efficiency, it requires major sources of certain budget. These financial funds are formed from tax revenues and tax revenues beyond. Therefore, the Governments need to have an accounting regime to manage the receipt, expenditure which are suitable for recording a full range of items. From that, it can help to increase the transparency and accountability in budget system. One of the main requirements in Vietnamese policies is to improve that accounting system of revenues and expenditures which can provide many reports to meet the information required of government and users, as well as directions to the trends of international standards requirements. By using quantitative research methods and analytical models to exploring factors, the main purpose of this article is to identify the factors affecting budget accounting and providing some direction for Vietnamese public sector in the future. The results indicated that Vietnam budget accounting has been impacted by seven factors and aims to implement three main orientations in the public sector units.

Keywords: state budget, accounting, IPSAS, budget management, government, public sector

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Authors: Laura Ulitzky, Dougbeh-Chris Nyan, Manuel M. Lafer, Erica Silberstein, Nicoleta Cehan, Deborah R. Taylor

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Hepatitis C virus (HCV)-associated hepatocellular carcinoma, fibrosis and cirrhosis are more frequent in men and postmenopausal women than in premenopausal women and women receiving hormone replacement therapy, suggesting that β-estradiol (estrogen) plays an innate role in preventing viral infection and liver disease. Estrogen classically acts through nuclear estrogen receptors or, alternatively, through the membrane-bound G-protein-coupled estrogen receptor (GPR30 or GPER). We observed a marked decrease in detectable virus when HCV-infected human hepatoma cells were treated with estrogen. The effect was mimicked by both Tamoxifen (Tam) and G1, a GPR30-specific agonist, and was reversed by the GPR30-specific antagonist, G15. Through GPR30, estrogen-mediated the down-regulation of occludin; a tight junction protein and HCV receptor, by promoting activation of matrix metalloproteinases (MMPs). Activated MMP-9 was secreted in response to estrogen, cleaving occludin in the extracellular Domain D, the motif required for HCV entry and spread. This pathway gives new insight into a novel innate immune pathway and the disparate host-virus responses to HCV demonstrated by the two sexes. Moreover, these data suggest that hormone replacement therapy may have beneficial antiviral properties for HCV-infected postmenopausal women and show promise for new antiviral treatments for both men and women.

Keywords: HCV, estrogen, occludin, MMPs

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Authors: Mehdi Damaliamiri, Firouzeh Akbari

Abstract:

Teaching literature to children at an early age is of great importance, and there have been different methods to facilitate learning literature. Based on the law, all children going to school in Iran should learn the Persian language and literature. This has been concomitant with two different levels of learning related to urban or rural bilingualism. For bilingual children living in the villages, learning literature and a new language (Persian) turns into a big challenge as it is done based on the translation the teacher does while in the city, it is easier as the confrontation of children with the Persian language is more. Over recent years, to change the trend of learning Persian by children speaking another language, the TV and radio programs have been considered to be effective, but the scores of the students in Persian language national exams show that these programs have not been so effective for the bilingual students living in the villages. To identify the determinants of weak learning of Persian by bilingual children, two different regions were chosen, Turkish-speaking and Kurdish-speaking communities, to compare their learning of Persian at the first and second levels of elementary school. The criteria of learning was based on the syllabification of Persian words, word order in the sentence, and compound sentences. Students were taught in Persian how to recognize syllabification without letting them translate the words in their own languages and were asked to produce simple sentences in Persian in response to situational questions. Teaching methods, language relatedness with Persian, and exposure to social media programs, especially TV and radio, were the factors that were considered to affect the potential of children in learning Persian.

Keywords: bilingualism, persian, education, Literature

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Authors: Tayyaba Bibi, Jenny Ronan, Robert Hernan, Kathleen O’Rourke, Brendan McHugh, Evin McGovern, Michelle Giltrap, Gordon Chambers, James Wilson

Abstract:

Sediment contamination is a major source of ecosystem stress and has received significant attention from the scientific community. Both the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) require a robust set of tools for biological and chemical monitoring. For the MSFD in particular, causal links between contaminant and effects need to be assessed. Appropriate assessment tools are required in order to make an accurate evaluation. In this study, a range of recommended sediment bioassays and chemical measurements are assessed in a number of potentially impacted and lowly impacted locations around Ireland. Previously, assessment indices have been developed on individual compartments, i.e. contaminant levels or biomarker/bioassay responses. A number of assessment indices are applied to chemical and ecotoxicological data from the Seachange project (Project code) and compared including the metal pollution index (MPI), pollution load index (PLI) and Chapman index for chemistry as well as integrated biomarker response (IBR). The benefits and drawbacks of the use of indices and aggregation techniques are discussed. In addition to this, modelling of raw data is investigated to analyse links between contaminant and effects.

Keywords: bioassays, contamination indices, ecotoxicity, marine environment, sediments

Procedia PDF Downloads 219

Authors: Carlos Gonzalez, Neil Slatcher, Marcus Properzi, Kan Seah

Abstract:

In many underground mining operations, shotcrete is used for permanent rock support. Shotcrete thickness is a critical measure of the success of this process. 3D Laser Mapping, in conjunction with Jetcrete, has developed a 3D laser scanning system specifically for measuring the thickness of shotcrete. The system is mounted on the shotcrete spraying machine and measures the rock faces before and after spraying. The calculated difference between the two 3D surface models is measured as the thickness of the sprayed concrete. Typical work patterns for the shotcrete process required a rapid and automatic system. The scanning takes place immediately before and after the application of the shotcrete so no convergence takes place in the interval between scans. Automatic alignment of scans without targets was implemented which allows for the possibility of movement of the spraying machine between scans. Case studies are presented where accuracy tests are undertaken and automatic audit reports are calculated. The use of 3D imaging data for the calculation of shotcrete thickness is an important tool for geotechnical engineers and contract managers, and this could become the new state-of-the-art methodology for the mining industry.

Keywords: 3D imaging, shotcrete, surface model, tunnel stability

Procedia PDF Downloads 284

Authors: Wiwat Kittinaraporn, Napat Harnpornchai, Sutja Boonyachut

Abstract:

This paper deals with the application of a novel neural network technique, so-called Support Vector Machine (SVM). The objective of this study is to explore the variable and parameter of forecasting factors in the construction industry to build up forecasting model for construction quantity in Thailand. The scope of the research is to study the non-residential construction quantity in Thailand. There are 44 sets of yearly data available, ranging from 1965 to 2009. The correlation between economic indicators and construction demand with the lag of one year was developed by Apichat Buakla. The selected variables are used to develop SVM models to forecast the non-residential construction quantity in Thailand. The parameters are selected by using ten-fold cross-validation method. The results are indicated in term of Mean Absolute Percentage Error (MAPE). The MAPE value for the non-residential construction quantity predicted by Epsilon-SVR in corporation with Radial Basis Function (RBF) of kernel function type is 5.90. Analysis of the experimental results show that the support vector machine modelling technique can be applied to forecast construction quantity time series which is useful for decision planning and management purpose.

Keywords: forecasting, non-residential, construction, support vector machines

Procedia PDF Downloads 429