The US Election in 2024 and the Trend of the Ukraine Crisis

The crisis in Ukraine,which has dragged on for more than two years,and whether military aid to Ukraine should continue are major issues debated and fought over by the two parties in the United States prior to the 2024 election.Regarding whether to continue to aid Ukraine,various political forces in the United States have chosen sides in the election campaign,which can be roughly divided into the“aid camp”and the“stop-aid camp”according to their positions.

Improving Sentiment Analysis in Election-Based Conversations on Twitter with ElecBERT Language Model

Sentiment analysis plays a vital role in understanding public opinions and sentiments toward various topics.In recent years,the rise of social media platforms(SMPs)has provided a rich source of data for analyzing public opinions,particularly in the context of election-related conversations.Nevertheless,sentiment analysis of electionrelated tweets presents unique challenges due to the complex language used,including figurative expressions,sarcasm,and the spread of misinformation.To address these challenges,this paper proposes Election-focused Bidirectional Encoder Representations from Transformers(ElecBERT),a new model for sentiment analysis in the context of election-related tweets.Election-related tweets pose unique challenges for sentiment analysis due to their complex language,sarcasm,andmisinformation.ElecBERT is based on the Bidirectional Encoder Representations from Transformers(BERT)language model and is fine-tuned on two datasets:Election-Related Sentiment-Annotated Tweets(ElecSent)-Multi-Languages,containing 5.31 million labeled tweets in multiple languages,and ElecSent-English,containing 4.75million labeled tweets in English.Themodel outperforms othermachine learning models such as Support Vector Machines(SVM),Na飗e Bayes(NB),and eXtreme Gradient Boosting(XGBoost),with an accuracy of 0.9905 and F1-score of 0.9816 on ElecSent-Multi-Languages,and an accuracy of 0.9930 and F1-score of 0.9899 on ElecSent-English.The performance of differentmodels was compared using the 2020 United States(US)Presidential Election as a case study.The ElecBERT-English and ElecBERT-Multi-Languages models outperformed BERTweet,with the ElecBERT-English model achieving aMean Absolute Error(MAE)of 6.13.This paper presents a valuable contribution to sentiment analysis in the context of election-related tweets,with potential applications in political analysis,social media management,and policymaking.

From Social Media to Ballot Box:Leveraging Location-Aware Sentiment Analysis for Election Predictions

Predicting election outcomes is a crucial undertaking,and various methods are employed for this purpose,such as traditional opinion polling,and social media analysis.However,traditional polling approaches often struggle to capture the intricate nuances of voter sentiment at local levels,resulting in a limited depth of analysis and understanding.In light of this challenge,this study focuses on predicting elections at the state/regional level along with the country level,intending to offer a comprehensive analysis and deeper insights into the electoral process.To achieve this,the study introduces the Location-Based Election Prediction Model(LEPM),which utilizes social media data,specifically Twitter,and integrates location-aware sentiment analysis techniques at both the state/region and country levels.LEPM predicts the support and opposing strength of each political party/candidate.To determine the location of users/voters who have not disclosed their location information in tweets,the model utilizes a Voter Location Detection(VotLocaDetect)approach,which leverages recent tweets/posts.The sentiment analysis techniques employed in this study include rule-based sentiment analysis,Valence Aware Dictionary and Sentiment Reasoner(VADER)as well as transformers-based sentiment analysis such as Bidirectional Encoder Representations from Transformers(BERT),BERTweet,and Election based BERT(ElecBERT).This study uses the 2020 United States(US)Presidential Election as a case study.By applying the LEPM model to the election,the study demonstrates its ability to accurately predict outcomes in forty-one states,achieving an 0.84 accuracy rate at the state level.Moreover,at the country level,the LEPM model outperforms traditional polling results.With a low Mean Absolute Error(MAE)of 0.87,the model exhibits more precise predictions and serves as a successful alternative to conventional polls and other methodologies.Leveraging the extensive social media data,the LEPM model provides nuanced insights into voter behavior,enabling policymakers to make informed decisions and facilitating in-depth analyses of elections.The study emphasizes the importance of using social media data for reliable election prediction and offers implications for enhancing prediction accuracy and understanding voter sentiment and behavior.

Elections in the United States

惊奇常常是在箱子里出现:包在彩色包装纸里面的生日礼物,朋友寄来牛皮纸包的包裹。不论是怎样的箱子,人们都喜欢打开来看看里面是什么。在美国以及其它许多国家,有一个特殊的箱子关系着未来。

On the 2002 U. S. Mid-Term Election Zhang Yanyu and Wang Wenfeng are both assistant research professors at the Division for American Studies in China Institute of Contemporary International Relations

The first mid-term election of the U. S. in the new century took place on November 5, 2002. One third of the senators from the 107th Congress (34 out of 100), all representatives (435), 36 state governors, and numerous local officials and legislators were to be elected or reelected. The resounding victory of the GOP in the congressional elections and the fact that the Democrats only got three more.

General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

To examine the interdependency and evolution of Pakistan’s stock market,we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange(KSE-100)index.Using the minimum spanning tree network-based method,we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan.Our results reveal a star-like structure after the general elections of 2018 and before those in 2008,and a tree-like structure otherwise.We also highlight key nodes,the presence of different clusters,and compare the differences between the three elections.Additionally,the sectorial centrality measures reveal economic expansion in three industrial sectors—cement,oil and gas,and fertilizers.Moreover,a strong overall intermediary role of the fertilizer sector is observed.The results indicate a structural change in the stock market network due to general elections.Consequently,through this analysis,policy makers can focus on monitoring key nodes around general elections to estimate stock market stability,while local and international investors can form optimal diversification strategies.

Election Spin Resonance Studies of Free Radical Formation and Oxygen Consumption of Lens Epithelium During Ultraviolet Exposure

A long life election spin resonance (ESR) signal at g=2.0006 was observed in the normal lens epithelium and cortical fibers. During ultraviolet (UV) exposure, a new ESR signal at g = 2.0060 was found in the lens epithelium. But this specific signal was not detected in the lens cortical fibers. This suggested that lens epithelial cells were more susceptible to the free radical formation which was induced by UV light. By means of ESR spin probe oxymetry, the oxygen uptake of lens epithelial cells was meas...

Clinical Observation on 80 Cases of Anal Edema after Mixed Hemorrhoids Operation with Chinese Medicine Hot Election Package

The subjects of this study were 80 patients who underwent mixed hemorrhoids surgery in our hospital from January to October 2020 (mixed hemorrhoids external and internal ligation, internal hemorrhoids ligation or Xiaozhiling injection) and developed anal edge edema after surgery. According to the order of hospitalization, the patients were randomly divided into treatment group and control group, with 40 cases each. In the control group, blank hot pack was applied on the basis of anorectal No. 1 lotion for prevention and treatment of anal edge edema after operation;in the treatment group, hot pack of Traditional Chinese medicine was applied on the basis of anorectal No. 1 lotion for prevention and treatment of anal edge edema. The course of treatment was 7 days. The edema subsidence and postoperative pain scores were observed in both groups. Results: The scores of anal edema and pain in the treatment group were significantly lower than those in the control group (P < 0.05), and the significant efficiency and total effective rate in the treatment group were significantly better than those in the control group, with statistical difference (P < 0.05). Conclusion: Chinese medicine hot election package is effective in treating postoperative anal edema of mixed hemorrhoids, and the method is simple and suitable for clinical promotion.

“recall election”是什么意思?

[问] [427]2003年10月7日美国加州州长、民主党人戴维斯(Gray Davis)由于争取竞选连任而谎报预算赤字遭到指责,为此加州选民举行了“recallelection”。在这次选举活动中,Davis被迫下台把州长宝座让给好莱坞动作明星、共和党人施瓦辛格(Arnold Schwarzenegger)。那么,请问“:recallelection”是什么意思? [答] 根据加州法律,选民有权通过选举对在任的不称职州长进行罢免,这种决定其是否能继续留任的选举被称为“recall election”,即罢免选举。

A Genetic Based Leader Election Algorithm for IoT Cloud Data Processing

In IoT networks,nodes communicate with each other for computational services,data processing,and resource sharing.Most of the time huge data is generated at the network edge due to extensive communication between IoT devices.So,this tidal data is transferred to the cloud data center(CDC)for efficient processing and effective data storage.In CDC,leader nodes are responsible for higher performance,reliability,deadlock handling,reduced latency,and to provide cost-effective computational services to the users.However,the optimal leader selection is a computationally hard problem as several factors like memory,CPU MIPS,and bandwidth,etc.,are needed to be considered while selecting a leader amongst the set of available nodes.The existing approaches for leader selection are monolithic,as they identify the leader nodes without taking the optimal approach for leader resources.Therefore,for optimal leader node selection,a genetic algorithm(GA)based leader election(GLEA)approach is presented in this paper.The proposed GLEA uses the available resources to evaluate the candidate nodes during the leader election process.In the first phase of the algorithm,the cost of individual nodes,and overall cluster cost is computed on the bases of available resources.In the second phase,the best computational nodes are selected as the leader nodes by applying the genetic operations against a cost function by considering the available resources.The GLEA procedure is then compared against the Bees Life Algorithm(BLA).The experimental results show that the proposed scheme outperforms BLA in terms of execution time,SLA Violation,and their utilization with state-of-the-art schemes.

Donald Trump Administration’s Domestic and Foreign Policy after the Midterm Election

After Democrats recaptured control of the US House at the 2018 midterms,the ramifications for American domestic and foreign policies have included increased partisan checks on President Donald Trump's proposals for immigration,energy,pollution,taxes,healthcare,and social welfare,and on the Republican Party's conservative agenda overall.After the longest government shutdown in US history over funding for a border wall to keep out illegal immigrants,Trump declared a national emergency in February 2019.Under his administration,US trade pacts with China,Mexico,Canada,Japan,the EU and other countries also face uncertainty.The Indo?Pacific Strategy and relations with Russia and Europe will remain,as is.Yet even if Sino-US trade negotiations progress,bilateral friction over high technology and cultural exchange will likely increase,and disputes over Taiwan,the South China Sea and human rights will continue.

RUSSIA AFTER THE PRESIDENTIAL ELECTION

In the recent presidential election,a most bitter trial of strength since its inde-pendence took place between the“democrats”and the so-called“traditionalists”in Russia.The outcome of this rivalry has a direct bearing on thechoice of Russia’s future development path.The reelection of the incumbent Presi-dent Boris Yeltsin in the second round of the voting has offered the political guaran-tee for the country’s further search for an appropriate development strategy alongthe current track.

Election Procedure for Rural Two Committees

In order to further strengthen the construction and improvement of villager autonomy system with democratic election,democratic decision making,democratic management,and democratic supervision of rural two committees with Chinese characteristics,experience of work team of Longyang District Agricultural Technology Extension Station dispatched to villager committees( or offices) and their guidance on election of rural two committees in 2007-2016 were used,and exploration was made for election of rural two committees from the third to the sixth committees. It summarized achievements and main problems in election of rural two committees and came up with pertinent recommendations.The results of this study are expected to provide certain reference for theory and practice of future villager autonomy.

EU's Fate after the French Election

In the second round of French presidential election,39-year-old Emmanuel Macron defeated the far-right candidate Marine Le Pen and was elected President of France.This is a historic victory to France and all EU countries.

Modeling Election Problem by a Stochastic Differential Equation

The proportion of the favorable among voters to a nominee might change over times and depend on different factors for example: talent, reputation, party and even name order on election. The unobservable factors which might have minor impacts on the approval rate are modelized by random elements. The approval rate is initially described by the differential equation and then by the random differential equation including the above unobservable factors. We figure out the formula of the solution for the stochastic differential equation and simulate these solutions to identify the changes of the approval rate over time.

THE EFFCTS IN ELECTION INDICATION OF PERCUTANEOUS BALLOON ATHETER VALVULOPLASTY(PBVP)BY 2DE AND M-MODE ECHOCARDIOGRAPHY

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A Study on Economic Impact in the Context of American Election Based on AHP

To assess the economic impact of the different policies of the Trump and Biden candidates,we formulate metrics on five aspects:Covid-19 prevention and control measures,environmental protection policies,taxation,health care reform,foreign trade.Moreover,each metric is subdivided into several secondary metrics,making a three-tier hierarchical structure.Take environmental protection policy as an example:Without direct data under Biden’s policies,we collected data on U.S.CO2 emissions and U.S.oil consumption during Obama’s presidency as Biden’s legacy.First,use the analytic hierarchy process(AHP)to select indicators that can reflect the U.S.economy and determine the weight of each indicator.For the U.S.economy,Biden scored 2.6498,Trump 2.3502,suggesting that the election of Biden might make things better for the economy.For China’s economy,Biden scored 0.6810 and Trump 0.3245,meaning Biden could give the Chinese economy more room to grow.To reduce the influence of AHP subjectivity on the results,the Pearson correlation coefficient is introduced to establish the P-AHP model.Take the impact on China’s economy.Biden scored 0.5846 and Trump 0.4154.