Search results for: sentiment shock

Authors: Aghamusa Azizov

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This study investigates the correlation between solar activity and sentiment in news media coverage, using a large-scale dataset of solar activity since 1750 and over 15 million articles from "The New York Times" dating from 1851 onwards. Employing Pearson's correlation coefficient and multiple Natural Language Processing (NLP) tools—TextBlob, Vader, and DistillBERT—the research examines the extent to which fluctuations in solar phenomena are reflected in the sentiment of historical news narratives. The findings reveal that the correlation between solar activity and media sentiment is generally negligible, suggesting a weak influence of solar patterns on the portrayal of events in news media. Notably, a moderate positive correlation was observed between the sentiments derived from TextBlob and Vader, indicating consistency across NLP tools. The analysis provides insights into the historical impact of solar activity on human affairs and highlights the importance of using multiple analytical methods to understand complex relationships in large datasets. The study contributes to the broader understanding of how extraterrestrial factors may intersect with media-reported events and underlines the intricate nature of interdisciplinary research in the data science and historical domains.

Keywords: solar activity correlation, media sentiment analysis, natural language processing, historical event patterns

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Authors: Ivana Lolic, Petar Soric, Mirjana Cizmesija

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Based on Business and Consumer Survey (BCS) data, the European Commission (EC) regularly publishes the monthly Economic Sentiment Indicator (ESI) for each EU member state. ESI is conceptualized as a leading indicator, aimed ad tracking the overall economic activity. In calculating ESI, the EC employs arbitrarily chosen weights on 15 BCS response balances. This paper raises the predictive quality of ESI by applying nonlinear programming to find such weights that maximize the correlation coefficient of ESI and year-on-year GDP growth. The obtained results show that the highest weights are assigned to the response balances of industrial sector questions, followed by questions from the retail trade sector. This comes as no surprise since the existing literature shows that the industrial production is a plausible proxy for the overall Croatian economic activity and since Croatian GDP is largely influenced by the aggregate personal consumption.

Keywords: business and consumer survey, economic sentiment indicator, leading indicator, nonlinear optimization with constraints

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Authors: Ravinder Singh, C Rajesh, Saroj Badhan, Shailendra Mishra, Ranjit Singh Kataria

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Heat shock protein 60 and 70 are crucial chaperones that guide appropriate folding of denatured proteins under heat stress conditions. HSP60 and HSP70 provide assistance in correct folding of a multitude of denatured proteins. The heat shock factors are the family of some transcription factors which controls the regulation of gene expression of proteins involved in folding of damaged or improper folded proteins during stress conditions. Under normal condition heat shock proteins bind with HSF-1 and act as its repressor as well as aids in maintaining the HSF-1’s nonactive and monomeric confirmation. The experimental protein structure for all these proteins in Bubalus bubalis is not known till date. Therefore computational approach was explored to identify three-dimensional structure analysis of all these proteins. In this study, an extensive in silico analysis has been performed including sequence comparison among species to comparative modeling of Bubalus bubalis HSP60, HSP70 and HSF-1 protein. The stereochemical properties of proteins were assessed by utilizing several scrutiny bioinformatics tools to ensure model accuracy. Further docking approach was used to study interactions between Heat shock proteins and HSF-1.

Keywords: Bubalus bubalis, comparative modelling, docking, heat shock protein

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Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

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Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision-making has not been far-fetched. Proper classification of this textual information in a given context has also been very difficult. As a result, we decided to conduct a systematic review of previous literature on sentiment classification and AI-based techniques that have been used in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that can correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy by assessing different artificial intelligence techniques. We evaluated over 250 articles from digital sources like ScienceDirect, ACM, Google Scholar, and IEEE Xplore and whittled down the number of research to 31. Findings revealed that Deep learning approaches such as CNN, RNN, BERT, and LSTM outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also necessary for developing a robust sentiment classifier and can be obtained from places like Twitter, movie reviews, Kaggle, SST, and SemEval Task4. Hybrid Deep Learning techniques like CNN+LSTM, CNN+GRU, CNN+BERT outperformed single Deep Learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of sentiment analyzer development due to its simplicity and AI-based library functionalities. Based on some of the important findings from this study, we made a recommendation for future research.

Keywords: artificial intelligence, natural language processing, sentiment analysis, social network, text

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Authors: Kun Xue, Lvlan Miu, Jiarui Li

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Jetting structures are widely found in particle rings or shells dispersed by the central explosion. In contrast, some explosive dispersal of particles only results in a dispersed cloud without distinctive structures. Employing the coupling method of the compressible computational fluid mechanics and discrete element method (CCFD-DEM), we reveal the underlying physics governing the formation of the jetting structure, which is related to the competition between the shock compaction and gas infiltration, two major processes during the shock interaction with the granular media. If the shock compaction exceeds the gas infiltration, the discernable jetting structures are expected, precipitated by the agglomerates of fast-moving particles induced by the heterogenous network of force chains. Otherwise, particles are uniformly accelerated by the interstitial flows, and no distinguishable jetting structures are formed. We proceed to devise the phase map of the jetting formation in the space defined by two dimensionless parameters which characterize the timescales of the shock compaction and the gas infiltration, respectively.

Keywords: compressible multiphase flows, DEM, granular jetting, pattern formation

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Authors: Thiago Victor Cordeiro Marcos, Joao Felipe de Araujo Martos, Ronaldo de Lima Cardoso, David Romanelli Pinto, Paulo Gilberto de Paula Toro, Israel da Silveira Rego, Antonio Carlos de Oliveira

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Currently, the use of 3D rapid prototyping, also known as 3D printing, has been investigated by some universities around the world as an innovative technique, fast, flexible and cheap for a direct plastic models manufacturing that are lighter and with complex geometries to be tested for hypersonic shock tunnel. Initially, the purpose is integrated prototyped parts with metal models that actually are manufactured through of the conventional machining and hereafter replace them with completely prototyped models. The mechanical design models to be tested in hypersonic shock tunnel are based on conventional manufacturing processes, therefore are limited forms and standard geometries. The use of 3D rapid prototyping offers a range of options that enables geometries innovation and ways to be used for the design new models. The conception and project of a prototyped model for hypersonic shock tunnel should be rethought and adapted when comparing the conventional manufacturing processes, in order to fully exploit the creativity and flexibility that are allowed by the 3D prototyping process. The objective of this paper is to compare the conception and project of a 3D rapid prototyping model and a conventional machining model, while showing the advantages and disadvantages of each process and the benefits that 3D prototyping can bring to the manufacture of models to be tested in hypersonic shock tunnel.

Keywords: 3D printing, 3D prototyping, experimental research, hypersonic shock tunnel

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Authors: Etsuo Morishita

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In this paper, we show shallow water in a tin box as an analogous simulation tool for high-speed aerodynamics education and research. It is customary that we use a water tank to create shallow water flow. While a flow in a water tank is not necessarily uniform and is sometimes wavy, we can visualize a clear supercritical flow even when we move a body manually in stationary water in a simple shallow tin box. We can visualize a blunt shock wave around a moving circular cylinder together with a shock pattern around a diamond airfoil. Another interesting analogous experiment is a hydrodynamic shock tube with water and tea. We observe the contact surface clearly due to color difference of the two liquids those are invisible in the real gas dynamics experiment. We first revisit the similarities between high-speed aerodynamics and shallow water hydraulics. Several educational and research experiments are then introduced for engineering students. Shallow water experiments in a tin box simulate properly the high-speed flows.

Keywords: aerodynamics compressible flow, gas dynamics, hydraulics, shock wave

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Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad

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As a result of the growth of the web, people are able to express their views and opinions. They can now post reviews of products at merchant sites and express their views on almost anything in internet forums, discussion groups, and blogs. Therefore, the number of product reviews has grown rapidly. The large numbers of reviews make it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). For sentiment classification, most existing methods utilize a list of opinion words whereas this paper proposes a fuzzy approach for evaluating sentiments expressed in customer product reviews, to predict the strength levels (e.g. very weak, weak, moderate, strong and very strong) of customer product reviews by combinations of adjective, adverb and verb. The proposed fuzzy approach has been tested on eight benchmark datasets and obtained 74% accuracy, which leads to help the organization with a more clear understanding of customer's behavior in support of business planning process.

Keywords: fuzzy logic, customer product review, sentiment analysis

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Sergio N. P. Laitón, Paulo G. P. Toro, João F. Martos

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A numerical study has been carried out to investigate the flow characteristics and performance of the 14-X B inlet with blunted cowl-lip. The Brazilian aerospace hypersonic vehicle 14-X B is a technology demonstrator of a hypersonic air-breathing propulsion system, based on supersonic combustion ramjet (scramjet). It is designed for Earth's atmospheric flight at Mach number of 6 and an altitude of 30 km. Currently, it is under development in the aerothermodynamics and hypersonic Professor Henry T. Nagamatsu laboratory at Advanced Studies Institute (IEAv). Numerical simulations were conducted at nominal freestream Mach number and altitude for two cowl-lip blunting radius and several angles of attack close to horizontal flight. The results show that the shock interference behavior on the blunted cowl-lip change with the angle of attack and blunted radius. The type VI or V together with III shock interferences are more likely to occur simultaneously at small negative angles of attack. When the inlet operates in positive angles of attack higher to 1, no shock interference occurs, only the bow shock conditions. The results indicate a high air pressure at beginning of the combustor and higher pressure recovery with 2 mm radius and positives angles of attack.

Keywords: blunted cowl-lip, hypersonic inlet, inlet unstart, shock interference

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Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Darma Putra Sitepu, Dewi Larasati, Yohanes Wolter Hendrik George

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Sepsis is a life-threatening medical emergency frequently observed in intensive care unit (ICU). Surviving Sepsis Campaign in 2018 has recommended the administration of early vasopressor in the first hour of sepsis or septic shock but has not yet included de-resuscitation protocol. De-resuscitation in acute management of septic shock is where patient received active removal of accumulated fluid. It has been proposed by some studies and ongoing clinical trials. Here we present a case with early vasopressor and de-resuscitation. Male, 27 years old presenting to the emergency room with shortness of breath, altered mental status, and widespread blisters on his body and lips started a few hours prior, after receiving non-steroidal anti-inflammatory drug through intravenous injection. Patient was hypotensive, tachycardic, and tachypneic at admission, diagnosed with Steven Johnson Syndrome with Septic Shock. Patient received fluid resuscitation, early vasopressor, and diuresis agent aimed to actively remove fluid after the initial phase of resuscitation. Patient was admitted to ICU and progressively recovering. At day-10, patient was stabilized and was transferred to general ward. Early vasopressor and de-resuscitation are beneficial for the patient.

Keywords: sepsis, shock, de-resuscitation, vasopressor, fluid, case report

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Authors: Sheng-Bo Zhang, Huan-Hao Zhang, Zhi-Hua Chen, Chun Zheng

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In this paper, the Richtmyer-Meshkov instability has been studied numerically by using the high-resolution Roe scheme based on the two-dimensional unsteady Euler equation, which was caused by the interaction between shock wave and the helium circular light gas cylinder with different component distributions. The numerical results further discuss the deformation process of the gas cylinder, the wave structure of the flow field and quantitatively analyze the characteristic dimensions (length, height, and central axial width) of the gas cylinder, the volume compression ratio of the cylinder over time. In addition, the flow mechanism of shock-driven interface gas mixing is analyzed from multiple perspectives by combining it with the flow field pressure, velocity, circulation, and gas mixing rate. Then the effects of different initial component distribution conditions on interface instability are investigated. The results show when the diffusion interface transit to the sharp interface, the reflection coefficient gradually increases on both sides of the interface. When the incident shock wave interacts with the cylinder, the transmission of the shock wave will transit from conventional transmission to unconventional transmission. At the same time, the reflected shock wave is gradually strengthened, and the transmitted shock wave is gradually weakened, which leads to an increase in the Richtmyer-Meshkov instability. Moreover, the Atwood number on both sides of the interface also increases as the diffusion interface transit to the sharp interface, which leads to an increase in the Rayleigh-Taylor instability and the Kelvin-Helmholtz instability. Therefore, the increase in instability will lead to an increase the circulation, resulting in an increase in the growth rate of gas mixing rate.

Keywords: shock wave, He light cylinder, Richtmyer-Meshkov instability, Gaussian distribution

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Authors: Cindy Agyemang

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This study seeks to find out if racial sentiment toward immigrants still matters in the United States with COVID-19 present. It is argued that previous studies on immigration and racial attitudes or race conducted do not consider how health-related pandemics influence public opinion on immigration and the racial attitudes of people during severe health-related pandemics. In doing so, this paper hypothesizes that respondents' racial sentiment towards immigrants during this pandemic will influence their views on opposing immigration, those that believe the president handled cases on COVID-19 better are more likely to oppose immigration, and party affiliation affects respondents' views on immigration and COVID-19. For testing these hypotheses, the 2012, 2016, and 2020 American National Election Studies data was used. In accordance with the expectations of this study, it was observed that there was a statistically significant relationship between all my estimated models. This paper concludes that racial sentiment toward immigrants still matters even more in the United States, especially with the existence of health-related pandemics.

Keywords: COVID-19, immigration, racial attitudes, partisanship

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Authors: Victor Radich, Tania Basso, Regina Moraes

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Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis or opinion mining can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results obtained so far have shown that it is possible to extract data from social networks and combine the techniques for a more complete classification.

Keywords: lead qualification, sentiment analysis, opinion mining, machine learning, CRM, lead scoring

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: M. Madheswaran, A. R. Prashant, S. Ramakrishna, V. Ramesh Naidu, P. Govindan, P. Aravindakshan

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Shock Response spectrum (SRS) tests are one of the tests that are conducted on some critical systems of spacecraft as part of environmental testing. The SRS tests are conducted to simulate the pyro shocks that occur during launch phases as well as during deployment of spacecraft appendages. Some of the methods to carryout SRS tests are pyro technique method, impact hammer method, drop shock method and using electro dynamic shakers. The pyro technique, impact hammer and drop shock methods are open loop tests, whereas SRS testing using electrodynamic shaker is a controlled closed loop test. SRS testing using electrodynamic shaker offers various advantages such as simple test set up, better controllability and repeatability. However, it is important to devise a a proper test methodology so that safety of the electro dynamic shaker and that of test specimen are not compromised. This paper discusses the challenges that are involved in conducting SRS tests, shaker validation and the necessary precautions to be considered. Approach involved in choosing various test parameters like synthesis waveform, spectrum convergence level, etc., are discussed. A case study of SRS test conducted on an optical payload of Indian Geo stationary spacecraft is presented.

Keywords: maxi-max spectrum, SRS (shock response spectrum), SDOf (single degree of freedom), wavelet synthesis

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Authors: Anupoju Rajeev, Joanne Mathew, Amit Shelke

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In the current study, a new type of Composite Structural Insulated Panels (CSIPs) is developed and investigated its performance against shock loading which can replace the conventional wooden structural materials. The CSIPs is made of Fibre Cement Board (FCB)/aluminum as the facesheet and the expanded polystyrene foam as the core material. As tornadoes are very often in the western countries, it is suggestable to monitor the health of the CSIPs during its lifetime. So, the composite structure is installed with three smart sensors located randomly at definite locations. Each smart sensor is fabricated with an embedded half stainless phononic crystal sensor attached to both ends of the nylon shaft that can resist the shock and impact on facesheet as well as polystyrene foam core and safeguards the system. In addition to the granular crystal sensors, the accelerometers are used in the horizontal spanning and vertical spanning with a definite offset distance. To estimate the health and damage of the CSIP panel using granular crystal sensor, shock wave loading experiments are conducted. During the experiments, the time of flight response from the granular sensors is measured. The main objective of conducting shock wave loading experiments on the CSIP panels is to study the effect and the sustaining capacity of the CSIP panels in the extreme hazardous situations like tornados and hurricanes which are very common in western countries. The effects have been replicated using a shock tube, an instrument that can be used to create the same wind and pressure intensity of tornado for the experimental study. Numerous experiments have been conducted to investigate the flexural strength of the CSIP. Furthermore, the study includes the damage detection using three smart sensors embedded in the CSIPs during the shock wave loading.

Keywords: composite structural insulated panels, damage detection, flexural strength, sandwich structures, shock wave loading

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Authors: G. C. Joshi, M. Paul, B. K. Kalita, V. Ranga, J. S. Rawat, P. S. Rawat

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Being a habitat of the global village, every place has established connection through the strength and power of social media piercing through the political boundaries. Social media is a digital platform, where people across the world can interact as it has advantages of being universal, anonymous, easily accessible, indirect interaction, gathering and sharing information. The power of social media lies in the intensity of sharing extreme opinions or feelings, in contrast to the personal interactions which can be easily mapped in the form of Sentiment Mapping. The easy access to social networking sites such as Facebook, Twitter and blogs made unprecedented opportunities for citizens to voice their opinions loaded with dynamics of emotions. These further influence human thoughts where social media plays a very active role. A recent incident of public importance was selected as a case study to map the sentiments of people through Twitter. Understanding those dynamics through the eye of an ordinary people can be challenging. With the help of R-programming language and by the aid of GIS techniques sentiment maps has been produced. The emotions flowing worldwide in the form of tweets were extracted and analyzed. The number of tweets had diminished by 91 % from 25/08/2017 to 31/08/2017. A boom of sentiments emerged near the origin of the case, i.e., Delhi, Haryana and Punjab and the capital showed maximum influence resulting in spillover effect near Delhi. The trend of sentiments was prevailing more as neutral (45.37%), negative (28.6%) and positive (21.6%) after calculating the sentiment scores of the tweets. The result can be used to know the spatial distribution of digital penetration in India, where highest concentration lies in Mumbai and lowest in North East India and Jammu and Kashmir.

Keywords: sentiment mapping, digital literacy, GIS, R statistical language, spatio-temporal

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Authors: Tettey Afi Pamela, Sotaro Fujii, Hidetoshi Saito, Kawaii Koichiro

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Introduction: Organisms employ adaptive mechanisms when faced with any stressor or risk of being wiped out. This has made it possible for them to survive in harsh environmental conditions such as increasing temperature, low pH, and anoxia. Some of the mechanisms they utilize include the expression of heat shock proteins, synthesis of cryoprotectants, and anhydrobiosis. Heat shock proteins (HSPs) have been widely studied to determine their involvement in stress tolerance among various organism, of which chironomid species have been no exception. We examined the survival and expression of genes encoding five (5) heat shock proteins (HSP70, HSP67, HSP60, HSP27, and HSP23) from Chironomus sulfurosus larvae reared from 1st instar at 25°C, 30°C, 35°C, and 40°C. Results: The highest survival rate was recorded at 30°C, followed by 25°C, then 35°C. Only a small percentage of C. sulfurosus survived at 40°C (14.5%). With regards to HSPs expression, some HSPs responded to an increase in high temperature. The relative expression levels were lowest at 30°C for HSP70, HSP60, HSP27, and HSP23. At 25°C and 40°C, HSP70, HSP67, HSP60, HSP27, and HSP23 had the highest expression. At 35°C, all had the lowest expression. Discussion: The expression of heat shock proteins varies from one species to another. We designated the genes HSP 70, HSP 67, HSP 60, HSP 27, and HSP 23 genes based on transcriptome analysis of C. sulfurosus. Our study can be termed as a long-heat shock study as C. sulfurosus was reared from the first instar to the fourth instar, and this might have led to a continuous induction of HSPs at 25°C. 40°C had the lowest survival but highest HSPs expression as C. sulfurosus larvae had to utilize HSPs for sustenance. These results and future high-throughput studies at both the transcriptome and proteome level will improve the information needed to predict the future geographic distribution of these species within the context of global warming.

Keywords: chironomid, heat shock proteins, high temperature, heat shock protein expression

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: N. Moradian, E. Timofeev, R. Tahir

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In this work, startability of the Busemann intake family with weak/strong conical shock, as most efficient intakes, via overboard mass spillage method is theoretically analyzed. Masterix and Candifix codes are used to numerically simulate few models of this type of intake and verify the theoretical results. Portions of the intake corresponding to various flow capture angles are considered to have mass spillage in the starting process of this intake. This approach allows for overboard mass spillage via a V-shaped slot with the tip of V coinciding with the focal point of the Busemann flow. The theoretical results, achieved using two different theories, of self-started Busemann takes with weak/strong conical shock show that significant improve in intake startability using overboard spillage technique. The starting phenomena of Busemann intakes with weak conical shock and seven different capture angles are numerically simulated at freestream Mach number of 3 to find the minimum area ratios of self-started intakes. The numerical results confirm the theoretical ones achieved by authors.

Keywords: Busemann intake, conical shock, overboard spillage, startability

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Authors: R. Haoui

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The purpose of this work is to simulate the flow at the exit of Vulcan 1 engine of European launcher Ariane 5. The geometry of the propellant nozzle is already determined using the characteristics method. The pressure in the outlet section of the nozzle is less than atmospheric pressure on the ground, causing the existence of oblique and normal shock waves at the exit. During the rise of the launcher, the atmospheric pressure decreases and the shock wave disappears. The code allows the capture of shock wave at exit of nozzle. The numerical technique uses the Flux Vector Splitting method of Van Leer to ensure convergence and avoid the calculation instabilities. The Courant, Friedrichs and Lewy coefficient (CFL) and mesh size level are selected to ensure the numerical convergence. The nonlinear partial derivative equations system which governs this flow is solved by an explicit unsteady numerical scheme by the finite volume method. The accuracy of the solution depends on the size of the mesh and also the step of time used in the discretized equations. We have chosen in this study the mesh that gives us a stationary solution with good accuracy.

Keywords: finite volume, lunchers, nozzles, shock wave

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Authors: Shenghong Huang, Weirong Wang, Xisheng Luo, Xinzhu Li, Xinwen Zhao

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Understanding of material mixing induced by Richtmyer-Meshkov instability (RMI) at extreme shock compressing conditions (high energy density environment: P >> 100GPa, T >> 10000k) is of great significance in engineering and science, such as inertial confinement fusion(ICF), supersonic combustion, etc. Turbulent mixing induced by RMI is a kind of complex fluid dynamics, which is closely related with hydrodynamic conditions, thermodynamic states, material physical properties such as compressibility, strength, surface tension and viscosity, etc. as well as initial perturbation on interface. For phenomena in ordinary thermodynamic conditions (low energy density environment), many investigations have been conducted and many progresses have been reported, while for mixing in extreme thermodynamic conditions, the evolution may be very different due to ionization as well as large difference of material physical properties, which is full of scientific problems and academic interests. In this investigation, the first principle based molecular dynamic method is applied to study metal Lithium and gas Hydrogen (Li-H2) interface mixing in micro/meso scale regime at different shock compressing loading speed ranging from 3 km/s to 30 km/s. It's found that, 1) Different from low-speed shock compressing cases, in high-speed shock compresing (>9km/s) cases, a strong acceleration of metal/gas interface after strong shock compression is observed numerically, leading to a strong phase inverse and spike growing with a relative larger linear rate. And more specially, the spike growing rate is observed to be increased with shock loading speed, presenting large discrepancy with available empirical RMI models; 2) Ionization is happened in shock font zone at high-speed loading cases(>9km/s). An additional local electric field induced by the inhomogeneous diffusion of electrons and nuclei after shock font is observed to occur near the metal/gas interface, leading to a large acceleration of nuclei in this zone; 3) In conclusion, the work of additional electric field contributes to a mechanism of RMI in micro/meso scale regime at extreme shock compressing conditions, i.e., a Rayleigh-Taylor instability(RTI) is induced by additional electric field during RMI mixing process and thus a larger linear growing rate of interface spike.

Keywords: ionization, micro/meso scale, material mixing, shock

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Authors: Richard Renou, Laurent Soulard

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Lasers are widely used in glass material processing, from waveguide fabrication to channel drilling. The gradual damage of glass optics under UV lasers is also an important issue to be addressed. Glass materials (including metallic glasses) can undergo a permanent densification under laser-induced shock loading. Despite increased interest on interactions between laser and glass materials, little is known about the structural mechanisms involved under shock loading. For example, the densification process in silica glasses occurs between 8 GPa and 30 GPa. Above 30 GPa, the glass material returns to the original density after relaxation. Investigating these unusual mechanisms in silica glass will provide an overall better understanding in glass behaviour. Non-Equilibrium Molecular Dynamics simulations (NEMD) were carried out in order to gain insight on the silica glass microscopic structure under shock loading. The shock was generated by the use of a piston impacting the glass material at high velocity (from 100m/s up to 2km/s). Periodic boundary conditions were used in the directions perpendicular to the shock propagation to model an infinite system. One-dimensional shock propagations were therefore studied. Simulations were performed with the STAMP code developed by the CEA. A very specific structure is observed in a silica glass. Oxygen atoms around Silicon atoms are organized in tetrahedrons. Those tetrahedrons are linked and tend to form rings inside the structure. A significant amount of empty cavities is also observed in glass materials. In order to understand how a shock loading is impacting the overall structure, the tetrahedrons, the rings and the cavities were thoroughly analysed. An elastic behaviour was observed when the shock pressure is below 8 GPa. This is consistent with the Hugoniot Elastic Limit (HEL) of 8.8 GPa estimated experimentally for silica glasses. Behind the shock front, the ring structure and the cavity distribution are impacted. The ring volume is smaller, and most cavities disappear with increasing shock pressure. However, the tetrahedral structure is not affected. The elasticity of the glass structure is therefore related to a ring shrinking and a cavity closing. Above the HEL, the shock pressure is high enough to impact the tetrahedral structure. An increasing number of hexahedrons and octahedrons are formed with the pressure. The large rings break to form smaller ones. The cavities are however not impacted as most cavities are already closed under an elastic shock. After the material relaxation, a significant amount of hexahedrons and octahedrons is still observed, and most of the cavities remain closed. The overall ring distribution after relaxation is similar to the equilibrium distribution. The densification process is therefore related to two structural mechanisms: a change in the coordination of silicon atoms and a cavity closing. To sum up, non-equilibrium molecular dynamics were carried out to investigate silica behaviour under shock loading. Analysing the structure lead to interesting conclusions upon the elastic and the densification mechanisms in glass materials. This work will be completed with a detailed study of the mechanism occurring above 30 GPa, where no sign of densification is observed after the material relaxation.

Keywords: densification, molecular dynamics simulations, shock loading, silica glass

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Authors: Song L. Yao, Ji D. Yu, Xiao Y. Pei

Abstract:

An explanation is introduced to study the quasi-elastic release phenomenon in shock compressed aluminum. A dislocation-based model, taking into account of dislocation substructures and evolutions, is applied to simulate the elastic-plastic response of both single crystal and polycrystalline aluminum. Simulated results indicate that dislocation immobilization during dynamic deformation results in a smooth increase of yield stress, which leads to the quasi-elastic release. While the generation of dislocations caused by plastic release wave results in the appearance of transition point between the quasi-elastic release and the plastic release in the profile. The quantities of calculated shear strength and dislocation density are in accordance with experimental result, which demonstrates the accuracy of our simulations.

Keywords: dislocation density, quasi-elastic release, wave profile, shock wave

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Authors: X. Wang, T. J. Craft, H. Iacovides

Abstract:

When handling the near-wall regions of turbulent flows, it is necessary to account for the viscous effects which are important over the thin near-wall layers. Low-Reynolds- number turbulence models do this by including explicit viscous and also damping terms which become active in the near-wall regions, and using very fine near-wall grids to properly resolve the steep gradients present. In order to overcome the cost associated with the low-Re turbulence models, a more advanced wall function approach has been implemented within OpenFoam and tested together with a standard log-law based wall function in the prediction of flows which involve 2-D shock wave/turbulent boundary layer interactions (SWTBLIs). On the whole, from the calculation of the impinging shock interaction, the three turbulence modelling strategies, the Lauder-Sharma k-ε model with Yap correction (LS), the high-Re k-ε model with standard wall function (SWF) and analytical wall function (AWF), display good predictions of wall-pressure. However, the SWF approach tends to underestimate the tendency of the flow to separate as a result of the SWTBLI. The analytical wall function, on the other hand, is able to reproduce the shock-induced flow separation and returns predictions similar to those of the low-Re model, using a much coarser mesh.

Keywords: SWTBLIs, skin-friction, turbulence modeling, wall function

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Authors: Mohsen Farhadloo, Majid Farhadloo

Abstract:

Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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Authors: K. Azimzadeh, S. Rasouli

Abstract:

The present study investigates whether malondialdehyde (MDA) and heat shock protein-27 (HSP-27) are altered in sheep with cystic echinococcosis (CE). For this purpose, forty parasitized and thirty healthy sheep were selected based on severe cystic form observation in liver and lack of blood parasite along with no cystic conformation in carcass respectively. The results revealed a significant decrease (p<0.01) in albumin (Alb) and total plasma protein (TPP) and a significant increase (p<0.01) in HSP-27, MDA, total bilirubin and unconjugated bilirubin in the infected group compared with healthy ones.The results indicate low levels of TPP and Alb reveal liver damage in suffered sheep and MDA elevation demonstrates oxidative stress in infected group. In addition, HSP-27 enhancement may attribute to disease-induced stress conditions.

Keywords: malondialdehyde, heat shock protein-27, Echinococcosis, blood parasites

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Authors: Amy Heaps, Amy Burns, Una McMahon-Beattie

Abstract:

Shock and fear tactics have been used to encourage consumer behaviour change within the UK regarding lifestyle choices such as smoking and alcohol abuse, yet such measures have not been applied to food labels to encourage healthier purchasing decisions. Obesity levels are continuing to rise within the UK, despite efforts made by government and charitable bodies to encourage consumer behavioural changes, which will have a positive influence on their fat, salt, and sugar intake. We know that taking extreme measures to shock consumers into behavioural changes has worked previously; for example, the anti-smoking television adverts and new standardised cigarette and tobacco packaging have reduced the numbers of the UK adult population who smoke or encouraged those who are currently trying to quit. The USA has also introduced new front-of-pack labelling, which is clear, easy to read, and includes concise health warnings on products high in fat, salt, or sugar. This model has been successful, with consumers reducing purchases of products with these warning labels present. Therefore, investigating if shock labels would have an impact on UK consumer behaviour and purchasing decisions would help to fill the gap within this research field. This study aims to develop an understanding of consumer’s initial responses to shock advertising with an interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes and will achieve this through a mixed methodological approach taken with a sample size of 25 participants ages ranging from 22 and 60. Within this research, shock mock labels were developed, including a graphic image, health warning, and get-help information. These labels were made for products (available within the UK) with large market shares which were high in either fat, salt, or sugar. The use of online focus groups and mouse-tracking experiments results helped to develop an understanding of consumer’s initial responses to shock advertising with interest in the perceived impact of long-term effect shock advertising on consumer food purchasing decisions, behaviour, and attitudes. Preliminary results have shown that consumers believe that the use of graphic images, combined with a health warning, would encourage consumer behaviour change and influence their purchasing decisions regarding those products which are high in fat, salt and sugar. Preliminary main findings show that graphic mock shock labels may have an impact on consumer behaviour and purchasing decisions, which will, in turn, encourage healthier lifestyles. Focus group results show that 72% of participants indicated that these shock labels would have an impact on their purchasing decisions. During the mouse tracking trials, this increased to 80% of participants, showing that more exposure to shock labels may have a bigger impact on potential consumer behaviour and purchasing decision change. In conclusion, preliminary results indicate that graphic shock labels will impact consumer purchasing decisions. Findings allow for a deeper understanding of initial emotional responses to these graphic labels. However, more research is needed to test the longevity of these labels on consumer purchasing decisions, but this research exercise is demonstrably the foundation for future detailed work.

Keywords: consumer behavior, decision making, labelling legislation, purchasing decisions, shock advertising, shock labelling

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