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<snippet id="S_ixOFgje">The White House fact sheet announces 25% additional tariffs on imports from Canada and Mexico, and a 10% additional tariff on imports from China</snippet>. Energy resources from Canada will have a lower 10% tariff rate instead of 25%. <snippet id="S_ixOFgje">These tariff rates are part of President Trump's action to address illegal immigration and fentanyl threats, with the 25% rate on Canada/Mexico and 10% on China specified as additional tariffs</snippet>. The fact sheet also notes that trade accounts for 67% of Canada's GDP, 73% of Mexico's GDP, and 37% of China's GDP, but only 24% of U.S. GDP. <snippet id="S_ixOFgje">The announcement references a Presidential Memorandum from November promising to charge Mexico and Canada 25% tariffs on all products until drugs and illegal aliens stop the "invasion" of the country</snippet>. Specific trade values, retaliation measures, and EU-specific tariff rates are not covered in this particular White House fact sheet.
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<snippet id="S_ixOFgje">The White House fact sheet specifies a 25% additional tariff on imports from Canada and Mexico, with energy resources from Canada receiving a lower 10% tariff, while China faces a 10% additional tariff</snippet>. <snippet id="S_ixOFgje">The fact sheet notes that in 2023 the U.S. trade deficit in goods was the world's largest at over $1 trillion</snippet>, and that trade accounts for 67% of Canada's GDP, 73% of Mexico's GDP, and 37% of China's GDP. However, <snippet id="S_ixOFgje">this fact sheet does not include specific dollar trade values covered by the tariffs, any retaliation measures from Canada, China, or the EU, or quantitative economic impact estimates (consumer cost, inflation, GDP)</snippet>. The tariff announcement is dated February 2025 and cites the International Emergency Economic Powers Act as the legal basis. <snippet id="S_ixOFgje">The tariffs remain in effect "until such time as Drugs, in particular Fentanyl, and all Illegal Aliens stop this Invasion of our Country"</snippet> as per the presidential directive.
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<snippet id="S_7QgSGSe">Recent scholarship discusses the interpretation of metaphors, particularly focusing on the slogans "War is Peace," "Freedom is Slavery," and "Ignorance is Strength" from George Orwell's "Nineteen Eighty-Four"</snippet>, highlighting challenges in quantifying their frequency in media and emphasizing the concept of 'discursive drift' in metaphorical meaning shifts over time. <snippet id="S_lgOMCo4">The term "doubleplus unfree," derived from Orwell's Newspeak in Nineteen Eighty-Four, exemplifies the intensifying use of language</snippet> in scholarly discussions of Orwell's linguistic engineering. <snippet id="S_iDUQY7x">Slogans are defined as brief and striking phrases that may include labeling and stereotyping, tending to act as emotional appeals</snippet>, while <snippet id="S_15dkzZt">they are also characterized as a brief and striking phrase that may include labeling and stereotyping, tending to act as emotional appeals</snippet> in the context of propaganda detection. <snippet id="S_tpXkvyW">Metaphoric themes in political discourse are deployed to project covert ideology of the speakers by showing shared experiences</snippet>, helping to exert influence on the general public. However, <snippet id="S_7QgSGSe">the analysis suggests that the slogans can evolve in their interpretation and application within public discourse, reflecting changing societal attitudes and contexts</snippet>, which contrasts with the agent's goal of grounding CDA claims in scholarly readings of the original text.
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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>, which indicates he held the concurrent title of President-Elect during the 2024 term. <snippet id="S_ZPx3NY5">Past MRS Presidents page also confirms Takao Someya (2024) in the vice president/president-elect context</snippet>, though Eric Stach's appointment is explicitly documented as starting in January 2024 for the 2025 leadership transition. The official MRS announcement from September 2024 confirms the Vice President/President Elect designation for the 2025 board team <snippet id="S_Mcho4xl">. Eric A. Stach is the confirmed individual who served as both Vice President and President-Elect for 2024</snippet>.
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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">The OASIS STIX 2.1 format is a machine-readable, semi-structured framework for structuring and exchanging cyber threat intelligence (CTI) 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</snippet>, with <snippet id="S_JYIyMdS">two STIX Relationship Objects enabling the linking of multiple SDOs to facilitate complex representations of CTI</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>, while <snippet id="S_Xa6M06B">the integration of CybOX into STIX 2.1 allows for the representation of cyber observables as cyber observable objects</snippet>. <snippet id="S_lIvobvB">For malware-specific indicators, the CSI value fills the pattern property of the Indicator SDO</snippet>, and <snippet id="S_3M0PARM">real-world datasets show that 75% of STIX bundles include a Malware entity with relationships to threat actors and vulnerabilities</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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<snippet id=3d29ab62-0,3d29ab62-1>The search results do not provide information about newly formed counties in Kohgiluyeh and Boyer-Ahmad Province during 2020-2024</snippet>. <snippet id=3d29ab62-0>The available snippets only describe general province information, with no mention of county-level administrative changes</snippet>. <snippet id=3d29ab62-1>One snippet mentions Kohgiluyeh County but only provides basic location and capital information, not recent formation status</snippet>. <snippet id=3d29ab62-2,3d29ab62-3,3d29ab62-4,3d29ab62-5,3d29ab62-6,3d29ab62-7,3d29ab62-8,3d29ab62-9>The remaining search results cover various topics including language distribution, climate studies, and groundwater, with no reference to new county creation</snippet>. <snippet id=3d29ab62-5>The only snippet mentioning government formation references "newly formed local and province level governments" without specifying Kohgiluyeh and Boyer-Ahmad</snippet>.
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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 area, the project "可信计算环境与平台" won the National Science and Technology Progress Award Second Prize</snippet>, establishing CROWN and providing high-trust software development environment, Web service middleware platform, and network environment operation platform. <snippet id="S_UoGmAYk">For the Virtual Reality & Digital Media area, the project "虚拟现实与数字媒体" won the National Science and Technology Progress Award First Prize and Second Prize</snippet>, with real-time 3D graphics platform BH-GRAPH and distributed interactive simulation support platform BH_RTI as key tools. <snippet id="S_ywdgTkl,S_UoGmAYk">These awards are documented on the official Beihang University School of Computer Science website pages for each research area</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">Sports betting has gained popularity among university students in Nigeria, influenced by the accessibility of online platforms and smartphone applications</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">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_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_d3zPQEk">The findings contribute to understanding the factors influencing sports betting behaviors among university students in Nigeria, although specific data on that demographic is not detailed in this study</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 Leaderboard can be accessed through the LMArena platform at lmarena.ai</snippet>, which has collected over 3.5M votes and counting 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 current top model and its specific Elo rating are not provided in these search snippets</snippet>, requiring direct page access to capture the live leaderboard data.
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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, challenging standard scalar-field models of dark energy</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>. These observations motivate theoretical exploration of non-minimal coupling mechanisms that can realize stable phantom crossing without ghosts, as standard minimally coupled canonical quintessence cannot cross w=-1 without violating theoretical consistency conditions <snippet id="S_ZIWoomJ">there is no obstacle to the phantom regime w < -1, which is unphysical in general relativity</snippet>.
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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 lethal dose to 1% of the population (LD1) and the effective dose to 99% of the population (ED99), or equivalently as LD50/ED50</snippet>. <snippet id="S_NDPofwS">The LD1 represents the dose that elicits lethality in 1% of the population, while the ED99 represents the dose that elicits therapeutic effect in 99% of the population</snippet>. <snippet id="S_KtkXCqd">Some formulations express margin of safety as a function of cube root of ratio between LT50 and LD50 and one-hundredth of ED</snippet>. However, <snippet id="S_RujXXPj,S_4mMdKmh,S_8bzg1KA,S_NDPofwS,S_Tg2CFEg">none of the provided search results discuss conditions under which margin of safety cannot be calculated or when it fails to appear as a meaningful value</snippet>. <snippet id="S_ITpLCrH">The search results confirm that LD50/ED50 is a standard therapeutic index calculation, but do not address scenarios where these dose quantiles are not observable or computable</snippet>.
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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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The search results do not provide explicit experimental evidence of group polarization or risky shift in avatar-mediated immersive VR environments. While some studies discuss avatar visual fidelity and embodiment effects <snippet id="S_X5s1Ifa">abstract avatars, particularly robots, led to a disconnection from reality and increased risky behaviors, whereas self-representations fostered a connection to the physical world, promoting cautious behavior</snippet>, none document systematic attitude extremity changes following group discussion in multi-user VR. Other results focus on social anxiety simulation <snippet id="S_JIjtTEQ">the study utilized a Virtual Research VR1280 head-mounted display and an Intersense IS900 tracking system to create a virtual reality environment simulating a 5-minute underground train journey populated by computer-generated avatars</snippet> or delusional beliefs testing <snippet id="S_XSKnvh7">The simulation lasted four minutes and featured computer-generated avatars created with 3D Studio Max</snippet>, but do not address group polarization constructs. No snippets contain explicit demonstrations of post-discussion extremitization or group influence on attitudes in avatar-mediated immersive environments.

<answer>
The search results do not provide explicit experimental evidence of group polarization or risky shift in avatar-mediated immersive VR environments. While some studies discuss avatar visual fidelity and embodiment effects <snippet id="S_X5s1Ifa">abstract avatars, particularly robots, led to a disconnection from reality and increased risky behaviors, whereas self-representations fostered a connection to the physical world, promoting cautious behavior</snippet>, none document systematic attitude extremity changes following group discussion in multi-user VR. Other results focus on social anxiety simulation <snippet id="S_JIjtTEQ">the study utilized a Virtual Research VR1280 head-mounted display and an Intersense IS900 tracking system to create a virtual reality environment simulating a 5-minute underground train journey populated by computer-generated avatars</snippet> or delusional beliefs testing <snippet id="S_XSKnvh7">The simulation lasted four minutes and featured computer-generated avatars created with 3D Studio Max</snippet>, but do not address group polarization constructs. No snippets contain explicit demonstrations of post-discussion extremitization or group influence on attitudes in avatar-mediated immersive environments.
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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">Nikola Tesla's Electric Arc Lamp patent is US335786A, titled "Electric arc lamp" and describes improvements in Electric-Arc Lamps</snippet>, with <snippet id="S_CBhXwnS,S_L4MYIrf">the patent being issued on February 9, 1886</snippet>. <snippet id="S_ktaELRS">The patent number is also listed as 335,787 in some sources for the Electric arc lamp</snippet>, which was granted to Nikola Tesla of Smiljan Lika, Austria-Hungary. <snippet id="S_yVKm3fu">This date of February 9, 1886 is confirmed in multiple sources as the issue date for the Electric Arc Lamp patent</snippet>, establishing it as Tesla's second U.S. patent after the Commutator for Dynamo-Electric Machines issued on January 26, 1886.
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<answer>
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,S_IhbWqXF">The episode is titled "Rhino Rocket with Tina Munjal, MD" and is part of Season 3, Episode 2 of the "Stories from the World of Medicine" podcast</snippet>, <snippet id="S_cGRsAZI,S_IhbWqXF">with a publication date of February 18, 2020</snippet>. <snippet id="S_cGRsAZI,S_Q1JiXuV">The guest is Otolaryngologist Tina Munjal, MD</snippet>, <snippet id="S_cGRsAZI,S_NZ9gUn7">who is an attending physician at the University of California, San Francisco</snippet>. <snippet id="S_cGRsAZI,S_NZ9gUn7">The episode features Tina Munjal telling a story about learning to be comfortable outside of her comfort zone</snippet>, <snippet id="S_NZ9gUn7">and the runtime is approximately 30 minutes</snippet>. <snippet id="S_cGRsAZI">The official episode page is available at The Nocturnists podcast website</snippet> <snippet id="S_C2IKgBh">with additional distribution through platforms like Libsyn and the Nocturnists website</snippet>.
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<answer>
<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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The search results do not contain explicit "de-extinction" terminology or recent 2022-2025 reviews/perspectives on the topic. <snippet id="S_btUw1xy">One snippet mentions the controversial concept 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_btUw1xy">It also addresses cloning techniques like somatic cell nuclear transfer (SCNT) could enable the de-extinction of recently extinct mammals with preserved tissues</snippet>. However, this appears to be a general genomics conservation page rather than a dedicated de-extinction review. <snippet id="S_aQHGJDJ,S_BVGS7oK,S_yJ0bKZt">Several snippets discuss evolutionary potential (EP) and extinction risk assessments, which are related concepts but do not explicitly use "de-extinction" terminology</snippet>. <snippet id="S_160DJq3,S_kpUOwfs">Other results focus on late-Quaternary megafauna extinctions and trophic rewilding rather than de-extinction technology or governance</snippet>. <snippet id="S_hlWQ6qg,S_ZV4SO7N,S_zN6EiNI,S_pIULMfn">The remaining snippets cover general conservation topics including biodiversity shortfalls, taxonomists' roles, and conservation paleobiology without de-extinction-specific content</snippet>.

<answer>
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>, with <snippet id="S_exyOPhA">the critical neutron chemical potential for the hadron-quark phase transition lying between 1050 MeV and 1400 MeV at zero temperature</snippet>. In general, <snippet id="S_jARyMl0,S_BQ1tanr">the baryon chemical potential in neutron stars is typically in the range of several hundred MeV to a few GeV</snippet>, reflecting the extreme conditions present in such dense astrophysical objects. <snippet id="S_dKTw9kz">The chemical potential values for neutrons in beta equilibrium are influenced by the presence of dark baryons, though specific numerical values are not provided</snippet>. For hyperonic matter, <snippet id="S_WRBepHG">neutron stars reach beta equilibrium involving neutrons, protons, and electrons, with additional baryons such as Λ hyperons emerging when their chemical potential condition (µΛ = µn = µp + µe) is satisfied</snippet>. The exact quantitative range of μ_B as a function of density or radius/mass requires solving the coupled Dirac and field equations self-consistently for a given total baryon density <snippet id="S_WWQcyyq">, as the chemical potentials and number densities of different particles are related by conditions at beta equilibrium</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 large-scale randomized 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 experiment showed messages encouraging users to vote and displaying images of friends who had already voted, which increased turnout by approximately 340,000 votes</snippet>. <snippet id="S_mXK3pZh,S_8SBonkH">Replication studies in 2012 found the effect was smaller (90,000 additional votes) but still significant, with an additional 270,000 votes from friends of treated users</snippet>. <snippet id="S_37bk94m">The study demonstrated that social media messages could significantly influence voting behavior through "social proof" mechanisms exploiting human heuristics</snippet>. <snippet id="S_gGLgZLn">However, the authors acknowledged very small effects from the information treatment, highlighting the need for careful interpretation of statistical significance in large sample sizes</snippet>. <snippet id="S_Z2mbNNa">The 2012 experiment also showed that treatment effects spread through the network, causing an additional 180,000 close friends of the treated to vote</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">This date is also referenced in IGN's 2010 article noting World of Warcraft first launched in North America on November 23, 2004</snippet>. <snippet id="S_Iyt7Mpt">Additional IGN coverage from December 2004 references the game's November 23 release date</snippet>. <snippet id="S_3ft58Qe">Wikipedia corroborates this, stating the game was released on November 23, 2004 for the 10th anniversary of the Warcraft franchise</snippet>. <snippet id="S_mhE8bKy">GamesIndustry.biz independently confirms the street date as November 23, 2004, launching simultaneously in North America, Australia, and New Zealand</snippet>. <snippet id="S_K0CkkAv">Wowpedia also documents the release date as November 23, 2004</snippet>.
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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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Cytokinin (CK), strigolactone (SL), and auxin form a regulatory network where CK promotes axillary bud outgrowth while SL and auxin act as inhibitors <snippet id="S_q2ORi2Q">CK promotes axillary bud outgrowth, while SL inhibits it, with both hormones acting antagonistically through the transcription factor TEOSINTE BRANCHED 1 (BRC1)</snippet>. Auxin inhibits CK biosynthesis while promoting SL biosynthesis, contributing to bud dormancy <snippet id="S_XRhJBhI">Auxin inhibits CK biosynthesis while promoting SL biosynthesis, contributing to bud dormancy</snippet>. In this hormonal interplay, auxin-mediated inhibition of bud outgrowth is linked to increased SL synthesis, which upregulates BRC1 expression <snippet id="S_gqi212y">Auxin can indirectly promote BRC1 expression in the bud through the control of two antagonistic factors, CK and SL</snippet>. BRC1 functions as a key integrator of pathways that suppress bud outgrowth, including those mediated by SL, auxin, and cytokinin <snippet id="S_Uuo070s">BRANCHED1 (BRC1) is identified as a key integrator of pathways that suppress bud outgrowth, including those mediated by SL, auxin, cytokinin, and sugar</snippet>. CKs are known to repress BRC1 expression, although the underlying molecular mechanisms remain unclear <snippet id="S_gLbtlMj">CKs are known to repress BRC1 expression, although the underlying molecular mechanisms remain unclear</snippet>. This regulatory mechanism is conserved across plant species, with SL mutants displaying increased branching and CK excess leading to enhanced axillary bud outgrowth in Arabidopsis <snippet id="S_nFj5ih3">SLs inhibit bud outgrowth by upregulating BRANCHED1 (BRC1), a gene that encodes a repressor of bud outgrowth</snippet> and <snippet id="S_gLbtlMj">mutants lacking functional BRC1 exhibit altered branching compared to wild-type plants</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 for its AI Copilot services: Free, Pro, and Enterprise Pro, with the Pro version costing $20/month or $200 annually</snippet>. <snippet id="S_Y8Mojus">The Pro tier includes additional features like multi-step reasoning searches and deep research queries, limited to three per day</snippet>, while <snippet id="S_5WLXO2p">the Enterprise Pro tier is priced at $40/month per seat or $400/year (16% discount) and provides unlimited queries with 500 daily deep research capabilities</snippet>. <snippet id="S_Gk4sG8w,S_5WLXO2p">The Pro subscription includes access to advanced AI models like GPT-4o, Claude 3.5 Sonnet, and DeepSeek R1, along with file analysis for PDFs and images and real-time web access for research</snippet>. <snippet id="S_yvm9XpN">Users find the Pro subscription beneficial for research and casual searches, though some report limitations in programming support and long-form content generation</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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