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Volume 09, Issue 02 (February 2020)
Emotion AI using Sectional Textual Repercussion
DOI : http://dx.doi.org/10.17577/IJERTV9IS020017
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A. Kumar , K. Naveen , Dr. B. Rama Subba Reddy, 2020, Emotion AI using Sectional Textual Repercussion, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 09, Issue 02 (February 2020),
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Authors : A. Kumar , K. Naveen , Dr. B. Rama Subba Reddy
Paper ID : IJERTV9IS020017
Volume & Issue : Volume 09, Issue 02 (February 2020)
Published (First Online): 06-02-2020
ISSN (Online) : 2278-0181
Publisher Name : IJERT
License: This work is licensed under a Creative Commons Attribution 4.0 International License
1A. Kumar, 2K. Naveen, 3Dr. B. Rama Subba Reddy
1,2Assistant Professor, Computer Science and Engineering, SV College of Engineering, Tirupati.
3Professor, Computer Science and Engineering, SV Engineering College, Tirupati.
AbstractThe internet is a puddle f raw data in the form of social multimedia or text messages, blogs, tweets, etc. – irregular and connectionless. The data becomes information on if it is pre-processed. A survey from the literature, we recognized that the present Emotional analysis tools are moderate, bulky and computationally heavy which makes the task at hand inefficient. Therefore, to overcome the aforementioned problem of analyzing sentiments efficiently, a new method is proposed in the present paper to drive the task of Sentiment Analysis by exploiting the idea of Partial Textual Entailment. We propose to use Partial Textual Entailment for measuring semantic similarity between the tweets so as to group similar tweets together. The method is anticipated to reduce the burden of sentiment analyzer and makes the processing faster. Moreover, we also propose a modification in an existing method of Partial Textual Entailment which can be further adopted for many Natural Language Processing applications.
Keywords Sentiment Analysis, Textual Entailment, Partial Textual Entailment.
In todays era of the ongoing digital revolution, one can find a plethora of textual content on social websites, microblogging websites, etc. The bite-sized messages allow users to voice opinions, exchange views on current affairs and post reviews – positive or negative – of routinely used products/services. Now a days, corporations also view social websites, microblogging websites, etc. as an important channel to gauge public sentiment for their product/services. Many corporations have teams dedicated to addressing user reactions. This has opened up the domain of holistic technology-driven sentiment analysis.
Levy et al [1] describe sentiment analysis as the study of determining polarity of a sentiment. The task of Sentiment Analysis includes finding the emotion, attitude, view or opinion of a person towardsanother person, object, product or event [2][3] which has become useful in areas like academics, business and industry. These extracted emotions, views or opinions offer the capability to provide accurate views on various applications in different fields. Social media sites like Facebook or Twitter have become a popular channel to perform analysis on shared opinion. Therefore, it can be said that Sentiment Analysis identifies the sentiment or feelings of a person in a domain. It helps to review a personssatisfaction or dis-satisfaction whereas Opinion Mining[4] is used to identify opinion or views of a person in a domain. It helps to review a persons satisfaction or dis-satisfaction. The task of Sentiment Analysis can be classified on the basis of different classes – it can be analyzed as a positive, negative or neutral
sentiment based on classes [5].
Positive Sentiment Analysis: If the document expresses positive views about an entity, the polarity of the document is said to be positive. Polarity can also be determined for sentences or aspects of sentences. For example: The fragrance of the flowers is good. In this sentence fragrance can be considered as an aspect of the flower and good indicates the positive view about the fragrance of the flower.
Negative Sentiment Analysis: If the document expresses negative views about an entity, the polarity of the document is said to be negative. For example: The toppings on the pizza were rotten. In this sentence the toppings are considered as an aspect of the pizza and rotten indicates the negative view about the toppings of the pizza.
Neutral Sentiment Analysis: If the sentence or document is unable to give a positive or a negative view, its polarity is said to be neutral. For example: He went to buy some products from the market.
Sentiment Analysis can be further classified on the basis of different granularity of text. It can be classified at document level, sentence level or aspect level [5] which is briefly discussed below
Document Level Sentiment Analysis: It analyses the content of the document as a whole for finding its polarity.
Sentence Level Sentiment Analysis: It takes into account different sentences of a document by further breaking them into smaller chunks of words for analyzing its polarity.
Word Level Sentiment Analysis: It determines the polarity of different words of a sentence with relation to some object or event.
With the ever increasing number of social media posts and tweets, it has become a challenging issue to accomplish the task of analyzing all reviews within reasonable time lines. It has become extremely important to categorize similar views so as to reduce computation burden on the organization. In order to reduce the above said issues, this paper proposes the use of Textual Entailment in the process of Sentiment Analysis. Textual Entailment is defined [6] as a directional relationship between two text snippets denoted as Text (T) and Hypothesis (H) It is a process of checking whether H can be concluded from T or not.
Through the Literature survey, the authors have found that TE has been used for redundancy detection by Lloret et al. [7]. This has motivated the authors in this paper to use it in task of Sentiment Analysis as well. TE is also considered as a notion that is used to check semantic inference between text expressions using syntax-based, semantic-based and hybrid methods [8]. The task of TE has been carried forward using various approaches like the bag of words, vectors and directional tree methods.
During the last few years TE has become a popular topic of interest in the area of Natural Language Processing (NLP) including student response analysis, document summarization, machine translation evaluation, paraphrase recognition etc. [9]. Ideally, the authors are not able to accurately measure the inference using TE because of many reasons like the complexity of sentences and limitations of existing linguistic resources. Therefore, a need of Partial Textual Entailment (PTE) has been felt that measures the level of entailment whether the text fully entails the hypothesis or not. The authors plan to employ Partial Textual Entailment (PTE) to improve the task of Sentiment Analysis in this paper. It is expected to reduce the amount of work done in analyzing the sentiment of text thereby providing a better solution for the task of SA.
The following paper is outlined as follows: the related work in the field of Sentiment Analysis and Textual Entailment has been discussed in Section 2, Partial Textual Entailment is introduced and discussed in Section 3, the proposed methodology for Sentiment Analysis is proposed in Section 4, conclusion and future work are laid down in Section 5.
Sentiment Analysis has been performed over the years and different models have come into existence. Classifiers using machine learning have been developed to generate polarity of a sentiment on the document level [10]. An algorithm to analyze the semantic arrangement of phrases using Point-wise Mutual Information (PMI) score has been developed[11]. A number of techniques have been used and have evolved over time for the sentiment analysis on data, video and audio [12][13]. NLP based techniques have been used for customer reviews to provide feature-based summaries [14. NLP techniques have been used to mine the opinion for a product from the web and generate the polarity of expression [15]. A machine learning algorithm has been proposed to calculate polarity of expression using sentiment analysis on phrase level [16]. An unsupervised system has been developed for the extraction of feature based summaries for customer reviews [14][17]. PMI score has been calculated to conclude if a noun can be used as a feature of a product review. The two scoring methods Latent Semantic Analysis (LSA) and PMI are tested using two different corpora to conclude LSA approach to be more accurate in semantic orientation classification[18].
In this paper the authors propose a framework for determination of the polarity of text using the flexibility of Partial Textual Entailment (PTE). The authors suggest the modification over the existing facets generation method in the proposed framework to reduce computations in Sentiment Analysis..
The next section will discuss limitation of Textual Entailment and introduce Partial Textual Entailment.
EMPLOYING PARTIAL TEXTUAL ENTAILMENT Recognizing Textual Entailment (RTE) is a binary
decision problem i.e. the process indicates if Text (T) entails Hypothesis (H) or not. The process can be said to be rigid and crisp [19] as the process is unable to determine the level at which T entails H [20].
To overcome the aforementioned limitations, Nielsen et al.
introduced the concept of Partial Textual Entailment (PTE) using facets. The paper reports that the concept of PTE has achieved significant improvement over baseline methods like bag of words. The idea has been further enhanced by Levy et al. [1] by using faceted PTE. In the following work, the ordered pair facets are created that are free from having semantic relationship and thereby, achieving better results.
According to Levy et al. [1] Partial Textual Entailment solved the problem of negative Textual Entailment. Text (T) partially entails Hypothesis (H) indicated that a part of hypothesis is entailed by text. For Example:
T: The Taj Mahal was constructed by Shahjahan.
H: Shahjahan constructed the Taj Mahal
T: Shahjahan constructed the Taj Mahal in Agra near the Yamuna river
Sentence (c) and (d) are an example of Partial Textual Entailment as some of the information like Agra, Yamuna River is missing. Next we are going to introduce Partial Textual Entailment and propose a method to carry out the task of recognizing entailment between text using Partial Textual Entailment.
INTRODUCTION TO PARTIAL TEXTUAL ENTAILMENT
The foundation of our work is based on recognizing Partial Textual Entailment. To develop a system for the same, it is required to introduce Faceted Partial Textual Entailment [1]. The authors are going to propose a fully automatic system of Faceted Partial Textual Entailment.
The concept of Partial Textual Entailment has been proposed by Nielsen et al. [21]. The concept has been further elaborated by Levy et al. [1] in the form of faceted Partial Textual Entailment[1]. The concept has been proposed as a solution to the rigidity and crispness of the task of Textual Entailment.
T: The main job of teachers is to educate students H: The teacher gives lectures to thestudents
A relationship can be seen in this pair of the sentences between the text(T) and the hypothesis(H) but to say there is entailment between the two would not be correct. It can be said that a relationship still exists between the two and is termed as Partial Textual Entailment i.e. a part of the hypothesis is entailed by the text.
Neilsen et al. [21] have defined the idea of facets that is in the form of ordered pair w1, w2 where w1 and w2 represent words that belong to nouns, pronouns, verbs or adjectives. The ordered pair have a semantic relationship between each other and also belong to the hypothesis. Levy et al. [1] have extended the idea by using faceted Partial Textual Entailment
– by considering the ordered pair without any semantic relationship between each other. Levy et al. [1], has suggested the following three stage framework for PTE.
Decompose the Hypothesis into Facets
The facets are generated in the form of ordered pairs from the hypothesis.
Determine whether each Facet is Entailed
The facets of the hypothesis are matched with the facets of the text to determine entailment between them.
Aggregate the Individual Facet Results and Decide on Complete Entailment Accordingly
The aggregated outcome of absolute matching of facets of hypothesis and text results in complete entailment.
The notion of faceted Partial Textual Entailment has been addressed by using the exact match method, the lexical inference method and the semantic method in literature survey [7]. Next, the authors briefly discuss theseapproaches.
Exact Match Method: All the lemma or tokens of H are contained in the bag of words. If the lemma or tokens of T are also present in the bag of words, then the decision is said to be positive. A positive decision implies T entails H. This approach has been commonly used in a number of Textual Entailment challenges.
Lexical Inference Method: The similarity between the ordered pair of T and H is estimated and measured using the Resnik Similarity Measure. A lexical based system has been represented as a model based on word overlap between the text and the hypothesis [22]. The authors have reported that the system has not been efficient and a web-based word similarity method has been given that used lexical edit distance for comparison [23].
Semantic Inference Method: Semantic entailment is
the problem of determining if the meaning of a given sentence entails that of another [24]. BIUTEE is a commonly used tool for recognizing entailment [6] where the dependency tree of facets for T and H is generated. The cost of generating H from T using a path between the ordered pair determines entailment between the two.
Using these methods and their different configurations, our methods will be checked for results.
PTE uses facets generation by creating pairs of all the words. This leads to a high number of faceted pairs and computations. The existing methods faced this major limitation. To overcome the following issues a new idea is proposed which will eventually be turned into a working method:
The existing methods generate a large number of facets that increases the amount of computation effort. This motivated the authors to the propose solution of using facets.
The existing methods of sentiment analysis require a lot of computation to generate a sentiment because the reviews are increasing daily. The integration of heavy linguistic resources like entity recognition, stemmers etc make processing and analysis of text/expressions further slower. To overcome the problem, SA is done using PTE.
The main aim of the present paper is:
To propose a modification over the existing method for the creation of facets in Partial Textual Entailment. This is done over the existing method of facets creation by Levy et al.
[1] so that the number of facets can be reduced to provide efficient results and reduced computation.
With the reduced number of text/expressions as a result of Partial Textual Entailment, the sentiment analyzer will be provided with fewer expressions. The burden of Sentiment Analyzer is reduced to the analysis of a small set of text instead of the original large set of expressions. This reduces the processing time considerably.
Lastly, the total percentage of each kind of sentiment can be determined.
To the best of our knowledge, Partial Textual Entailment has not been used anywhere for sentiment analysis till now. Therefore, the idea is:
To implement the task of faceted Partial Textual Entailment.
To use faceted Partial Textual Entailment for grouping tweets with similar polarity.
To apply a theoretical method for sentiment analysis on the tweets extracted from Partial Textual Entailment.
The method proposed will be further checked with the existing methods.
The next section discusses the proposed modification for faceted Partial Textual Entailment. It discusses the steps for generation of facets and the process of faceted PTE.
PROPOSED METHODOLOGY FOR SENTIMENT ANALYSIS The authors propose a method to carry out the task of
Sentiment Analysis that has been broken into two subtasks: (a) developing a method for recognizing PTE and (b) developing the method of Sentiment Analysis using Partial Textual Entailment.
Developing the method of Recognizing Partial Textual Entailment
The proposed idea is to develop a model to reduce computation due to a large number of facets construction and to generate efficient results. This will be done by removing helping words. The facets will only be constructed using the subject of the sentence as a primary word in the creation of facets. This method is expected to predict better Textual Entailment as the text revolves mainly around the subject of the sentence. Consider,
S: Sentence
X: Set of words in the sentence S Q: Subjects of sentences
R: Attributes of the sentence
Selecting Text and Hypothesis:
The text and hypothesis have to be selected from the reviews. For Example,
Text: Rahul goes for jogging daily. He brought some eggs today.
Hypothesis: Rahul takes good care of his health.
Refinement of Text and Hypothesis by removing helping words like of, some, for.
The helping words like stop words, prepositions are removed. Text and hypothesis are modified as
X (T): {Rahul, goes, Jogging, daily, He, brought, eggs, today}
X (H): {Rahul, takes, good, care, his, health}
Identification of the Subject where Q represents the subject and R represents the remaining words
The subjects from the sentences are selected and the remaining words are listed down separately.
Q (T): {Rahul, eggs}
R (T): {goes, Jogging, daily, He, brought, to-day}
Q (H): {Rahul}
R (H): {takes, good, care, his, health}
Selecting Text and Hypothesis
Refinement of Text and Hypothesis by removing helping word
Identification of Subject
Formation of facets
Determination for
Fig. 1. Block Diagram of Faceted Partial Textual Entailment
Formation of facets:
The facets are created by pairing remaining words with the subjects as follows:
Facet (T): Q*R = ({Rahul, goes}, {Rahul, Jogging},
{eggs,
brought} Total 12 facets
Facet (H): Q*R = ({Rahul, takes}, {Rahul, good},
{Rahul,
care} Total 5 facets
Determination of Partial Textual Entailment will be done:
In the last step, the authors have observed that the number of facets gets reduced significantly. The total number of facets generated are equal to 60(12*5 = 60). This is going to reduce the number of comparisons and thus reduce the computation required. The whole process will be applied to the tweets and the result will be countable non-similar sentences which can be easily passed to the sentiment analyzer to determine the sentiment of the collection of tweets, reviews or expressions. In addition, the number of text inputs relating to a sentiment will determine how strongly people agree or disagree to a topic. The next section discusses the flow of work i.e. an overall architecture of Sentiment Analysis using Partial Textual Entailment.
Developing a method for Sentiment Analysis using Partial Textual Entailment
The authors discuss the overall framework for SA using PTE below
Recognizing new models or methods for Partial Textual Entailment:
As discussed in Section 4.1, this step will perform the
task of grouping similar tweets so as to reduce the burden of the Sentiment Analyzer resulting in faster processing of reviews. The entailment recognition will be done using BIUTEE tool [6].
The result obtained from Step 1 will be passed to the sentiment analyzer to determine the sentiment of the text/expressions.
The total number of sentences that entail the hypothesis will then be provided as an estimator of how strong the sentiment is.
Faceted Partial Textual Entailment
Polarity and Sentiment Weightage Estimator
Sentiment Analyzer
Fig. 2. Overall Architecture of Sentiment Analysis using Faceted Partial Textual Entailment example of a figure caption.
CONCLUSION AND FUTURE WORK In the present paper the authors have proposed a
novel method of Sentiment Analysis using Partial Textual Entailment. To the best of our knowledge, it has been used for the first time in this paper for reducing the computational overhead. The authors plan to implement the proposed method of Partial Textual Entailment which is discussed in Section
IV. In future, the authors also plan to implement method of Sentiment Analysis using the proposed method of Partial Textual Entailment. The authors also plan to use the standard data sets to compute the efficacy of their proposed method in future. The authors plan to use the BIUTEE tool for the task of entailment recognition. The authors also intend to extend this work for different regional languages of thecountry.
O. Levy, T. Zesch, I. Dagan, I. Gurevych. Recognizing Partial Textual En-tailment Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, Vol 2, pp. 451- 455,2013
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H. Kaur, V. Mangat, Nidhi A survey of sentiment analysis techniques I-SMAC (IoT in Social, Mobile, Analytics and Cloud)(I- SMAC), In-ternational Conference on IEEE, 2017.
I. Guellil, K. Boukhalfa, Social big data mining: A survey focused on opinion mining and sentiments analysis Programming and Systems (ISPS), 12th International Symposium on IEEE, 2015
K. Mouthami, K. Nirmala Devi, V. Murali Bhaskaran. Sentiment analysis and classification based on textual reviews Information communi-cation and embedded systems (ICICES), international conference on IEEE, 2013
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E. Lloret, O. Ferr´andez, R. Munoz and M. Palomar, A Text Summarization Approach under the Influence of Textual Entailment Natural Language Processing and Information Systems Group, pp: 22- 31,June 2008
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I. Dagan, B. Dolan, B. Magnini And D. Roth, Recognizing Textual Entailment: Rational, evaluation and approaches erratum Natural Language Engineering, Vol 16(1) pp: 105-105, 2010
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P. D. Turney, Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews In Proceedings of the 40th annual meeting o association for computational linguistics, pp: 417424.
E. Cambria, B. Schuller, Y. Xia, Catherine, New avenues in opinion mining and sentiment analysis IEEE Intelligent Systems, Vol 28(2) pp: 1521, 2013.
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Sagae and L-P Morency. 2013. YouTube Movie
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M. Vita. Computing Semantic Textual Simi-larity Based on PartialTextual Entailment.
http://ama.liglab.fr/GreenSeminars/2015/Speechs/Diana.pdf
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Tough week- end in Paris. As thousands of protesters were in the streets to complain about whatever the Government was proposing, the NeuroChain team keeps working to stay in line with the published roadmap. The Champs Elysées where the NeuroChain offices are were kept out of trouble this week-end although the surrounding suffered from severe damages. The team is back at work this Monday and although the conversations were intense in the early morning, all got back to normal quickly. We are now one month after the Test net was delivered (31st of October). The Bug Bounty is going well and allowed a healthy teamwork between the Lead Dev. team and those of you in the community who had the technical background to install the bot.
Last week was busy for the NeuroChain team. Gold sponsor of the BLOCKCHAIN PARIS event with MICROSOFT, we picked up a lot of leads and interest. Most companies represented pitched applications available for industry usage like Supply Chain and traceability. We released 2 business applications developed by our team in preparation for the days when the NeuroChain protocol will be fully ready to be deployed. NeuroChain Tracer and NeuroChain Origin are applications built out of customers specifications. The unique value proposal is to offer a multi blockchain architecture able to mix Permission and Permission-less protocols to administer supply chain and food traceability processes. We have set follow up meetings with customers willing to deploy test environments and who are willing to explore the NeuroChain protocol when available in early 2019. Promising talks with a transportation consortium and a certification company were help to enhance the applications. One of the highlight of the event was the presentation delivered jointly with DAHER. Frédéric Goujon, our CEO, showcased a complete tracking on the blockchain of a DAHER aviation component across multiple geographies. Temperature, acceleration, timestamp and positions are logged in the blockchain and accessed via an easy to read interface.
Next stop for all of us is the #CES2019. Exciting time for all of us since it will be the first time we are exhibiting NeuroChain in the US. Last year NY was just a first step along with other events like Dubai, Seoul, Tokyo, Singapore, Berlin and Paris. Meet us at the event if you are around. Among other demonstrations, we will be proving the environmental friendly aspect of NeuroChain. The bot will be showcased running on a Raspberry. Business applications described above will be showcased too. We are looking forward seeing you there. In all cases, we will be reporting from this exciting event.


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{
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        }

        public ExecuteSqlStatementExpression(DatabaseProviders current, DatabaseProviders[] databaseProviders) : base(current, databaseProviders)
        {
        }

        public virtual string SqlStatement { get; set; }

        public override string ToString()
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        }
    }
}

redpajama_set_name: RedPajamaGithub


Originally, the idea was to pair the 1968 Paralympic Games with the Olympic Games in Mexico City. However, two years prior, the Mexican government backed out of the commitment to host the Paralympics because of technical difficulties.
As everyone wanted to keep the Paralympic Movement going, Sir Ludwig Guttmann accepted the invitation of the Israeli government and the ILAN Society (an Israeli organisation for individuals with physical impairment) to host the 1968 International Stoke Mandeville Games at Ramat Gan, near Tel Aviv.
Israel's offer to host the Games was motivated by its wish to mark the 20th anniversary of its independence.
Under the direction of Gershon Huberman, the sports programme was enlarged considerably from 1964 in Tokyo. New events such as Lawn Bowls, Women's wheelchair basketball and the 100m wheelchair race for men were introduced. Changes in the classification systems for Athletics, wheelchair basketball and swimming were also made.
The Opening Ceremony was held on 4 November at the Hebrew University Stadium in Jerusalem before a crowd of 10,000. The Games were declared open by the Deputy Prime Minister, Yigal Allon.
At age 25, Italy's Robert Marson was proclaimed the outstanding athlete of the Games. After having won two gold medals in field events in the 1964 Tokyo Games, he broadened his participation to swimming and fencing. He won an astounding 10 gold medals in 1968 – three in field events, three in swimming and four in fencing.
Australian Lorraine Dodd set three records in her classification – 25m backstroke, 25m freestyle and 25m breaststroke - all on the same day.
Ed Owen, a 20-year-old from USA, swiped two golds in athletics, two in swimming, a silver in wheelchair basketball and a bronze in javelin.
In the men's wheelchair basketball final, Israel defeated USA, 47-37, under the leadership of captain Baruch Hagai.
The Closing Ceremony, held on 13 November, took place at the Tel Aviv Fairgrounds and was attended by Deputy Prime Minister Allon.


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4bbbd60035 To play Nintendo 3DS games on your PC you need the emulator, and you need a 3DS BIOS, put the BIOS map inside the map with the emulator. And you will be able to open .3ds roms with the. The best 3DS emulator out there period. This Emulator simulates the 3D effect using anaglyph type 3D or stereoscopic 3D! Of course you can also play normal in 2D.. GameStop Corp. (known simply as GameStop) is an American video game, consumer electronics, and wireless services retailer.. Nintendo 3ds Emulator 2.9.4.zip  THIS IS A STATIC MIRROR OF USERSCRIPTS.ORG - LOGINS DO NOT WORK WARNING: SOME SCRIPTS MAY BE DANGEROUS! request removal;. Get Free Email, Chat, & Messaging.. Here you can download ps3 emulatorx bios shared files: PS3 Emulator BIOS.zip from 4shared.com 1.6 MB, rebuilt.3DS EmulatorX Bios.rar from mediafire.com 4.25 MB, PS3 Emuleitor Bios.zip from. N3DS Emulator. 2,849 likes 4 talking about this. This is our 3DS Emulator Project that allows users to play Nintendo 3DS games in their devices like.. Get Free Email, Chat, & Messaging.. Ricks 3DS Emulator Free + Bios + ROM [no More Survey].rar (zippyshare.com) Download Links - Download Ricks 3DS Emulator Free + Bios + ROM [no More Survey].rar (zippyshare.com). Reddit is also anonymous so you . This is /r/emulation - not /r/flashcarts or /r . Posts asking which games are playable/what the emulator is called/where to get .. 2012-08-28 You can choose one of the links to download 3DS Emulator v1.1.2. If there is any further question, you can post here or here.Thank you !. Get Free Email, Chat, & Messaging.. Download 3DS Emulator and enjoy Nintendo 3DS game roms using your PC or Android device. It works with Pokemon X and Y.. Here you can download 3ds emulator v2.9.4 shared files: 3DS Emulator V2.9.4 BIOS.rar from mediafire.com 51.72 KB, 3DS Emulator V2.9.4 Plugins.rar from mediafire.com .. Conctate con amigos, familiares y compaeros.. N3DS Emulator. 2,849 likes 4 talking about this. This is our 3DS Emulator Project that allows users to play Nintendo 3DS games in their devices like.. 2013-2018 UploadedTrend.com Search Engine - 3DS emulatorX + bios file info/download 3DS emulatorX + bios file info/download. 3Ds emulator is software that duplicates the graphical system and another process of a console so that allows people to play Nintendo 3Ds games on their Android or PC.. This PlayStation 3 emulator from playstation3emulator.net is the first and best emulator for PS3! They started developing 2 years ago and are still active and updating! If your looking for a. There is already a 3DS emulator, the Citra (citra-emu.org). You will need to have installed the Visual C++ Redistributable for Visual Studio 2015. Download the 64-bit version.. All you need to use this emulator is an original BIOS from a xbox 360, it is illegal to use a copy of a BIOS. .. Citra codename 'eMu3Ds' is a Nintendo 3DS emulator for playing Nintendo 3DS Games on Windows, Linux, Mac & Android.. Instructions: Step 1: Download the Bios installer Step 2: Install the Bios in the same path as the emulator Step 3: The emulator will now detect the bios files.. How to download pokemon x [3ds] and 3DSe emulator with working bios - Duration: 5:43. Dark hero - the pokemon channel 203,753 views. 5:43.. Emulatorx.info is tracked by us since February, 2013.. GameStop Corp. (known simply as GameStop) is an American video game, consumer electronics, and wireless services retailer.. Download SNES DS 0.6.a (143.1KB) for NDS. The file 'SNESDS.ZIP' can be downloaded instantly from our NDS Emulators category.. Download Bios File Rom to continue and stable playing with this emulator. Click here and more.. EmulatorX.info - Xbox 360 Emulator, PS3 Emulator and 3DS Emulator. WEB SEARCH KEYWORD ANALYZER. . 198.143.133.74.. This 3D emulator would help you to play all kinds of 3DS games in your PC. 3ds Emulator Bios V2 9 . emulator.3ds.emulator.bios.v2.9.4 . 3ds.emulator.bios.rar .. Best Answer: there still are no 3ds emulators.


Fee Range: Contact AHNA for details.
Contact Details: For a full list of speakers and topics contact the AHNA office.
The American Holistic Nurses Association (AHNA) is a specialty nursing association serving over 4,500 nurses and other holistic healthcare professionals. AHNA is well known as the definitive voice for holistic nursing through continuing education, research, practice, networking, and advocacy. The American Nurses Association recognizes Holistic Nursing as an official specialty in nursing.


but in other ways, things are humming along. One thing on my mind is the ferry dredging progress. Up front, this is my version of the events and I am not a professional concerning water issues. Hence, I have hesitated to step into this area but since this sort of transportation is essential for the Island, here goes. It has been at a steady/urgent pace over the past several weeks with what seems - to me - just two days off at Christmas. The crew from Roen Salvage are here working with their barge. An excavator and dump trucks from Mike Kahr's Death's Door Marine arrived the day after Christmas. Mike arrived last week fresh off another job on the water at Fish Creek. Okay...I just had to include this photo...I hope Mike doesn't mind...it was a Kodak moment for me. Dump trucks carry the clay,stone, sand, muck, etc. from the barge at the Potato Dock to Julian Hagens's gravel pit. A hearty, conscientious group of Islanders drive those trucks. As I recall, since New Year's, two shifts from Roen have been in place. Hauling starts around 6:30 am carrying the softer material from the night digging and continues through the day into the evening with matter from the "hardpan" portion. As an example weather-wise, this afternoon it was sunny with the winds at 24 mph with gusts of 33mph - and the crew was out there at work. I am impressed to see how many different people, groups, entities have come together to make this project possible. This spirit of teamwork is evident in other places on this Island as well. It is one reason why I have chosen to be here. I could see skim ice in Detroit Harbor as we arrived on the afternoon ferry last Thursday so time is of the essence. We were on the Washington. The weather will dictate how long the Washington and the Eyrabakki can operate. They have a shallower draft, the portion of each vessel that is submerged, so the lower water levels are not as much of a challenge for these two ferries. The "regular dock" can be used - for now. I have heard the Roen crews are hoping to work til/ finish on the 8th. A couple of other interesting facts......The rates will not change in 2013. The Board of Directors for the WIFL voted to maintain the current rates at the November meeting. Given the impending use of the Arni J. Richter as the ice sets in, I thought I would have to come to grips with the return of side loading. I remember when this was the custom on the former ice breaking ferry, C. G. Richter. But today I found the excavation will allow the Arni J. Richter to load as it does at the "regular dock". It looks like the amount of digging completed will allow truck traffic as well. Ticketing? Ticketing will be on a portable tablet-like system. According to what I see on the NOAA website, the weather could be above freezing for most of this week and once the temperature drops it will take some time for the harbor to ice over. I hasten to add there is a learning curve here. It will be a new process or challenge for all of us. Glad to see there is some time to continue to work on everything. Last year, the harbor was frozen over /ice breaker was needed about six weeks Speaking for myself, I am thankful for the efforts I have observed. My thanks to Hoyt Purinton for allowing me to take some photos. This is going to be an interesting Winter, but then the Winter is always interesting on the Island...Over the holiday, I found I couldn't get away from low water levels. I come from a town in Southern Illinois located on the Mississippi River. St. Louis was a stop for us this Christmas and the water was in the news there, too.
It is day to day as to when commercial traffic on the Mississippi could cease given the troubled section south of St. Louis to Cairo. The photo above (from Reuters) shows crews clearing river-bottom rocks as well as what they call rock pinnacles as the water recedes near Thebes, Il, 150 miles south of St.Louis. Water from at least two lakes nearby has been released into the river but it may not be enough. The other negative is the forming of ice in the same area. It's known as "ice bite" - ice taking a bite out of the flow of the river toward the Gulf.
*At Alton, I have watched the flow of the Mississippi...the highs...the lows...sometimes harsh...but it has always been steady so this is interesting, too. Maybe living alongside water has helped me to understand, accept, respect life on the water here as well. Not sure how I would cope in a land-locked area!
**Here's another team effort on the Island ...actually this is just a portion of this team...The Island Players team that is. The group hosted their first "Center Stage," an afternoon of humor through staged readings on Sunday. Held at the Rec. Center at 2:00, monthly performances will be held on the first Sunday of the month through May. Complimentary refreshments are available at intermission and members of the audience are invited to try their hand in a reading during the second half of the program.
Lastly, this is a team that needs no introduction yet is an integral part of Island Life. Next Saturday - the 12th - The Packers meet the 49ers in San Fransisco @ 7pm. Go Pack!


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After King Nebuchadnezzar had dreamed the dream, He made a big beautiful statue all of gold. He was puffed up in his heart thinking that he would always be the only one to be king over the whole world, instead of the five kingdoms like God showed him in the dream.
Then he brought men who could play music real well and made all his people everywhere to bow down to the statue, not the Lord our Maker, when the music was playing. But the statue couldn't walk or talk or do anything. It couldn't help anyone or make anyone happy.
Anyone who wouldn't bow down to the statue was tied up and thrown into a big room full of fire, called a furnace. Some bad men of the king hated Daniel and his three friends so told on them that they weren't bowing down to the statue.
The king called them and gave them another chance to bow down to his statue but they wouldn't do it at all. They told him, No, Our God is able to save us from the fire, and even if He doesn't, even if you kill us, we won't bow down to your statue, ever.
So the king had his soldiers tie up Shadrach, Meshach, and Abednego and make the oven seven time hotter and then threw them in it. The room was so hot that the fire burned up the soldiers that took Shadrach, Meshach, and Abednego to put them in the furnace.
Then the king looked and was amazed. He said, Didn't we throw three men into the furnace. I see four men walking around in there. And one of them looks like the Son of God.
Then the king took them out of the furnace and all the people crowded around them to see the men who the fire couldn't hurt. Their clothes didn't even smell smoky.
Nebuchadnezzar said, I make a law that all people everywhere say nothing bad about the God of Shadrach, Mechach, and Abednego. Anyone who does will be chopped up into little pieces and their houses made a potty.
Because there is no God anywhere that can save like the God of heaven saved these men. Then the king made Shadrach, Mechach, and Abednego princes in his kingdom.
King Nebuchadnezzar, in Babylon, the place where some children of Israel had been captured and taken, wrote what happened to him and sent the letter to all the people of all the countries all around the world.
He said, I think its good to show you the signs and wonderful things the High God did to me. His signs are great big and the amazing things He does are very strong and full of wonder.
His kingdom lasts forever and ever and he rules over everything everywhere through all the years and all the families and all the countries of the world for always.
Now here is what happened to me, said the king. I was resting in my house and enjoying everything in my palace when I saw a dream that made me real scared.
So I sent to all the smart men in my country to come to me and tell me what it meant. So all the magicians came and all the ones who read the stars and all the scientists and all the fortunetellers came to me but couldn't tell me what the dream said to me.
But then at the last, Daniel came in to me. The Spirit of the holy God is in him. I told him about my dream.
I said to Daniel, I know that the Spirit of the holy God is in you and no secret is too hard for you to know.
I was on my bed resting and saw a tree in the middle of the earth. It was very tall and reached up to heaven and its branches spread out over the whole world.
The tree had beautiful leaves and there was lots of fruit on it, enough for food to feed all the birds and animals and people in the world.
Then I saw a watcher, a holy one, come down from heaven and yelled out real loud, Cut down the tree and shake off its leaves and throw it fruit all around.
Let the animals get out from under it and all the birds in it fly away. But leave the stump in the ground and the roots going down with a band of iron and brass. And let the dew of earth make it wet.
Give him a heart like an animal for 7 years. This is set strong by the watchers and demanded by the word of the holy ones so that all people living will know that it is the Most High God that is in charge, ruling over everything everywhere in the kingdom of men and He puts in charge over it anyone He wants, the lowest men.
So now, Daniel, the king said, Tell me what this means. You can do it. The Spirit of the holy God is in you. Daniel sat still and quiet for an hour, he was so amazed at the dream. Then the king said, Don't let it dream upset you. Tell me what it means.
So Daniel said, The tree you saw that grew strong and reached up into heaven that all the world could see with its beautiful leaves and food for all and under it the animals rested in its shade and the birds lived in its branches, the tree is you, O king.
You have grown strong and great and reach to heaven and rule over everything all over the world.
The watcher you saw is a holy one coming down from heaven saying, Cut down the tree but leave the roots and stump kept right where they are with a band of iron and brass, and let it be that way for 7 years, this is what it means.
This is what the Most High says about you. Men will chase you from your palace and your job of ruling over everyone and you will live in the field like an animal with the animals for 7 years until you learn to know that it is the Most High God who causes everything to happen and rules over everything and gives the ruling to whoever He wants.
The stump being kept with its roots in the ground means that after the seven years you will be made the king over the world again, when you know that it is the Most High who is really in charge over everything.
Daniel said then, Please listen to what I say so maybe this won't happen to you. Stop turning away from God and do what He says is right. Don't be puffed up but be kind to the poor, helping them.
All that the dream showed happened to king Nebuchadnezzar. The Lord gave him 1 year to turn away from doing bad, but he didn't.
He was walking around the palace of his kingdom bragging how he had made the kingdom great by himself and bragging about all the beauty and splendor of his kingdom, when a voice came from heaven saying to him, Your kingdom is taken away from you.
You will be chased away from people and live with the animals. You will eat the grass like a cow for 7 years, until you know that the Most High is in charge over the kingdom of men and gives it to who He wants.
That same hour it happened like the Lord said. The king was chased away and lived out in the fields like an animal and ate grass like the cows. His body was wet with the dew and his hair grew long like eagles feathers and his fingernail turned like birds claws.
At the end of 7 years he looked up to heaven and his right thinking came back to him and he was happy to know the God of heaven and said good things to him. He told the best high words to the Lord who is in charge over everything.
All the ones who live in the world are nothing next to the Lord. He does what He wants in all the armies of the angels in the heavens too, and all with the people in the world.
No one can stop anything He wants. Who can say to Him, What do you think You are doing?
At the time the king's thinking came back and king Nebuchadnezzar was put in charge over the kingdom of the world again, and he was made very great and majestic. All his leaders who had left came back to listen to him and obey him.
He said, Now I, Nebuchadnezzar, hold high and say the best words about the King of heaven who does everything true and right. He knows how to bring down the puffed up ones.
+Load
+Crying
+Shhhhhh
+Who
+Jeremiah
+Throw
+Great
+Ezekiel
*Sword
+So empty
+Daniel
Gold Statue
+Hosea
+Amos
+Jonah
+Micah
+Zechariah
Come!
You are invited.
www.streets-of-gold.info
© Streets of Gold

redpajama_set_name: RedPajamaCommonCrawl


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March against racism
'We must all work harder to repair the fissures and polarization that are so prevalent in our societies today. We must nurture mutual understanding and invest in making diversity a success. And we must counter and reject political figures who exploit differences for electoral gain.'
UN Secretary-General António Guterres
The 21st of March is the United Nations' International Day for the Elimination of Racial Discrimination. It is an important date on the calendar for those of us who understand that increased racism will be one outcome of climate breakdown. Everywhere, the climate and ecological crisis will disproportionately affect communities of colour.
According to a recent study by Cornell University, 1.4 billion people could be forced to leave their homes by 2060 and this number could rise to two billion by 2100.
Extreme weather events are already devastating communities. In 2016, 'weather-related sudden- onset hazards', such as cyclones and floods displaced around 23.5 million people. In the first half of the year 2019, million people were internally displaced by such weather events, according to the Internal Displacement Monitoring Centre. This is a record number, and it's twice as big as the number of people displaced by violence and conflicts.
In central America, desperate Campesinos are migrating north due to the collapse of agriculture, especially coffee production. They are reaching the wall Trump is building on the border with Mexico. This is a wall of climate apartheid, designed to keep out the victims of climate breakdown.
When Hurricane Dorian struck the Bahamas last year, it was left to a cruise ship to pick up the survivors. When Trump falsely claimed that Dorian would make landfall in Alabama, this became the big media controversy, rather than the fact that he had prevented a cruise ship carrying survivors from disembarking in US ports.
We know that the hardest impacted victims will be in the Global South. Climate change is one of the factors driving migration from Africa and forcing people to make the perilous crossing across the Mediterranean. According to a recent NGO, there were over 34,000 documented refugee deaths in the Mediterranean as a result of Europe's border regime.
The climate crisis doesn't care about skin colour or borders. We invite you to join us between 12-4pm on the 21st of March in central London.
by JOHN SINHA
Find your local event page at https://www.facebook.com/ events/518483265364312/