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Academic literature on the topic 'LARGE INFLUENCERS'

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Published: 11 September 2023

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Journal articles on the topic "LARGE INFLUENCERS"

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Firmansyah, Delima Destiana, and Isna Wijayani. "Penerapan Personal Branding Andini Shidqin Maza sebagai Beauty Influencer Palembang di Media Sosial Tiktok." Da'watuna: Journal of Communication and Islamic Broadcasting 3, no. 1 (September 27, 2022): 1–11. http://dx.doi.org/10.47467/dawatuna.v3i1.2157.

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The existence of TikTok social media has created a new phenomenon among youth. An influencer is also known as someone who has the ability to influence other people in making decisions to buy a product. TikTok influencers are people who are famous for having a fairly high popularity, namely by having a large number of followers, which is tens to hundreds of thousands. Someone is said to be an influencer because of the large number of followers or fans on TikTok and this can also be seen from the interesting video content that is liked by other TikTok users. Influencers use TikTok to build their personal brand according to their skills and interests. Based on gender, influencers are divided into several types, namely travel influencers, fashion influencers, food influencers, lifestyle/socialite influencers, comedy influencers, and beauty influencers. TikTok @andinishidqin05 has around 56.4K followers and 1.8 million likes (as of July 14, 2022). The author sees Andini Shidqin Maza has something interesting as an influencer. It can be seen from his who has 56.4 thousand followers and can form good personal branding on TikTok so that he can attract the attention of several big brands in Indonesia to use his services as endorsers. Keywords: Personal Branding, Social Media TikTok, Beauty Influencer
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Firmansyah, Delima Destiana, and Isna Wijayani. "Penerapan Personal Branding Andini Shidqin Maza sebagai Beauty Influencer Palembang di Media Sosial Tiktok." Da'watuna: Journal of Communication and Islamic Broadcasting 2, no. 4 (September 27, 2022): 1–11. http://dx.doi.org/10.47467/dawatuna.v2i4.2157.

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The existence of TikTok social media has created a new phenomenon among youth. An influencer is also known as someone who has the ability to influence other people in making decisions to buy a product. TikTok influencers are people who are famous for having a fairly high popularity, namely by having a large number of followers, which is tens to hundreds of thousands. Someone is said to be an influencer because of the large number of followers or fans on TikTok and this can also be seen from the interesting video content that is liked by other TikTok users. Influencers use TikTok to build their personal brand according to their skills and interests. Based on gender, influencers are divided into several types, namely travel influencers, fashion influencers, food influencers, lifestyle/socialite influencers, comedy influencers, and beauty influencers. TikTok @andinishidqin05 has around 56.4K followers and 1.8 million likes (as of July 14, 2022). The author sees Andini Shidqin Maza has something interesting as an influencer. It can be seen from his who has 56.4 thousand followers and can form good personal branding on TikTok so that he can attract the attention of several big brands in Indonesia to use his services as endorsers. Keywords: Personal Branding, Social Media TikTok, Beauty Influencer
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Kim, Seungbae, Xiusi Chen, Jyun-Yu Jiang, Jinyoung Han, and Wei Wang. "Evaluating Audience Loyalty and Authenticity in Influencer Marketing via Multi-task Multi-relational Learning." Proceedings of the International AAAI Conference on Web and Social Media 15 (May 22, 2021): 278–89. http://dx.doi.org/10.1609/icwsm.v15i1.18060.

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Since influencer marketing has become an essential marketing method, influencer fraud behavior such as buying fake followers and engagements to manipulate the popularity is under the spotlight. To address this issue, we propose a multi-task audience evaluation model that can assess both the loyalty and authenticity of influencers’ audiences. More specifically, the proposed model takes engagement information of an influencer’s audience, including likes and comments on social media posts, and predicts (i) the retention rate of the audience of the influencer and (ii) how the influencer is associated with fake audiences (or engagement bots). To learn the social interaction between influencers and their audiences, we build multi-relational networks based on the diverse engagement behavior such as commenting. Our model further utilizes the contextualized information captured in user comments to learn distinct engagement behavior of genuine and fake users. Based on the predicted loyalty and authenticity scores, we rank influencers to find those who are followed by loyal and authentic audiences. By using a large-scale Instagram influencer-audience dataset which contains 14,221 influencers, 9,290,895 audiences, and 65,848,717 engagements, we evaluate ranking performance, and show that the proposed framework outperforms other baseline methods.
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Chiny, Mohamed, Marouane Chihab, El Mahdi Juiher, Khaoula Jabari, Omar Bencharef, and Younes Chihab. "The impact of influencers on the companies reputation in developing countries: Case of Morocco." Indonesian Journal of Electrical Engineering and Computer Science 24, no. 1 (October 1, 2021): 410. http://dx.doi.org/10.11591/ijeecs.v24.i1.pp410-419.

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With the emergence of social networks and their adoption by a large number of users, the importance of influencers continues to grow and companies are in a frantic race to recruit those most likely to promote their reputation and brand image. However, in the existing literature, there is little work that conducts quantitative studies on this subject in developing countries. For this reason, we conducted a study that attempts to understand the importance of influencers in reshaping public opinion of a company or brand. We chose as a subject of study a large Moroccan company operating in the telecommunications sector that hired a popular influencer among young Moroccans. We then adopted an approach based on scraping and analyzing the occurrences of the influencer's posts on Instagram and the content of the company's website and then publishing a questionnaire to 180 respondents in the age range of most of the followers of the influencer in question. The results suggest that a positive relationship exists between the influencer and brand reputation, meaning that if the person is following the influencer who has published content on the brand, that person is expected to be systematically aware of the brand, and vice versa.
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Wong Jiayan, Natalie, and Ameen Talib. "Instagram influencers and brand awareness: the impact on the youth followers in Singapore." Global Advances in Business Studies 1, no. 1 (April 1, 2022): 12–26. http://dx.doi.org/10.55584/gabs001.01.2.

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Due to the proliferation of social media, such as Instagram and its influencers, brands have begun to leverage on the latter’s large following to generate brand awareness for their products. The objective of this study was to conduct an exploratory research to examine if Instagram influencers have any impact on brand awareness. The study employed the use of focus groups and online questionnaires to gather primary data about the users’ motivations behind following such influencers. Multiple regression techniques were used to calculate the significance of the independent variables of the study. It was found that followers were more likely to have a negative opinion of influencers, as compared to a positive opinion. Despite this, it was also found that they continue to follow them on Instagram due to the three main themes that were identified: an attractive influencer, a high number of followers, and nicely taken pictures. In addition, it was observed that the brand awareness that followers receive through an Instagram influencer’s post, does not make any significant impact on the purchase intention of that product.
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Berliantha, Berliantha, Anne Shavira, Ilma Ainun Nabila Fasya, and Ghita Rhakasiwi. "PERTANGGUNGJAWABAN HUKUM INFLUENCER YANG MELANGGAR TATA CARA PERIKLANAN DALAM MELAKUKAN ENDORSEMENT." IBLAM LAW REVIEW 2, no. 3 (September 30, 2022): 45–55. http://dx.doi.org/10.52249/ilr.v2i3.92.

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Influencers are well-known individuals who have a large following on social media and are considered a strong influence on their followers. Because they have influence and a large number of followers, many business actors hire influencer endorsement services. This aims to expand market reach so that the products of business actors can be recognized by many people. However, there is no guarantee that the information submitted by Influencers in advertising a product is correct. The reviews given can be misleading, so that in reality consumers are always in a position of ignorance and are always at a loss. This study aims to determine the forms of violations in advertising procedures and legal liability for the behavior of influencers when making endorsements by comparing the laws and regulations related to the problems studied. Researchers want to know which laws and regulations are more relevant in giving the burden of responsibility to these influencers. This research uses normative legal research methods. The approach used in solving the problems in this research is the statutory approach and conceptual approach. The results of this study indicate that there are no special regulations governing influencers who do endorsements on social media. Although there are no specific regulations governing influencers, it is emphasized that influencers can follow the regulations regarding advertising when making endorsements. Keywords: Influencer, endorsement, accountability
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Lokithasan, Komathi, Salomi Simon, Nur Zahrawaani Jasmin, and Nur Ajeerah Othman. "MALE AND FEMALE SOCIAL MEDIA INFLUENCERS: THE IMPACT OF GENDER ON EMERGING ADULTS." International Journal of Modern Trends in Social Sciences 2, no. 9 (September 11, 2019): 21–30. http://dx.doi.org/10.35631/ijmtss.29003.

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Social media influencers are people who have established a reputation for themselves on social media. Nowadays, a social media influencer has played the important role of a marketing tool for organizations. Organizations use the power of social media influencers to influence and persuade consumers through social media. It is because social media influencers have a huge number of followers in their social media, thus, social media influencers could promote and reach a large number of consumers in a short time. The result is more effective than celebrity endorsement for small-and-medium-sized enterprises (SME). This research is to study the perceptions of emerging adults on the difference between male and female social media influencers’ style of promotion. Qualitative method is used by conducting a focus group and content analysis to compare the impact of male and female social media influencers towards emerging adults. Findings showed that female respondents are influenced by influencers who promote beauty products while male respondents are drawn to technology and gaming products. The most important factors mentioned by the respondents in the impact of the social media influencers’ posts are the entertainment factor and followed by informativeness.
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Ariasih, Made Putri, and I. Putu Dharmawan Suryagita Susila Putra. "Analisis Pengaruh Marketing Influencer Tiktok Terhadap Keinginan Pembelian Pada Pengguna Aplikasi Tiktok." Jurnal Sutasoma 1, no. 1 (December 22, 2022): 22–27. http://dx.doi.org/10.58878/sutasoma.v1i1.178.

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The TikTok application contains various videos created by content creators. Content creators whose video content is watched a lot and has many followers are called influencers. Influencers with a large audience usually open services to advertise a product, with influencers the advertised product will be noticed by many people, so that people watching have an intention to buy the advertised product. The purpose of this study was to analyze the influence of the tiktok marketing influencer on the emergence of purchase intentions from users of the tiktok. This study uses a qualitative research approach. The data collection technique used in this study uses data collection techniques on various literature, as well as various reports related to research variables. This study uses data collected by observation techniques on the TikTok. Data was also collected using interview techniques, by interviewing a company that had used the services of an influencer, and interviewing users of the TikTok. This study obtained the results, the first company uses the services of influencers to introduce their products and generate purchase intentions. Second, consumers in making purchasing decisions will seek information about the products they will buy through influencers. Third, video content created by influencers can raise consumers' purchase intention.
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Qian, Yang, Yezheng Liu, Yuanchun Jiang, and Xiao Liu. "Detecting topic-level influencers in large-scale scientific networks." World Wide Web 23, no. 2 (December 11, 2019): 831–51. http://dx.doi.org/10.1007/s11280-019-00751-4.

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Wu, Jiaxi, Alyssa F. Harlow, Derry Wijaya, Micah Berman, Emelia J. Benjamin, Ziming Xuan, Traci Hong, and Jessica L. Fetterman. "The Impact of Influencers on Cigar Promotions: A Content Analysis of Large Cigar and Swisher Sweets Videos on TikTok." International Journal of Environmental Research and Public Health 19, no. 12 (June 9, 2022): 7064. http://dx.doi.org/10.3390/ijerph19127064.

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Little is known about the content, promotions, and individuals in cigar-related videos on TikTok. TikTok videos with large cigar and Swisher Sweets-related hashtags between July 2016 and September 2020 were analyzed. Follower count was used to identify influencers. We compared content characteristics and demographics of featured individuals between cigar types, and by influencer status. We also examined the association between content characteristics and video engagement. Compared to large cigar videos, Swisher Sweets videos were more likely to feature arts and crafts with cigar packages, cannabis use, and flavored products. In addition, Swisher Sweets videos were also more likely to feature females, Black individuals, and younger individuals. Both Swisher Sweets and large cigar influencers posted more videos of cigar purchasing behaviors than non-influencers, which was associated with more video views. None of the videos disclosed sponsorship with #ad or #sponsored. Videos containing the use of cigar packages for arts and crafts, and flavored products highlight the importance of colorful packaging and flavors in the appeal of Swisher Sweets cigars, lending support for plain packaging requirements and the prohibition of flavors in cigar products to decrease the appeal of cigars. The presence and broad reach of cigar promotions on TikTok requires stricter enforcement of anti-tobacco promotion policies.
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Dissertations / Theses on the topic "LARGE INFLUENCERS"

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Linstead, Conor. "The influences of large woody debris on British headwater streams." Thesis, University of Birmingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368996.

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This thesis examines the influence of large woody debris (LWD) on the physical habitat of British headwater streams. The distribution and density of LWD accumulations throughout catchments is considered using data from the River Habitat Survey (RHS) and more detailed catchment scale surveys. The effect of accumulations of LWD on stream hydraulics and physical habitat at a reach scale is examined using transect based measurements of depth and velocity over a range of discharges before and after LWD removal for two reaches, measurement of reach average hydraulic parameters for 25 reaches with differing levels of LWD and the application of the Aggregated Dead Zone (ADZ) and Physical Habitat Simulation (PHABSIM) models. The RHS and catchment scale surveys showed that LWD accumulations exhibit systematic patterns in abundance within catchments, smaller streams having a higher density of LWD and a greater number of LWD accumulations. The most hydraulically active type of LWD accumulations were found to reduce flow velocity by an average of 55%, increase channel roughness by 149% and increase depth by 165%. This impact was, however, found to vary with discharge. Application of the Aggregated Dead Zone (ADZ) model showed that LWD increases the volume of ADZ, which may indicate greater ecological refuge potential. Using the Physical Habitat Simulation (PHABSIM) model, it was found that LWD improved habitat quality and overall habitat diversity.
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Mills, Roger W. "Influences upon the capital budgeting decision : an analysis of the influence of senior central and divisional management in large, divisionalised UK companies." Thesis, Henley Business School, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305307.

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Olkhovskaya, Julia. "Large-scale online learning under partial feedback." Doctoral thesis, Universitat Pompeu Fabra, 2022. http://hdl.handle.net/10803/673926.

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La toma secuencial de decisiones con incertidumbre cubre una amplia clase de problemas. Las aplicaciones reales requieren que los algoritmos sean computacionalmente eficientes y escalables. Nosotros estudiamos un rango de problemas de toma secuencial de decisiones donde el agente obtiene información parcial de las recompensas, y desarrollamos algoritmos que son robustos y computacionalmente eficientes en problemas de grandes dimensiones. El primer problema que consideramos es un problema de maximización de la influencia en línea en el que el agente selecciona secuencialmente los nodos del grafo con el objetivo de esparcir la información a través de éste poniéndola en los nodos elegidos. El feedback disponible es solo alguna información sobre los vecinos más cercanos del vértice seleccionado. Nuestros resultados muestran que esas observaciones locales y parciales pueden ser suficientes para maximizar la influencia global. Proponemos algoritmos de aprendizaje secuencial que intentan maximizar la influencia y presentamos un análisis teórico tanto en los regímenes subcrítico y supercrítico de modelos gráficos. Estos son los primeros algoritmos de maximización secuencial de influencia que son eficientes en grafos con gran cantidad de nodos. En otra línea de trabajo, estudiamos el problema de bandidos multibrazos contextuales, donde la función recompensa puede cambiar de modo adverso y el agente solo puede observar las recompensas asociadas a sus acciones. Asumimos que el número de brazos es finito y que la dimensión del espacio de contextos puede ser infinita. Desarrollamos un algoritmo computacionalmente eficiente bajo la asunción que los contextos d-dimensionales son generados aleatoriamente de una distribución conocida, de forma idéntica e independiente. También proponemos un algoritmo robusto frente a errores de especificación en el caso en el que la función recompensa real es lineal con un error aditivo no lineal. Hasta nuestro conocimiento, nuestras garantías de performance constituyen los primeros resultados en este problema. También mostramos una extensión para cuando el contexto es un elemento de un espacio de hilbert con kernel reproducible. Finalmente, consideramos una extensión del problema de las máquinas tragamonedas contextuales descrito previamente. Estudiamos el caso en el que el agente interactúa con un proceso de decisión de Markov en una secuencia de episodios, donde un adversario escoge la función recompensa y solo observamos las observaciones de las recompensas de la acción elegida. Consideramos un espacio de estados arbitrariamente grande, pero asumimos que todas las funciones de acción-valor pueden ser representadas como funciones lineales en términos de un mapa de características de baja dimensión conocido, y que el agente tiene acceso a un simulador de trayectorias en el MDP. Nuestra principal contribución es el desarrollo de los primeros algoritmos que se han probado robustos y eficientes en este problema.
Sequential decision making under uncertainty covers a broad class of problems. Real-world applications require the algorithms to be computationally efficient and scalable. We study a range of sequential learning problems, where the learner observe only partial information about the rewards we develop the algorithms that are robust and computationally efficient in large-scale settings. First problem that we consider is an online influence maximization problem in which a decision maker sequentiaonally selects a node in the graph in order to spread the information throughout the graph by placing the information in the chosen node. The available feedback is only some information about a small neighbourhood of the selected vertex. Our results show that such partial local observations can be sufficient for maximizing global influence. We propose sequential learning algorithms that aim at maximizing influence, and provide their theoretical analysis in both the subcritical and supercritical regimes of broadly studied graph models. Thus this is the first algorithms in the sequential influence maximization setting, that perform efficiently in the graph with a huge number of nodes. In another line of work, we study the contextual bandit problem, where the reward function is allowed to change in an adversarial manner and the learner only gets to observe the rewards associated with its actions. We assume that the number of arms is finite and the context space can be infinite. We develop a computationally efficient algorithm under the assumption that the d-dimensional contexts are generated i.i.d. at random from a known distribution. We also propose an algorithm that is shown to be robust to misspecification in the setting where the true reward function is linear up to an additive nonlinear error. To our knowledge, our performance guarantees constitute the very first results on this problem setting. We also provide an extension when the context is an element of a reproducing kernel Hilbert space. Finally, we consider an extension of the contextual bandit problem described above. We study a setting where the learner interacts with a Markov decision process in a sequence of episodes, where an adversary chooses the reward function and the reward observations are available only for the selected action. We allow the state space to be arbitrarily large, but we assume that all action-value functions can be represented as linear functions in terms of a known low-dimensional feature map, and that the learner at least has access to the simulator of the trajectories in the MDP. Our main contributions are the first algorithms that are shown to be robust and efficient in this problem setting.
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Hill, S. D. "Influences of large herbivores on small rodents in the New Forest, Hampshire." Thesis, University of Southampton, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356782.

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Janzen, Izabelle. "Modeling distal pointing on large screens : the influence of target depth." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/59047.

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Pointing is a fundamental task within many interactions in current computer applications. It is incorporated into everything from selecting buttons to dragging files or positioning objects in a virtual environment. Thus, understanding, modeling and predicting pointing performance is crucial to the design and evaluation of many computer interfaces. Fitts’s Law (1954) is the basis for modeling human pointing performance in the international standard on pointing device evaluation (ISO 9241-400:2007). However, while it is extremely robust for many standard desktop applications, previous work by Shoemaker et al. (2012) has suggested that Fitts’s Law may not be robust enough to accurately model pointing at more extreme levels of gain and has proposed alternatives to Fitts’s Law based on earlier work by Welford (1968). This thesis extends preliminary research by Rajendran (2012) that further examined these alternatives to Fitts’s Law for distal pointing. Distal pointing is common in virtual and augmented reality interfaces. We first re¨analyze results reported by Rajendran using a variety of Welford-style models to explore the relationship between target depth and a parameter k that was first suggested by Kopper et al. (2010) but is inherent inWelford’s model. We then present a new experiment that removes the confound of system latency from Rajendran’s approach. Our analyses provide evidence that k varies monotonically (possibly linearly) with target depth, which further supports the claim by Shoemaker et al. that Welford-style two-part models are preferable to Fitts-style one-part models in some situations. Our analyses also challenge Kopper et al.’s suggestion that angular measures of task difficulty are superior to linear measures for pointing models. We close with a discussion of how our findings about the variation of k with target depth might be used in calibration procedures for virtual environments.
Science, Faculty of
Computer Science, Department of
Graduate
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Lock, Cinde L. "The influence of a large-scale assessment program on classroom practices." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2002. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/NQ65679.pdf.

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De, Basso Rachel. "Influence of genetics and mechanical properties on large arteries in man." Doctoral thesis, Linköpings universitet, Fysiologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-29492.

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Arterial pathology is the major contributor to cardiovascular diseases and mortality. The mechanical properties of arteries are independent factors for cardiovascular disease and mortality, where genetics influence the structure of the arterial wall, which may result in change in arterial stiffness. The aims of this thesis were to study the mechanical properties of the popliteal artery (PA) in healthy subjects and the influence of angiotensin-converting enzyme (ACE) polymorphism and Fibrillin-1 (FBN1) polymorphism on large arteries. Further, the impact of FBN1 polymorphism on cardiovascular morbidity and mortality was investigated. The PA is, after the abdominal aorta, the most common site of aneurysmal development. The PA was studied in healthy subject with ultrasound and the diameter increased and the distensibility decreased with age, with men having lower distensibility than women. This seems not to be the behavior of a true muscular artery but rather of a central elastic artery such as the aorta, and might have implications for the susceptibility to aneurysm formation, as well as the association of dilating disease between the PA and the aorta. The wall stress in the PA was low and unaffected by age, probably caused by a compensatory remodeling response with an increase in wall thickness. This indicates that other mechanisms than wall stress contribute to the process of pathological dilatation in the PA. The ACE D allele may be associated with abdominal aortic aneurysm. Elderly men with the ACE D allele were associated with increased abdominal aortic stiffness compared to men carrying the I/I genotype. This suggests that the ACE D allele impairs arterial wall integrity, and in combination with local hemodynamic and other genetic factors it may have a roll in aneurysm formation. The FBN1 2/3 genotype has been associated with increased systolic blood pressure. The FBN1 2/3 genotype in middle-aged men was associated with increased abdominal aortic stiffness and blood pressure which indicates an increased risk for developing cardiovascular disease. The increased presence of plaque in the carotid artery of middle-aged men with the FBN1 2/3 genotype indicates a pathological arterial wall remodeling with a more pronounced atherosclerotic burden, but did however not affect the risk of cardiovascular events and/or death in this population. This relationship needs to be studied further.
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Klossner, David. "FACTORS THAT INFLUENCE FIRMS’ ENVIRONMENTAL PERFORMANCE: AN EXAMINATION OF LARGE COMPANIES." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1395301067.

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Zierler, Rupert. "Energy-saving attitudes and behavioural influences in large organisations : the case of Network Rail." Thesis, University of Surrey, 2018. http://epubs.surrey.ac.uk/845644/.

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Railways in the UK account for 1% of all electricity consumed nationally, and Network Rail consumed in excess of 400GWh in 2013/14. Large organisations need to reduce their energy consumption in order to prevent adverse climatic effects driven by anthropogenic greenhouse gas emissions. This doctoral thesis investigates attitudes and behaviours of individual Network Rail employees, relating to the adoption of energy-efficient practices and technologies, and their likely impacts on the organisation’s energy consumption. The research programme consists of two principal stages. Firstly, an exploratory approach is taken with managers of railway energy infrastructure to establish factors which may be influencing these behaviours, based on a commonly-used research framework for semi-structured interviews. Secondly, a staff survey is developed based on findings from the exploratory interviews. This is designed to test commonly-used behavioural frameworks from the sociological and psychological literature on pro-environmental behaviours in a variety of contexts, including the Theory of Planned Behaviour (Ajzen, 1991), and Theory of Interpersonal Behaviour (Triandis, 1977). This survey also tests the salience of a set of barriers to energy efficiency in organisations proposed by Sorrell et al (2000; 2004). However, analysis of collected survey data suggests that no single theory provided a strong fit with observed results. Principal components analysis and structural equation modelling suggest an array of 6 alternative factors governing energy-efficient behaviours, management practices, and technology adoption, and an alternative causal model is proposed, based on these new factors. Cluster analysis then categorises groups of employees based on their personal approaches to energy consumption. Although a combination of technological- and behavioural interventions are required to mitigate global greenhouse gas emissions (IPCC, 2014b), the findings presented here highlight how understanding the attitudinal and behavioural context in which energy consumption behaviours take place can help large organisations such as Network Rail lower their electricity consumption.
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Morris, Arthur E. L. "Influence of stream corridor geomorphology on large wood jams and associated fish assemblages in mixed deciduous-conifer forest in Upper Michigan." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1123513768.

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Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xvi, 263 p.; also includes graphics (some col.). Includes bibliographical references (p. 241-263). Available online via OhioLINK's ETD Center
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Books on the topic "LARGE INFLUENCERS"

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Undue influence. New York: Ivy Books, 1992.

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Drubel, Oliver. Converter Applications and their Influence on Large Electrical Machines. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36282-8.

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Drubel, Oliver. Converter Applications and their Influence on Large Electrical Machines. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Mills, Roger W. Influences upon the capital budgeting decision: An analysis of the influence of senior central and divisional management in large, divisionalised UK companies. Uxbridge: Brunel University, 1985.

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Undue influence. Thorndike, Me: G.K. Hall, 1994.

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Undue influence. Thorndike, Me: Thorndike Press, 1991.

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Yastrow, Shelby. Undue influence. London: Crime Club, 1991.

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Undue influence. London: HarperCollins, 1995.

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Mills, Kyle. Sphere of influence. Waterville, Me: Thorndike Press, 2003.

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Mills, Kyle. Sphere of influence. New York: G.P. Putnam's Sons, 2002.

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Book chapters on the topic "LARGE INFLUENCERS"

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Singh, Shashank Sheshar, Ajay Kumar, Shivansh Mishra, Kuldeep Singh, and Bhaskar Biswas. "Influence Maximization in Social Networks." In Optimization in Large Scale Problems, 255–67. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28565-4_22.

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Ellinghaus, Paul, Mihail Nedjalkov, and Siegfried Selberherr. "The Influence of Electrostatic Lenses on Wave Packet Dynamics." In Large-Scale Scientific Computing, 277–84. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26520-9_30.

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Zlatev, Zahari, Ivan Dimov, István Faragó, Krassimir Georgiev, and Ágnes Havasi. "Studying the Influence of Climate Changes on European Ozone Levels." In Large-Scale Scientific Computing, 391–99. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41032-2_45.

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Fidanova, Stefka, and Olympia Roeva. "Influence of Ant Colony Optimization Parameters on the Algorithm Performance." In Large-Scale Scientific Computing, 358–65. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73441-5_38.

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Fidanova, Stefka, and Olympia Roeva. "Influence of the ACO Evaporation Parameter for Unstructured Workforce Planning Problem." In Large-Scale Scientific Computing, 234–41. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97549-4_27.

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Boguslawsky, Iliya, Nikolay Korovkin, and Masashi Hayakawa. "Frequency-Controlled Induction Motors in Nonlinear Networks: Assessment Criteria of Higher Harmonics Influence—Method of Criteria Calculation." In Large A.C. Machines, 349–61. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-56475-1_17.

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Darling, Andrea L., and Susan A. Lanham-New. "Dietary Protein and Bone Health: The Urgent Need for Large-Scale Supplementation Studies." In Nutritional Influences on Bone Health, 17–26. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-978-7_3.

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ElJack, E., I. AlQadi, and J. AlMutairi. "Influence of Periodic Forcing on Laminar Separation Bubble." In Direct and Large-Eddy Simulation X, 199–204. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63212-4_24.

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Fidanova, Stefka, Pencho Marinov, and Marcin Paprzycki. "Influence of the Number of Ants on Multi-objective Ant Colony Optimization Algorithm for Wireless Sensor Network Layout." In Large-Scale Scientific Computing, 232–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43880-0_25.

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Trujillo Guajardo, L. A., and A. Conde Enríquez. "Wind Power Plants and FACTS Devices’ Influence on the Performance of Distance Relays." In Large Scale Renewable Power Generation, 331–67. Singapore: Springer Singapore, 2014. http://dx.doi.org/10.1007/978-981-4585-30-9_13.

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Conference papers on the topic "LARGE INFLUENCERS"

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Moraes, Leonardo, and Robson Cordeiro. "Detecting Influencers in Very Large Social Networks of Games." In 21st International Conference on Enterprise Information Systems. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007728200930103.

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Contero López, Pilar, Jorge Camba, and Manuel Contero. "An Analysis of Influencer Marketing Effectiveness in Luxury Brands using Eye tracking Technology." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002051.

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In this paper, we examine the advertising impact of influencers on the promotion of a luxury fashion item and the effect of the presentation style. More specifically, we focus on the application of eye-tracking technologies to analyze how consumers respond to different presentation strategies used by influencers when promoting a product in a photograph.We report the results of an experimental study in which a group of participants were exposed to a set of static visual stimuli (i.e. photographs) related to new product launches by luxury fashion brands in the form of promotions by social media influencers. Individual responses were evaluated based on the participant’s ability to recall information from the stimuli as well as their recorded gaze points and fixations, which were tracked to identify areas in which the viewer had a particular interest at a specific time during exposure.Our results revealed that consumers tend to be impacted more heavily and recall a luxury item more easily when the product is promoted by influencers who appear not to be looking directly at the camera in the pictures (i.e. not making eye contact with the viewer). The percentage of individuals who correctly identified the luxury item with this type of stimulus was 87.5% as opposed to 46.25% when the influencer was looking directly at the camera. In addition to the influencers' visual contact, two other aspects were evaluated: the impact of the influencers' popularity and the aesthetic characteristics of the photographs used as stimuli.Our study confirms the effectiveness of the marketing strategies pioneered by some of the most recognized luxury fashion brands and delivered by influencers, particularly if the influencer does not establish visual contact with the target audience. This type of communication enables a more targeted type of advertising which moves from the exclusivity of promoting luxury fashion brands in certain events and marketing campaigns by celebrities to influencers that can reach large audiences on social networks.
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Bhattacharyya, Mayukh, Sayan Nag, and Udita Ghosh. "Deciphering Environmental Air Pollution with Large Scale City Data." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/698.

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Air pollution poses a serious threat to sustainable environmental conditions in the 21st century. Its importance in determining the health and living standards in urban settings is only expected to increase with time. Various factors ranging from artificial emissions to natural phenomena are known to be primary causal agents or influencers behind rising air pollution levels. However, the lack of large scale data involving the major artificial and natural factors has hindered the research on the causes and relations governing the variability of the different air pollutants. Through this work, we introduce a large scale city-wise dataset for exploring the relationships among these agents over a long period of time. We also introduce a transformer based model - cosSquareFormer, for the problem of pollutant level estimation and forecasting. Our model outperforms most of the benchmark models for this task. We also analyze and explore the dataset through our model and other methodologies to bring out important inferences which enable us to understand the dynamics of the casual agents at a deeper level. Through our paper, we seek to provide a great set of foundations for further research into this domain that will demand critical attention of ours in the near future.
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Bhattacharjya, Debarun, Oktie Hassanzadeh, Ronny Luss, and Keerthiram Murugesan. "Probabilistic Rule Induction from Event Sequences with Logical Summary Markov Models." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/629.

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Event sequences are widely available across application domains and there is a long history of models for representing and analyzing such datasets. Summary Markov models are a recent addition to the literature that help identify the subset of event types that influence event types of interest to a user. In this paper, we introduce logical summary Markov models, which are a family of models for event sequences that enable interpretable predictions through logical rules that relate historical predicates to the probability of observing an event type at any arbitrary position in the sequence. We illustrate their connection to prior parametric summary Markov models as well as probabilistic logic programs, and propose new models from this family along with efficient greedy search algorithms for learning them from data. The proposed models outperform relevant baselines on most datasets in an empirical investigation on a probabilistic prediction task. We also compare the number of influencers that various logical summary Markov models learn on real-world datasets, and conduct a brief exploratory qualitative study to gauge the promise of such symbolic models around guiding large language models for predicting societal events.
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Hansen, H. R., and T. Dinham-Peren. "EEDI Challenges in the Design of Large Slow-Speed Ships." In Influence of EEDI on Ship Design 2014. RINA, 2014. http://dx.doi.org/10.3940/rina.eedi.2014.03.

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Klímová, Viktorie, and Lucie Herbočková. "Teritoriální marketing v inovativních městech: Případová studie města graz." In XXIV. mezinárodního kolokvia o regionálních vědách. Brno: Masaryk University Press, 2021. http://dx.doi.org/10.5817/cz.muni.p210-9896-2021-52.

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The paper deals with the issue of city marketing. By its nature, this topic is gaining importance worldwide, especially in the practical sphere. The aim of the article is to demonstrate the implementation of marketing activities on the example of a large city, which is considered modern, open, environmentally friendly, and at the same time well-developed. The city of Graz in Austria was chosen for this case study. For this purpose, in-depth desk research was carried out. The city of Graz does not have an explicitly defined marketing strategy, but how it wants to present itself can be deduced from the Smart city strategy. The implementation of marketing activities is entrusted primarily to the municipal company Holding Graz. The main target groups include visitors, residents and businesses. Most of the marketing activities relate to the promotion of the inner city. Graz uses modern marketing tools such as websites, social networks, influencers and events. The city company MCG Graz focuses on organizing events at seven different locations in Graz.
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Griffin, Lewis, Bennett Kleinberg, Maximilian Mozes, Kimberly Mai, Maria Do Mar Vau, Matthew Caldwell, and Augustine Mavor-Parker. "Large Language Models respond to Influence like Humans." In Proceedings of the First Workshop on Social Influence in Conversations (SICon 2023). Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.sicon-1.3.

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Rui, Congshan, Suodong Ma, Peiji Guo, and Chunmei Zeng. "Influence of ply misalignment on form error in the manufacturing of CFRP mirrors with different layup sequences." In Large Mirrors and Telescopes, edited by Xiaoliang Ma, Bin Fan, Xiangang Luo, Adrian Russell, and Yongjian Wan. SPIE, 2019. http://dx.doi.org/10.1117/12.2504964.

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Jiang, Chunheng, Jianxi Gao, and Malik Magdon-Ismail. "Inferring Degrees from Incomplete Networks and Nonlinear Dynamics." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/457.

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Inferring topological characteristics of complex networks from observed data is critical to understand the dynamical behavior of networked systems, ranging from the Internet and the World Wide Web to biological networks and social networks. Prior studies usually focus on the structure-based estimation to infer network sizes, degree distributions, average degrees, and more. Little effort attempted to estimate the specific degree of each vertex from a sampled induced graph, which prevents us from measuring the lethality of nodes in protein networks and influencers in social networks. The current approaches dramatically fail for a tiny sampled induced graph and require a specific sampling method and a large sample size. These approaches neglect information of the vertex state, representing the dynamical behavior of the networked system, such as the biomass of species or expression of a gene, which is useful for degree estimation. We fill this gap by developing a framework to infer individual vertex degrees using both information of the sampled topology and vertex state. We combine the mean-field theory with combinatorial optimization to learn vertex degrees. Experimental results on real networks with a variety of dynamics demonstrate that our framework can produce reliable degree estimates and dramatically improve existing link prediction methods by replacing the sampled degrees with our estimated degrees.
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Varela, Antonia M., Casiana Munoz-Tunon, and Jean Vernin. "The influence of spot saturation on DIMM seeing measurements." In Second Backaskog Workshop on Extremely Large Telescopes, edited by Arne L. Ardeberg and Torben Andersen. SPIE, 2004. http://dx.doi.org/10.1117/12.566376.

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Reports on the topic "LARGE INFLUENCERS"

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Wodtke, A. M. Large Amplitude Vibrational Influence on Electron Transfer Reactions. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada421048.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, and Chun-Chieh Wu. Using NOGAPS Singular Vectors To Diagnose Large-scale Influences On Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada532804.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, James D. Doyle, Chun-Chieh Wu, and David S. Nolan. Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541929.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, James D. Doyle, Chun-Chieh Wu, and David S. Nolan. Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada574128.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, James D. Doyle, Chun-Chieh Wu, and David S. Nolan. Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada575524.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, James D. Doyle, Chun-Chieh Wu, and David S. Nolan. Using NOGAPS Singular Vectors to Diagnose Large-Scale Influences on Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada597866.

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Majumdar, Sharanya J., Melinda S. Peng, Carolyn A. Reynolds, James D. Doyle, Chun-Chieh Wu, and David S. Nolan. Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada557077.

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Lindahl, Mikael, Evelina Lundberg, Mårten Palme, and Emilia Simeonova. Parental Influences on Health and Longevity: Lessons from a Large Sample of Adoptees. Cambridge, MA: National Bureau of Economic Research, January 2016. http://dx.doi.org/10.3386/w21946.

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Moustakas, Leonidas A., Phil J. Marshall, Jeffrey A. Newman, Alison L. Coil, Michael C. Cooper, Marc Davis, Christopher D. Fassnacht, et al. A Strong-Lens Survey in AEGIS: the Influence of Large Scale Structure. Office of Scientific and Technical Information (OSTI), July 2006. http://dx.doi.org/10.2172/886784.

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R.B. White, V.V. Lutsenko, Y.I. Kolesnichenko, and Y.V. Yakovenko. Theory of Resonance Influence of Sawtooth Crashes on Ions with Large Orbit Width. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/3753.

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