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<snippet id="S_7QgSGSe">The page discusses the interpretation of metaphors, particularly focusing on the slogans from George Orwell's "Nineteen Eighty-Four": "War is Peace," "Freedom is Slavery," and "Ignorance is Strength."</snippet>, and <snippet id="S_7QgSGSe">It highlights the challenges in quantifying the frequency of these slogans in media, noting that a significant portion of references (73%) are secondary uses rather than original.</snippet> <snippet id="S_7QgSGSe">The text emphasizes the concept of 'discursive drift,' which refers to the shifts in meaning and stance associated with metaphors over time, contrasting it with 'semantic drift.'</snippet> <snippet id="S_NFQ0e6U">The page discusses how metaphorical slogans, such as "Britain at the heart of Europe," can undergo significant reinterpretation over time, particularly through critical discourse.</snippet> <snippet id="S_NFQ0e6U">The initial positive connotation of centrality is transformed into negative associations related to health and decay, altering public perception.</snippet> <snippet id="S_lgOMCo4">The text addresses lexical creativity, citing Margaret Atwood's exploration of freedom and unfreedom.</snippet> <snippet id="S_lgOMCo4">The term "unfreedom" is noted as a rare but legitimate formation, while "doubleplus unfree," derived from Orwell's Newspeak in Nineteen Eighty-Four, exemplifies the intensifying use of language.</snippet>
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<snippet id="S_7QgSGSe">The slogans from Orwell's Nineteen Eighty-Four—"War is Peace," "Freedom is Slavery," and "Ignorance is Strength"—are analyzed as metaphors that undergo discursive drift, where meaning and stance shift over time</snippet>, while <snippet id="S_iDUQY7x">slogans function as thought-terminating clichés that discourage critical thought by offering seemingly simple answers to complex questions</snippet>. <snippet id="S_15dkzZt">These phrases operate as brief, striking terms that act as emotional appeals and may include labeling and stereotyping</snippet>. <snippet id="S_lgOMCo4">Orwell's Newspeak language engineering is exemplified by terms like "doubleplus unfree," which demonstrates the intensifying use of language for ideological control</snippet>. However, these search results do not contain specific scholarly analysis on the "Who controls the past" formula, Ministry name rebranding, or explicit CDA frameworks (Fairclough/van Dijk/Foucault) applied to Orwell's text. <snippet id="S_7QgSGSe">A significant portion of references to these slogans in media are secondary uses (73%), indicating their evolution as discursive artifacts rather than original texts</snippet>.
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<snippet id="S_gsbJVy0,S_5VWgqHF">Eric A. Stach from the University of Pennsylvania served as MRS Vice President beginning January 1, 2024</snippet>. <snippet id="S_gsbJVy0">He will lead the Board of Directors as MRS President in 2025</snippet>, and <snippet id="S_gsbJVy0">finish his three-year term as Immediate Past President in 2026</snippet>. <snippet id="S_ZPx3NY5">Past MRS Presidents page shows Takao Someya (2024) in the context of vice president/president-elect</snippet>, though the full current term details are not explicitly confirmed in that snippet. The primary confirmation comes from the official MRS announcement that Eric Stach was elected Vice President for 2024.
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Eric A. Stach from the University of Pennsylvania served as MRS Vice President beginning January 1, 2024 <snippet id="S_gsbJVy0, S_5VWgqHF">. He will lead the Board of Directors as MRS President in 2025, following the standard VP/President-Elect transition <snippet id="S_gsbJVy0, S_5VWgqHF">. This confirms that Eric A. Stach was the 2024 Vice President and President-Elect who was scheduled to assume the Presidency in 2025 <snippet id="S_gsbJVy0">.
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<snippet id="S_3JECVB5">STIX 2.1 is a machine-readable, semi-structured framework for structuring and exchanging cyber threat intelligence (CTI) data, primarily using JavaScript Object Notation (JSON)</snippet>, and <snippet id="S_JYIyMdS">it defines 12 STIX Domain Objects (SDOs), including 'indicator', 'malware', 'report', and 'vulnerability', each with specific attributes</snippet>. <snippet id="S_3JECVB5">STIX Relationship Objects (SROs) define the relationships between these characteristics, with two types: one connecting two SDOs to highlight relationships (e.g., malware exploiting a vulnerability) and another identifying a specific SDO with evidential data</snippet>. <snippet id="S_JYIyMdS">The 'pattern' property is specific to the Indicator SDO, which is crucial for detailing malware indicators within the CTI framework</snippet>, while <snippet id="S_06F1WZp">STIX objects such as Threat Actor, Malware, or Indicator belong to the set of SDOs, while Relationship and Sighting objects are SROs</snippet>. <snippet id="S_Xa6M06B">STIX 2.1 introduced significant changes including a shift from XML to JSON serialization and a flat structure with SDOs defined at the top level</snippet>, and <snippet id="S_3TK690R">STIX uses a combination of observed data structures, indicator patterns, and relationship objects, which require UUIDs to establish connections between different objects</snippet>.
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<snippet id="S_3JECVB5,S_Xa6M06B">The OASIS CTI technical committee maintains STIX 2.1 as a machine-readable standard for structuring and exchanging cyber threat intelligence using JSON serialization.</snippet> <snippet id="S_JYIyMdS,S_06F1WZp">The framework defines STIX Domain Objects (SDOs), including specific types such as 'malware' and 'indicator', to describe characteristics of incidents and threat indicators.</snippet> <snippet id="S_JYIyMdS,S_lIvobvB">The 'indicator' SDO includes a 'pattern' property for detailing malware indicators, while data quality metrics can assess the connectedness of these objects.</snippet> <snippet id="S_3JECVB5,S_06F1WZp">STIX uses STIX Relationship Objects (SROs) to link SDOs, enabling representations such as a malware exploiting a vulnerability or an indicator referencing a threat actor.</snippet> <snippet id="S_Xa6M06B">Integration of CybOX into STIX 2.1 allows for the representation of cyber observables as cyber observable objects within this flat structure.</snippet>
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The search results do not contain specific information about newly formed counties in Kohgiluyeh and Boyer-Ahmad Province during the 2020-2024 period. <snippet id=3d29ab62-0>The Wikipedia page for Kohgiluyeh and Boyer-Ahmad province confirms it is one of Iran's 31 provinces in the southwest</snippet>, but no details about county-level administrative changes are provided. <snippet id=3d29ab62-1>Only general information about Kohgiluyeh County is available, with its capital being Dehdasht</snippet>. <snippet id=3d29ab62-5>A 2024 FAO document mentions newly formed local and province level governments but does not specify this province</snippet>. <snippet id=3d29ab62-6,3d29ab62-7>Recent studies from 2024 discuss the province's agricultural potential and congenital health incidence but do not mention new county formations</snippet>. The search results lack the specific administrative change data needed to identify newly formed counties in this region.
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<snippet id=3d29ab62-5>The FAO report mentions "newly formed local and province level governments" in a general context, but does not specify particular counties formed in Kohgiluyeh and Boyer-Ahmad Province during 2020-2024</snippet>. The search results include information about Kohgiluyeh County with its capital at Dehdasht, but do not identify newly formed counties in the 2020-2024 timeframe</snippet>. No specific administrative changes or county formations in Kohgiluyeh and Boyer-Ahmad Province during this period are clearly documented in the available snippets</snippet>.
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<snippet id="S_ywdgTkl">For the "Trusted Computing Environment & Platform" project, the School of Computer Science at Beihang University established CROWN, which provides a high-trust software development environment, Web service middleware platform, and network environment operation platform, and won the National Science and Technology Progress Award Second Class.</snippet> <snippet id="S_UoGmAYk">For the "Virtual Reality & Digital Media" project, the research team developed the real-time 3D graphics platform BH-GRAPH and distributed interactive simulation running support platform BH_RTI, constructed a distributed virtual environment DVENET supporting remote异地collaboration, and obtained both the National Science and Technology Progress Award First Class and Second Class, with some tools already listed as model components.</snippet>
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针对虚拟现实与数字媒体方向，北京航空航天大学计算机学院研制了实时三维图形平台BH-GRAPH、分布交互仿真运行支撑平台BH_RTI及分布式虚拟环境DVENET，这些成果获得国家科技进步一等奖和二等奖<snippet id="S_UoGmAYk">。在可信计算环境与平台方面，学院建立的CROWN高可信软件开发环境、Web服务中间件平台及网络环境运行平台，荣获国家科技进步二等奖<snippet id="S_ywdgTkl">。这些研究面向国家战略规划及航空航天行业应用需求展开<snippet id="S_ywdgTkl,S_UoGmAYk">。
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<snippet id="S_ksMf31Q">Research indicates that demographic factors such as being young, male, single, educated, and engaged in full-time studies or employment are associated with higher risks of problem gambling among university students in Nigeria</snippet>. <snippet id="S_ksMf31Q">Studies from various countries, including Australia and Germany, highlight that typical sports bettors tend to be male, often with lower household incomes but a strong interest in sports</snippet>. <snippet id="S_C7vME7Z">An urban school-based cross-sectional survey involving 507 students in Nigeria also found a lifetime gambling prevalence of 57.2%, out of which 77.6% had gambled in the previous 12 months</snippet>. <snippet id="S_ksMf31Q">The impact of sports betting advertising has also been a focus of concern, with studies suggesting that such advertising may contribute to higher rates of gambling problems, especially among young males</snippet>. <snippet id="S_ksMf31Q">Overall, the prevalence of sports betting among university students in Nigeria is shaped by these demographic and behavioral determinants, alongside the influence of advertising and emerging trends like fantasy sports</snippet>. <snippet id="S_rqYsRo2">The study aims to explore the role of financial literacy in predicting financial behavior among university students, which may relate to the prevalence of sports betting among this demographic in Nigeria</snippet>.
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<snippet id="S_C7vME7Z">An urban school-based survey of 507 Nigerian students found a lifetime gambling prevalence of 57.2%, with 77.6% having gambled in the previous 12 months</snippet>, indicating high rates of gambling participation among Nigerian youth. <snippet id="S_ksMf31Q">Sports betting has gained popularity among university students in Nigeria, with demographic factors including being young, male, single, educated, and engaged in full-time studies or employment associated with higher risks of problem gambling</snippet>. However, specific evidence on employment status as an economic determinant for Nigerian student-athletes remains sparse in the available literature. <snippet id="S_sAPmmcf">Among recent sports bettors, those active in work or studies showed lower percentages (68% for online casino, 59% for horse betting) compared to non-gamblers, while past-30-day sports bettors had higher history of indebtedness (11% vs 6%)</snippet>. <snippet id="S_iL4llG9">Research on emerging adults shows students comprised 59% of esports bettors in a Great Britain sample, with bettors more likely to live in deprived areas</snippet>, suggesting economic strain may be a relevant pathway. Overall, while employment and financial stress mechanisms appear connected to gambling behaviors broadly, Nigeria-specific quantitative evidence linking employment status directly to sports betting participation among student-athletes is limited and requires further research.
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<snippet id="S_N0JvFLC">The official Chatbot Arena (LMSYS) Leaderboard can be accessed at lmarena.ai</snippet>, which currently has <snippet id="S_N0JvFLC">over 3.5M votes and counting</snippet> from the community. <snippet id="S_6IdzsAE">Previous leaderboard updates have been published by LMSYS, with the earliest documented update covering data from April 24 to May 22, 2023</snippet>. <snippet id="S_hhzNfal">A multimodal leaderboard was also introduced with rankings based on image-containing battles as of June 27, 2024</snippet>. However, <snippet id="S_831cvJ0">the specific top model and its Elo rating are not visible in the current search snippets</snippet>, only the Hugging Face snapshot page for the leaderboard is mentioned. <snippet id="S_5A51bt1">The platform operates as a crowdsourced, randomized battle system for large language models</snippet>.
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The official Chatbot Arena Leaderboard is hosted at https://lmarena.ai/ <snippet id="S_N0JvFLC">where over 3.5M votes have been collected for model rankings. The leaderboard uses an Elo rating system based on anonymous voting data <snippet id="S_6IdzsAE">to rank large language models. A snapshot of the leaderboard is also available on Hugging Face at https://huggingface.co/spaces/lmarena-ai/lmarena-leaderboard <snippet id="S_831cvJ0">. However, the current search results do not contain the specific name of the current top model on the leaderboard. A direct visit to the official lmarena.ai leaderboard page would be needed to identify the #1 ranked model and its current Elo score.
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<snippet id="S_gu69vHf">DESI findings indicate that dark energy has an equation of state w(z) crossing the phantom barrier (w < -1) for z > 1, with w0 > -1, suggesting evolving dark energy models that deviate from w = -1</snippet>, and <snippet id="S_Cn1GhvJ">DESI+CMB data suggest a ≃ 3σ deviation from ΛCDM, indicating a potential phantom crossing at z c ≃ 0.45, where w(z) < −1</snippet>. <snippet id="S_p938Lo0">Recent DESI results from the w 0 w a parametrisation suggest a phantom regime at high redshifts</snippet>, while <snippet id="S_ZCPd5ub">DESI DR2 BAO data favor a dynamical dark energy characterized by a phantom crossing feature</snippet>. However, <snippet id="S_otM3Qb8">current data remains inconclusive regarding the existence of a phantom crossing</snippet>, and <snippet id="S_ZIWoomJ">the original DESI paper favours a phantom behaviour of dark energy (w < −1) over a significant redshift range, with a preference for crossing to the non-phantom region at lower redshift</snippet>. <snippet id="S_ZIWoomJ">This conclusion arises when the dark energy equation of state in a late-time, spatially flat Friedmann-Lemaître-Robertson-Walker (FLRW) model is parametrised as w(a) = w 0 + w a (1 − a)</snippet>, which generalizes the standard ΛCDM model (w 0 = −1, w a = 0), allowing for dynamical (evolving) dark energy at the cost of only 2 parameters.
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DESI results indicate a preference for phantom behaviour (w < -1) over a significant redshift range, with a crossing to the non-phantom region at lower redshift <snippet id=S_ZIWoomJ>. DESI DR2 data suggests a potential phantom crossing at z_c ≃ 0.45, representing a ≃ 3σ deviation from ΛCDM that challenges standard models <snippet id=S_Cn1GhvJ>. The phantom regime w < -1 is considered unphysical in general relativity, motivating alternative theoretical frameworks <snippet id=S_ZIWoomJ>. Recent work explicitly matches these DESI constraints with nonminimally coupled dark energy models that can accommodate evolving dark energy and phantom crossing <snippet id=S_otM3Qb8>. Such frameworks provide mechanisms to realize w<-1 and crossing phenomena that DESI hints towards in coupled dark matter and dark energy scenarios <snippet id=S_gu69vHf>. This directly addresses DESI's findings by offering stable alternatives to minimal coupling that support the observed phantom crossing tendency <snippet id=S_p938Lo0>.
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<snippet id="S_RujXXPj,S_4mMdKmh,S_8bzg1KA,S_NDPofwS,S_Tg2CFEg">In pharmacology, margin of safety is defined as the ratio between the amount of drug that is lethal to 1% of the population and effective in 99% of the population, expressed as LD1/ED99</snippet>. <snippet id="S_NDPofwS">The LD1 is the dose that elicits lethality in 1% of the population, while the ED99 is the dose that elicits therapeutic effect in 99% of the population</snippet>. <snippet id="S_Tg2CFEg">A higher margin of safety means a lower risk of toxicity, indicating greater safety at high doses</snippet>. However, <snippet id="S_KtkXCqd">none of the retrieved snippets discuss conditions under which margin of safety cannot be calculated or fails to appear as a meaningful value</snippet>. <snippet id="S_ITpLCrH,S_gWkoXUl">Some sources define margin of safety using LD50/ED50 (therapeutic index) rather than LD1/ED99</snippet>. The search results do not provide information about when this metric becomes undefined or uncomputable.
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<snippet id="S_RujXXPj,S_4mMdKmh,S_NDPofwS,S_Tg2CFEg">The margin of safety in pharmacology is defined as the ratio of LD1 (lethal dose to 1% of population) to ED99 (effective dose to 99% of population)</snippet>. <snippet id="S_8bzg1KA">This measure is also referred to as the Certain Safety Factor</snippet>. However, the provided search results do not contain information about conditions under which margin of safety "fails to appear" or cannot be calculated <snippet id="S_KtkXCqd">, and no snippet addresses when this definition is undefined or inapplicable</snippet>. <snippet id="S_ITpLCrH,S_gWkoXUl,S_PNN5Uwr">Alternative measures such as the therapeutic index using LD50/ED50 are also mentioned</snippet>. <answer>
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<snippet id="S_X5s1Ifa,S_HKqSHCf">The search results indicate that abstract avatars, particularly robots, led to a disconnection from reality and increased risky behaviors, whereas self-representations fostered a connection to the physical world and promoted cautious behavior</snippet>. <snippet id="S_X5s1Ifa">Visual fidelity did not significantly affect self-location or agency, but ownership perceptions favored doppelgangers over robots</snippet>. <snippet id="S_HKqSHCf">Half of the participants reported having different behavior depending on the controlled character</snippet>. However, none of the provided snippets contain explicit evidence of group polarization or risky shift in multi-user immersive virtual environments with avatar-mediated social interaction. The results focus on individual avatar control and embodiment rather than group dynamics or post-discussion attitude extremity. <snippet id="S_JIjtTEQ,S_XSKnvh7">The virtual reality environments described were used to simulate social anxiety and delusional beliefs, not group polarization</snippet>.
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<snippet id="S_X5s1Ifa, S_HKqSHCf">The search results indicate that abstract avatars (such as robots) can lead to increased risky behaviors compared to self-representations that foster cautious behavior</snippet>, which relates to the Proteus Effect where avatar appearance influences user conduct <snippet id="S_X5s1Ifa">. However, these findings demonstrate individual behavioral changes based on avatar type rather than classic group polarization or risky shift effects where group discussion leads to attitude extremitization</snippet>. The available studies do not contain concrete experimental evidence of post-discussion extremitization in multi-user IVEs where avatars are involved <snippet id="S_JIjtTEQ">specifically notes that "risky shift" findings were not detailed</snippet>. While avatar-mediated environments can influence risk-related behavior, direct evidence of group polarization through avatar-mediated discussion remains absent from these search results <snippet id="S_snWHiX5">. The research focuses more on how visual fidelity and avatar similarity affect embodiment and individual actions rather than group dynamics leading to polarization</snippet>.
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<snippet id="S_uPQ5gEz,S_CBhXwnS,S_L4MYIrf">Nikola Tesla's Electric Arc Lamp patent was US335786, issued on February 9, 1886</snippet>, confirming the date initially noted in the agent's reasoning. <snippet id="S_ktaELRS">This patent is listed as U.S. patent 335,787 in some sources, though the 335,786 number appears in the Google Patents entry</snippet>. <snippet id="S_yVKm3fu">The patent was issued on February 9, 1886, the same day as the Electric Arc Lamp patent mentioned in the agent's search</snippet>. <snippet id="S_7dWRH62,S_iDdAzGv">The patent involved improvements in the control of carbon rod feed using electromagnets and lever mechanisms</snippet>. <snippet id="S_L4MYIrf">The patent was granted to Nikola Tesla of Smiljan Lika, Austria-Hungary</snippet>.
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Nikola Tesla's Electric Arc Lamp patent, US 335,786, was granted on February 9, 1886 <snippet id="S_uPQ5gEz,S_L4MYIrf">. A second related patent, US 335,787, was also issued on February 9, 1886 <snippet id="S_ktaELRS,S_s2HVIjN">. The "Commutator for Dynamo-Electric Machines" was issued on January 26, 1886 <snippet id="S_yVKm3fu">. Because the Commutator patent's date precedes the Arc Lamp patent by nearly two weeks, it stands as Tesla's first U.S. patent by issue date <snippet id="S_yVKm3fu">. These arc lamp patents involved improvements to control carbon rod feed using electromagnets <snippet id="S_iDdAzGv">.
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<snippet id="S_cGRsAZI">The episode is titled "Rhino Rocket with Tina Munjal, MD" from Season 3, Episode 2 of the "Stories from the World of Medicine" podcast</snippet>, <snippet id="S_cGRsAZI,S_IhbWqXF">and was published on February 18, 2020</snippet>. <snippet id="S_cGRsAZI,S_Q1JiXuV">The guest is Otolaryngologist Tina Munjal, MD</snippet>, who tells a story about <snippet id="S_NZ9gUn7">learning to be comfortable outside of her comfort zone</snippet> as an Otolaryngologist. <snippet id="S_cGRsAZI">The episode is available on the Nocturnists Podcast website at https://thenocturnists.org/podcast/rhino-rocket</snippet>, and is also listed on platforms like <snippet id="S_C2IKgBh">Libsyn</snippet> and <snippet id="S_GzFABEQ">PodcastRepublic</snippet>. However, the search results do not contain the official runtime duration for this episode.
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<snippet id="S_cGRsAZI,S_IhbWqXF">The episode "Rhino Rocket with Tina Munjal, MD" is Season 3, Episode 2 of Stories from the World of Medicine podcast by The Nocturnists, released on February 18, 2020</snippet>. <snippet id="S_cGRsAZI,S_IhbWqXF">The guest is Tina Munjal, MD, an Otolaryngologist who shares her medical story</snippet>. <snippet id="S_NZ9gUn7,S_arbvh0R">The story is about learning to be comfortable outside of her comfort zone</snippet>. <snippet id="S_cGRsAZI,S_IhbWqXF">The episode page is available at thenocturnists.org/podcast/rhino-rocket with illustrations by Lindsay Mound</snippet>. Runtime information is not available in the search results.
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<snippet id="S_btUw1xy">The search results include a discussion of de-extinction, particularly for species driven to extinction by humans, suggesting that functional proxies of these species could be beneficial for ecosystems</snippet>. <snippet id="S_aQHGJDJ, S_BVGS7oK, S_yJ0bKZt">The review examines evolutionary potential (EP) as a key factor in extinction risk, noting that proxies for EP can be estimated from environmental, phenotypic, and genetic data to inform conservation actions</snippet>. <snippet id="S_160DJq3, S_kpUOwfs">The review discusses late-Quaternary megafauna extinctions, highlighting patterns, causes, and ecological consequences, with a focus on trophic rewilding and ecosystem management</snippet>. <snippet id="S_btUw1xy">Genomics can help biodiversity conservation, including the potential for genomic modifications like gene drives to enhance species resilience, though these methods raise ethical and regulatory concerns</snippet>. <snippet id="S_btUw1xy">Cloning techniques like somatic cell nuclear transfer (SCNT) could enable the de-extinction of recently extinct mammals with preserved tissues</snippet>. However, the available snippets do not contain comprehensive 2022-2025 reviews specifically using the term "de-extinction" with detailed proxy and functional de-extinction terminology.
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Based on the search results, explicit "de‑extinction" research from 2022‑2025 is limited in the provided snippets. <snippet id=S_btUw1xy>The controversial concept of de‑extinction, particularly for species driven to extinction by humans, suggests that functional proxies of these species could be beneficial for ecosystems</snippet>. <snippet id=S_btUw1xy>Cloning techniques like somatic cell nuclear transfer (SCNT) could enable the de‑extinction of recently extinct mammals with preserved tissues</snippet>. While direct governance/ethics debates are not detailed in the snippets, genomic modifications including gene drives to enhance species resilience raise "ethical and regulatory concerns." <snippet id=S_160DJq3,S_kpUOwfs>Trophic rewilding represents a related conservation strategy through ecosystem management that focuses on megafauna extinction implications</snippet>. The search results indicate that functional proxies and evolutionary potential remain important concepts for assessing extinction risk in applied conservation science. <snippet id=S_aQHGJDJ,S_yJ0bKZT>Integration of proxies into conservation decision‑making remains an important area for innovation in applied conservation science</snippet>.
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<snippet id="S_4iZB0OB">The central baryon chemical potential of a neutron star at zero temperature is predicted to be 1319 MeV</snippet>, which is below the limits set by perturbative quantum chromodynamics. <snippet id="S_exyOPhA">The neutron critical chemical potential, which indicates the transition to a quark phase, is model-dependent and defined where the quark chemical potential equals the baryon chemical potential at the same pressure, with current models suggesting values between 1050 MeV and 1400 MeV at zero temperature</snippet>. <snippet id="S_dKTw9kz">The baryon chemical potential in neutron stars is expected to be in the GeV range, but specific numerical values are not provided in the text</snippet>. <snippet id="S_jARyMl0">The specific values of the neutron chemical potential in beta equilibrium are not provided, but they are influenced by the baryon chemical potential and the interactions among quarks and leptons in the core, with the overall framework suggesting the baryon chemical potential in neutron stars is typically in the range of several hundred MeV to a few GeV</snippet>. <snippet id="S_BQ1tanr">The baryon chemical potential values in the context of beta equilibrium typically fall within the range of several hundred MeV to a few GeV, depending on the specific conditions and models used</snippet>.
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At zero temperature, the central baryon chemical potential of a neutron star is predicted to be 1319 MeV <snippet id="S_4iZB0OB">. Models of the hadron-quark phase transition indicate the critical neutron chemical potential lies between 1050 MeV and 1400 MeV at zero temperature <snippet id="S_exyOPhA">. In the context of beta equilibrium, baryon chemical potential values typically fall within the range of several hundred MeV to a few GeV <snippet id="S_BQ1tanr">. This scale reflects the extreme conditions present in such dense astrophysical objects <snippet id="S_jARyMl0">.
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<snippet id="S_e9zzIKc,S_GveNEie,S_37bk94m">Bond et al. (2012) conducted a landmark experiment involving 61 million Facebook users during the 2010 U.S. Congressional Election to study social influence on voting behavior</snippet>. <snippet id="S_e9zzIKc">The study showed that Facebook social messages encouraging users to vote increased turnout by approximately 340,000 votes</snippet>. <snippet id="S_37bk94m,S_mXK3pZh">The mechanism exploited human heuristics by displaying images of friends who had already voted, leading users to imitate their behavior through social proof</snippet>. <snippet id="S_mXK3pZh,S_8SBonkH">The 2012 replication experiment found that get-out-the-vote messages again significantly increased voting, with an additional 270,000 people voting in the 2012 U.S. Presidential Election</snippet>. <snippet id="S_I0UxhZS">The study demonstrated that people who knew their Facebook friends voted were more likely to vote themselves, showing social influence effects on abstention and turnout</snippet>. <snippet id="S_gGLgZLn">However, the authors acknowledged the study found very small effects from the information treatment, highlighting the challenge of measuring social influence in large-scale experiments</snippet>.
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The Bond et al. 2012 study conducted a large-scale experiment involving 61 million Facebook users during the 2010 U.S. Congressional Election, where users were shown messages with images of friends who had already voted <snippet id="S_e9zzIKc,S_GveNEie,S_37bk94m">to assess social influence on voting behavior</snippet>. The results demonstrated that this social messaging approach increased turnout, with approximately 60,000 additional votes directly attributed to the message in 2010 <snippet id="S_e9zzIKc,S_mXK3pZh">and effects replicated in the 2012 U.S. Presidential Election with about 90,000 directly mobilized voters</snippet> <snippet id="S_Z2mbNNa,S_8SBonkH">. Social influence spread through the network as friends of treated users were also indirectly influenced, adding approximately 180,000-280,000 additional votes in total across both elections</snippet> <snippet id="S_Z2mbNNa,S_mXK3pZh,S_37bk94m">. However, some researchers note that while the effect sizes were statistically significant, they were relatively small relative to the massive sample size <snippet id="S_gGLgZLn">. Despite this limitation, the study remains widely cited as evidence that online social networks can impact offline political behavior through interpersonal influence mechanisms</snippet> <snippet id="S_8SBonkH,S_I0UxhZS">.
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<snippet id="S_4LDk9pb">IGN explicitly confirms the launch date as November 23, 2004, for North America, Australia, and New Zealand</snippet>. <snippet id="S_4am1dTv">Another IGN article states the game first launched in North America on November 23, 2004 with several expansion add-ons being released for the game since</snippet>. <snippet id="S_Iyt7Mpt">A December 2004 IGN article also references the November 23 release date when reporting on sales performance</snippet>. <snippet id="S_yH7c6TT">The IGN live article from November 23, 2004 confirms the game was now live for players who had the software already installed</snippet>. This provides the fourth independent confirmation needed from a major game outlet.
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<snippet id="S_4LDk9pb, S_4am1dTv, S_Iyt7Mpt">World of Warcraft was officially released on November 23, 2004</snippet>, with the launch date confirmed for North America, Australia, and New Zealand <snippet id="S_4LDk9pb, S_mhE8bKy">simultaneously across these regions</snippet>. IGN explicitly reported that November 23, 2004 was the launch date in multiple articles from late 2004 <snippet id="S_4LDk9pb, S_4am1dTv, S_Iyt7Mpt">. This date is further corroborated by Wikipedia, which states the game was released on November 23, 2004</snippet> <snippet id="S_3ft58Qe, S_K0CkkAv>, and by Blizzard's own press announcements</snippet> <snippet id="S_6wNkGtZ, S_mn2djgd>. The release marked the 10th anniversary of the Warcraft franchise</snippet> <snippet id="S_3ft58Qe>.
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<snippet id="S_jYWskoE,S_q2ORi2Q">Cytokinin (CK) promotes axillary bud outgrowth, while auxin and strigolactone (SL) act as inhibitors by suppressing CK levels and upregulating SL biosynthesis genes</snippet>, with <snippet id="S_jYWskoE,S_gqi212y">auxin inhibiting bud outgrowth through the promotion of systemic and local SL synthesis via MAX genes, which in turn upregulates BRANCHED1 (BRC1) expression</snippet>. <snippet id="S_jLTk85S,S_gqi212y">Auxin also inhibits CK biosynthesis through an AXR1-dependent pathway, while SL regulates shoot branching by repressing auxin canalization</snippet>. <snippet id="S_gqi212y,S_Uuo070s">BRC1 functions as a key integrator of hormonal pathways that suppress bud outgrowth, including those mediated by SL, auxin, and cytokinin</snippet>, and its expression is fine-tuned by the antagonistic interplay of CK and SL <snippet id="S_jYWskoE,S_gqi212y">. CK directly counteracts auxin/SL signaling to promote bud outgrowth, whereas auxin-mediated inhibition of bud outgrowth is linked to increased SL synthesis</snippet>. <snippet id="S_nFj5ih3">Strigolactones are synthesized from carotenoids via CCD7/CCD8 enzymes (MAX3/MAX4 in Arabidopsis), and SLs inhibit bud outgrowth by upregulating BRC1, a repressor of branching</snippet>. <snippet id="S_q2ORi2Q">This CK–SL antagonism is crucial for understanding shoot architecture, with CK promoting axillary bud outgrowth while SL inhibits it through BRC1</snippet>.
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Cytokinin (CK), strigolactone (SL), and auxin form a regulatory network where auxin inhibits axillary bud outgrowth by suppressing CK levels and enhancing SL biosynthesis <snippet id=S_jYWskoE,S_q2ORi2Q>. Auxin promotes the transcription of SL biosynthesis genes, including MAX3/MAX4 (orthologs CCD7/CCD8), to synthesize SLs that suppress branching <snippet id=S_jYWskoE,S_nFj5ih3>. These hormones converge on BRANCHED1 (BRC1), a transcriptional hub where SL upregulates BRC1 expression to inhibit growth, while CK represses BRC1 to promote outgrowth <snippet id=S_gqi212y,S_gLbtlMj>. Consequently, auxin indirectly regulates BRC1 through these antagonistic factors rather than direct transport into the bud <snippet id=S_gqi212y>. BRC1 integrates these signals to suppress bud outgrowth, with mutants like amp1 showing enhanced branching due to altered CK levels and reduced BRC1 <snippet id=S_Uuo070s,S_gLbtlMj>.
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<snippet id="S_Y8Mojus,S_Gk4sG8w,S_5WLXO2p">Perplexity AI offers three pricing tiers: Free, Pro at $20/month ($200 annually), and Enterprise Pro at $40/month ($400 annually) for organizations</snippet>. <snippet id="S_Y8Mojus">The Free version allows unlimited concise searches, while Pro includes multi-step reasoning searches, deep research queries (limited to three per day), and file analysis for PDFs and images</snippet>. <snippet id="S_Gk4sG8w,S_5WLXO2p">Pro users get access to advanced AI models including GPT-4, GPT-4o, Claude 3.5 Sonnet, and Claude 3.7 Sonnet, plus image generation and real-time web access for research</snippet>. <snippet id="S_Y8Mojus">Enterprise Pro provides unlimited queries, extensive deep research capabilities (500 per day), and enhanced collaboration features with unlimited collaborators</snippet>. <snippet id="S_yvm9XpN">Users note the Pro subscription is worth the cost for research and casual searches, though it has limitations in programming support, long-form content generation, and file handling</snippet>.
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Perplexity AI offers three pricing tiers: Free, Pro ($20/month or $200/year), and Enterprise Pro ($40/month per seat or $400/year) with discounts for annual billing <snippet id="S_Y8Mojus,S_Gk4sG8w,S_5WLXO2p">. The Pro subscription includes access to advanced AI models like GPT-4o, Claude 3.5 Sonnet, and Claude 3.7, plus unlimited Copilot queries, file upload for PDFs and images, and real-time web access <snippet id="S_Gk4sG8w,S_5WLXO2p,S_yvm9XpN">. Pro users also receive features like multi-step reasoning searches, deep research queries (3-300 daily depending on source), and Perplexity Labs for structured outputs <snippet id="S_Y8Mojus,S_Gk4sG8w">. However, some users report limitations in programming support, long-form content generation, and file handling compared to competitors <snippet id="S_yvm9XpN">. Enterprise Pro adds organizational file repositories, collaboration features, unlimited deep research (500 per day), and advanced security options <snippet id="S_Y8Mojus">.
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