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<snippet id="S_NIP4aKy,S_M9NC8Eo,S_L5NhumS">The search did not return specific peer-reviewed research by Merga in Journal of Adolescent & Adult Literacy on adolescent recreational reading best practices, though multiple sources confirm that dedicated reading time, teacher support, and student choice are crucial for fostering reading cultures in secondary schools</snippet>. <snippet id="S_WIheApX,S_xbJmN70">Merga (2019a) reviews the literacy supportive role of school librarians in the UK, noting that qualified librarians in well-resourced schools are associated with benefits for students' literacy attainment</snippet>. <snippet id="S_xbJmN70">Merga and Mat Roni (2018) establish that pleasure in reading is a strong predictor of reading frequency, which leads to growth in literacy skills</snippet>. <snippet id="S_L5NhumS">Effective classroom practices should create supportive contexts that foster engagement through promoting choice, collaboration, and competence, with teachers' behaviors playing a significant role in influencing students' motivation</snippet>. <snippet id="S_NIP4aKy">Schools should provide dedicated time for reading and implement initiatives like summer reading programs, as teacher support and strong relationships with educators are crucial for fostering a reading culture</snippet>. While the specific Merga review from the target journal was not found in these results, the collective evidence confirms that choice reading, teacher modeling, and creating inviting reading environments are research-backed strategies for increasing adolescent recreational reading in secondary settings.
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<snippet id="S_WIheApX,S_HOSScoU">School librarians are identified as key figures in fostering reading engagement and literacy attainment in secondary education, a finding supported by research citing Merga (2019a, 2019b)</snippet>, and <snippet id="S_xbJmN70">pleasure in reading is a strong predictor of reading frequency which leads to growth in literacy skills</snippet>. <snippet id="S_NIP4aKy">Schools should provide dedicated time for reading and implement initiatives like summer reading programs</snippet>. <snippet id="S_NIP4aKy">Unlike primary schools, high schools often do not actively encourage book reading</snippet>. <snippet id="S_L5NhumS">Effective practices involve creating supportive contexts that foster collaboration, competence, and positive teacher behaviors, and reading interventions integrating motivational principles alongside cognitive skills show positive effects</snippet>.


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<snippet id="S_0NbePdE,S_RLXmKuG">The EU AI Act mandates that high-risk AI systems must provide sufficient transparency mechanisms and be "sufficiently transparent to enable users to interpret outputs," as outlined in Article 13</snippet>. <snippet id="S_TVBhkcK,S_WG0otDu">Article 14(3) requires human overseers to have the authority to decide against using the AI system, override its outputs, and intervene in its operation, including the ability to halt it safely</snippet>. <snippet id="S_UuXjGBn">Article 11(2) allows for a unified technical documentation file that combines AI system details with existing EU MDR/IVDR documentation, including comprehensive information on design, architecture, data requirements, training methodologies, and performance metrics</snippet>. <snippet id="S_3iocoPc">Article 4(2)(b) details that if an AI system is considered high-risk, opaque, and complex, explainability is mandated from an EU court through orders to disclose proportional evidence such as logs, documentation, and datasets</snippet>. <snippet id="S_E4eihUQ,S_xQp268d">General-purpose AI (GPAI) systems are subject to high-risk obligations if they can be used in high-risk contexts, with Article 53 requiring technical documentation and transparency in the value chain</snippet>. <snippet id="S_vzKoGDA">The Act contains disclosure obligations under Article 11 and Annex IV that apply primarily to high-risk systems, though some provisions like Article 50 impose transparency duties on deployers requiring outputs to be "watermarked" and users to be informed when interacting with chatbots</snippet>.
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The EU AI Act mandates high-risk AI systems to provide sufficient transparency mechanisms under Article 13, including user instructions detailing characteristics, capabilities, and limitations to ensure adequate user information <snippet id="S_0NbePdE, S_RLXmKuG">. To enable effective human oversight, Article 14 requires providers to implement measures allowing overseers to correctly interpret outputs, detect anomalies, and override decisions <snippet id="S_WG0otDu">. Oversight personnel must understand system capabilities and limitations to identify automation bias and intervene safely, ensuring outputs are not blindly followed <snippet id="S_TVBhkcK">. Comprehensive technical documentation under Article 11(2) and Annex IV supports these goals by recording design, data, and performance metrics for authorities and users <snippet id="S_UuXjGBn">. Specific transparency duties apply to deepfakes requiring AI-generated disclosure, while GPAI providers face duties for technical documentation summaries, with specific exemptions for open-source models <snippet id="S_JvLynMd, S_XQp268d">.
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<snippet id="S_tyjIFLb,S_soikqKO">Strava serves as a social network for amateur and professional athletes, enabling users to log, monitor, and share fitness accomplishments with others via status updates, comments, photos, and leaderboards</snippet>. <snippet id="S_tyjIFLb,S_KfOy5t1">Core gamification techniques include challenges where users compete to complete specific distances, receiving digital badges, trophies, and prizes for completion</snippet>. <snippet id="S_ohmbRBN,S_tyjIFLb">The app fosters competitive behaviors and motivation through tracking routes, providing performance feedback, and creating a culture of self-monitoring and enhancement</snippet>. <snippet id="S_soikqKO">Users can compare their performance to friends or local users, with premium subscriptions offering demographic-specific leaderboards</snippet>. <snippet id="S_fdz63NK">Cyclists often selectively share data, withholding metrics like heart rate and wattage while opting for basic information such as segment times and elevation</snippet>. <snippet id="S_fdz63NK,S_5nbN41y">This behavior reflects a desire for self-validation and awareness of how others perceive their data, with users modifying their behavior due to potential scrutiny of their profiles</snippet>. <snippet id="S_5nbN41y">However, the app's social features have limitations, including reliance on cross-sectional samples and lack of longitudinal data on user engagement</snippet>.
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Strava employs social features such as challenges, leaderboards, and digital badges as core gamification techniques to encourage repeated use and foster a sense of community among its 36 million active users <snippet id="S_tyjIFLb">. The competitive nature of these persuasive technologies significantly influences user motivation by facilitating social comparison, though individual preferences for comparison direction vary <snippet id="S_ohmbRBN, S_KfOy5t1">. To manage privacy and self-presentation, users often selectively share data, withholding specific metrics like heart rate to avoid potential profile scrutiny <snippet id="S_fdz63NK">. Features like user-defined segments allow for performance comparisons while enabling users to control data visibility and foster localized community connections <snippet id="S_soikqKO">. Incorporating competitive and cooperative social features is recommended to increase user engagement and intrinsic motivation in fitness applications <snippet id="S_47DnIT5">. However, current implementations largely overlook nuanced psychological theories regarding social comparison, which could otherwise enhance engagement further <snippet id="S_KfOy5t1">.
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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>, with energy resources from Canada subject to a lower 10% tariff rate. <snippet id="S_ixOFgje">These tariff rates are part of President Trump's action to address illegal immigration and fentanyl-related national emergency threats</snippet>, as declared under the International Emergency Economic Powers Act (IEEEPA). <snippet id="S_ixOFgje">The fact sheet references trade statistics showing Canada, Mexico, and China contribute significantly to U.S. trade deficits, with 2023 U.S. trade deficit in goods exceeding $1 trillion</snippet>. <snippet id="S_ixOFgje">The document cites that fentanyl seizures at U.S. borders reached over 21,000 pounds in the last fiscal year, enough to kill more than 4 billion people</snippet>. However, the snippet does not provide specific effective dates for these tariff implementations, EU-specific tariff rates, or quantified economic impact estimates such as consumer cost increases or GDP projections. <snippet id="S_ixOFgje">The fact sheet emphasizes that these measures leverage America's economic position to secure borders against illegal migration and combat drug trafficking</snippet>.
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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">Scholarly analysis of Orwell's Nineteen Eighty-Four slogans ("War is Peace," "Freedom is Slavery," "Ignorance is Strength") emphasizes their role in discursive control and metaphorical interpretation</snippet>, noting that a significant portion of references are secondary uses rather than original</snippet>. <snippet id="S_7QgSGSe">The concept of 'discursive drift' is applied to track how these slogans evolve in meaning and stance over time within public discourse</snippet>, reflecting shifting societal attitudes</snippet>. <snippet id="S_lgOMCo4">The doubleplus unfree formation is cited as evidence of the intensifying use of language in Orwell's Newspeak, exemplifying lexicographical control</snippet>. <snippet id="S_iDUQY7x">Slogans are defined as brief, striking phrases that may include labeling and stereotyping, acting as emotional appeals</snippet>, while <snippet id="S_15dkzZt">they are also characterized as persuasive tools that can act as thought-terminating clichés to discourage critical thought</snippet>. <snippet id="S_tpXkvyW">Metaphoric slogans are analyzed for their function in projecting covert ideology through shared experiences between speakers and audiences</snippet>. However, <snippet id="S_7QgSGSe">the available snippets do not provide comprehensive CDA frameworks (Fairclough/van Dijk/Foucault) explicitly applied to Orwell's discourse power and ideology</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>, which indicates he held the concurrent title of President-Elect during the 2024 term. <snippet id="S_ZPx3NY5">Past MRS Presidents page also shows Takao Someya (2024) in the vice president/president-elect context</snippet>, though Eric Stach's appointment is confirmed for the 2024 Vice President position with the 2025 presidential transition.

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<answer>
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,S_Xa6M06B">OASIS 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) rather than XML</snippet>. <snippet id="S_JYIyMdS,S_3JECVB5">The STIX 2.1 format defines 12 STIX Domain Objects (SDOs), including 'indicator', 'malware', 'report', and 'vulnerability', each with specific attributes</snippet>, while <snippet id="S_JYIyMdS">STIX Relationship Objects (SROs) enable the linking of multiple SDOs to facilitate complex representations of CTI</snippet>. <snippet id="S_lIvobvB">For malware-specific indicators, the CSI value fills the pattern property of the Indicator SDO</snippet>, which is crucial for detailing malware indicators within the CTI framework. <snippet id="S_3M0PARM">Real-world CTI datasets capture malware variants and threat actor relationships, with STIX bundles containing entities like Malware (75% of bundles) and Threat Actor (54% of bundles)</snippet>. <snippet id="S_3TK690R">STIX uses UUIDs to establish connections between observed data structures and indicator patterns through relationship 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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<snippet id=3d29ab62-0>Kohgiluyeh and Boyer-Ahmad province is one of the 31 provinces of Iran located in the southwest of the country</snippet>. <snippet id=3d29ab62-1>Kohgiluyeh County is in Kohgiluyeh and Boyer-Ahmad province, with its capital being the city of Dehdasht</snippet>. <snippet id=3d29ab62-2>The province is firmly situated in the Zagros Mountains, stretching from the heights of Denā Peak in the west to lower, warmer ranges in the east</snippet>. <snippet id=3d29ab62-5>Recent studies from 2024 reference newly formed local and province level governments in the region</snippet>. However, <snippet id=3d29ab62-3,3d29ab62-4,3d29ab62-6,3d29ab62-7,3d29ab62-9>the available search results do not provide specific information about newly formed counties being created in Kohgiluyeh and Boyer-Ahmad Province between 2020-2024</snippet>. <snippet id=3d29ab62-8>The UNHCR search results list various locations including some in the province but do not confirm new county formations</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" project, the award is titled "CROWN" which won the National Science and Technology Progress Second Prize</snippet>. <snippet id="S_UoGmAYk">For the "Virtual Reality & Digital Media" project, the award includes both First and Second Prize levels, with tools that have been incorporated into models</snippet>. <snippet id="S_ywdgTkl,S_UoGmAYk">The Virtual Reality & Digital Media project specifically involved developing real-time 3D graphics platform BH-GRAPH and distributed interactive simulation support platform BH_RTI</snippet>. <snippet id="S_ywdgTkl">The Trusted Computing Environment & Platform project established CROWN providing high-trust software development environment, Web service middleware platform, and network environment operation platform</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 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_sAPmmcf">Those who reported past-30-day sports betting were more likely to have a history of indebtedness (11 vs. 6%, p = 0.04), and had higher levels of gambling problems</snippet>. However, <snippet id="S_d3zPQEk">specific data on university students in Nigeria is not detailed in the esports betting study, which instead uses data from Great Britain</snippet>. <snippet id="S_rqYsRo2">A study involving 5,000 college students from 12 universities in Ghana explored the role of financial literacy in predicting financial behavior, which may relate to the prevalence of sports betting among university students in Nigeria</snippet>.
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<answer>
<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 at lmarena.ai, which has collected over 3.5M votes</snippet>. <snippet id="S_6IdzsAE">Previous leaderboard updates have been published by LMSYS, including an Elo rating system based on anonymous voting data</snippet>. However, <snippet id="S_hhzNfal">the available search results do not contain the specific current top model name, Elo rating, or timestamp/update note from the live leaderboard page</snippet>. The search results show historical data and links to past leaderboard announcements rather than the current ranking snapshot. To obtain the definitive top model information, direct access to the live leaderboard at lmarena.ai is required.
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<answer>
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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<answer>
<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>. <snippet id="S_ZIWoomJ">This conclusion arises when the dark energy equation of state in a late-time, spatially flat Friedmann-Lemaître-Robertson-Walker model is parametrised as w(a) = w 0 + w a (1 − a), allowing for dynamical (evolving) dark energy at the cost of only 2 parameters</snippet>. It is important to note that <snippet id="S_ZIWoomJ">there are various issues associated with using this parametrisation as it is a phenomenological ansatz that is not based on a physical and selfconsistent model of dark energy</snippet>, and <snippet id="S_ZIWoomJ">the phantom regime w < -1 is unphysical in general relativity</snippet>.
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<answer>
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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<answer>
<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 LD1/ED99</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_ITpLCrH,S_PNN5Uwr">This is sometimes also expressed as LD50/ED50 (lethal dose in 50% of patients compared to effective dose in 50% of patients)</snippet>. <snippet id="S_RujXXPj">The margin of safety ratio indicates the safety of a drug at high doses, with a higher margin meaning lower risk of toxicity</snippet>. However, <snippet id="S_KtkXCqd">none of the provided snippets discuss conditions under which this margin of safety cannot be calculated or is considered undefined</snippet>.
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<answer>
<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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<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 its effects on behavior, they do not specifically measure group discussion outcomes or attitude extremity <snippet id="S_X5s1Ifa">avatar visual fidelity did not significantly affect self-location or agency</snippet>, with findings noting that abstract avatars led to increased risky behaviors compared to self-representations <snippet id="S_HKqSHCf">abstract representations allow the users to adopt more risky behaviors, while self-representations maintain a connection with the real world and encourage users to preserve the integrity of their avatar</snippet>. One study used avatars in a virtual reality context to explore social anxiety and persecutory ideation, but did not detail findings related to risky shift <snippet id="S_JIjtTEQ">the aim was to explore the differential prediction of social anxiety and persecutory ideation in an experimental context, although specific findings related to "risky shift" in virtual reality avatars were not detailed in the provided text</snippet>. Another study simulated a London Underground train journey with computer-generated avatars but also did not report results on group polarization <snippet id="S_XSKnvh7">The setup aimed to investigate aspects of delusional beliefs within a controlled virtual environment</snippet>. Overall, the current search results lack the specific multi-user IVE evidence demonstrating post-discussion attitude extremity increases in avatar-mediated social VR settings.
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<answer>
<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 filed from Smiljan Lika, Austria-Hungary</snippet>, with <snippet id="S_CBhXwnS,S_L4MYIrf">an issue date of February 9, 1886</snippet>. <snippet id="S_ktaELRS">The patent number is 335,787 for the "Electric arc lamp" with automatic fail switch and reactivation features</snippet>, also issued on <snippet id="S_s2HVIjN,S_hppOrTi">February 9, 1886</snippet>. This confirms the Electric Arc Lamp patent came after the Commutator for Dynamo-Electric Machines which was issued on January 26, 1886, establishing the commutator as Tesla's first patented invention by issue date.
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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,S_IhbWqXF">The episode is titled "Rhino Rocket with Tina Munjal, MD" and is part of Stories from the World of Medicine, Season 3, Episode 2</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_NZ9gUn7">who tells a story about learning to be comfortable outside of her comfort zone</snippet>. <snippet id="S_cGRsAZI">The episode is available on The Nocturnists Podcast website at thenocturnists.org/podcast/rhino-rocket</snippet>, <snippet id="S_IhbWqXF">and is also listed on the official Stories From The World Of Medicine page</snippet>. <snippet id="S_NZ9gUn7">The episode runtime is approximately 30 minutes</snippet>, <snippet id="S_C2IKgBh">and the episode is sponsored by The Nocturnists</snippet>.
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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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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">Another snippet notes that cloning techniques like somatic cell nuclear transfer (SCNT) could enable the de-extinction of recently extinct mammals with preserved tissues</snippet>. However, these appear to be isolated mentions rather than dedicated de-extinction reviews. <snippet id="S_aQHGJDJ,S_BVGS7oK,S_yJ0bKZt">Multiple snippets discuss evolutionary potential (EP) and extinction risk assessments, including proxies for EP that can be estimated from environmental, phenotypic, and genetic data</snippet>. <snippet id="S_160DJq3,S_kpUOwfs">A review on late-Quaternary megafauna extinctions notes growing interest in megafauna's role in ecosystem conservation and restoration, particularly through trophic rewilding</snippet>. <snippet id="S_hlWQ6qg">One article discusses the ongoing crisis of biodiversity loss and advocates for "salvage sampling" to document species before they disappear</snippet>. None of the provided snippets contain the specific "de-extinction" terminology or 2022-2025 dated review perspectives the agent is seeking.

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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>, 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 beta-equilibrated hadronic matter, <snippet id="S_WRBepHG">the chemical potentials satisfy the relationship µp = µn - µe</snippet>, where neutrons, protons, and electrons are in equilibrium. <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 in dense astrophysical objects. <snippet id="S_dKTw9kz">The baryon chemical potential is derived from µ_B = (P_nuc + ρ_nuc)/n_B</snippet>, where it is expected to be in the GeV range but specific numerical values are not always provided. <snippet id="S_in5xo5t">The density dependence of neutron and proton chemical potentials shows small differences between models at high densities</snippet>, indicating the complexity of determining μ_B as a function of density.
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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">The Bond et al. (2012) experiment involved 61 million Facebook users during the 2010 U.S. Congressional Election who received get-out-the-vote messages</snippet>, with <snippet id="S_e9zzIKc">results showing the social message increased turnout by close to 340,000 votes</snippet>. <snippet id="S_37bk94m,S_GveNEie">The study demonstrated social proof by displaying images of friends who had voted, encouraging users to imitate their behavior</snippet>. <snippet id="S_mXK3pZh,S_8SBonkH">Replication data from the 2012 U.S. Presidential Election showed direct effects of about 90,000 additional votes and indirect effects through friends of approximately 270,000 votes</snippet>. <snippet id="S_I0UxhZS">People who knew their Facebook friends voted were more likely to vote themselves, showing influence through social ties</snippet>. <snippet id="S_gGLgZLn">The paper emphasized the success of influencing voter behavior through Facebook, though the authors acknowledged very small effects from the information treatment</snippet>. <snippet id="S_8SBonkH">These results replicate earlier work and add to growing evidence that online social networks can be instrumental for spreading offline behaviors</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>, providing the fourth independent confirmation needed. <snippet id="S_4am1dTv">Another IGN article states World of Warcraft first launched in North America on November 23, 2004</snippet>, with several expansion add-ons released since. <snippet id="S_mhE8bKy">GamesIndustry.biz corroborates this with a press announcement for the street date of November 23, 2004</snippet>. <snippet id="S_3ft58Qe">Wikipedia notes the game was released for the 10th anniversary of the Warcraft franchise on November 23, 2004</snippet>. <snippet id="S_Iyt7Mpt">Blizzard reported record sales on November 23, 2004, with the game selling more in its first 24 hours than any other PC title</snippet>. The release date is now confirmed across multiple authoritative sources.
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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 <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>In Arabidopsis, 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 <snippet id=S_nFj5ih3>Various SL mutants in plants like pea, petunia, and Arabidopsis display increased branching, indicating the role of SL in regulating shoot architecture</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</snippet>, with the <snippet id="S_Y8Mojus,S_Gk4sG8w,S_5WLXO2p">Pro version costing $20/month or $200 annually</snippet> and including enhanced functionalities like <snippet id="S_Gk4sG8w">access to advanced AI models (e.g., GPT-4o, Claude 3.5 Sonnet)</snippet>, 300 daily Pro searches, and file analysis for PDFs and images. <snippet id="S_Y8Mojus">The Enterprise Pro tier is priced at $40/month per seat or $400/year</snippet> and provides unlimited queries, extensive deep research capabilities (500 per day), and enhanced collaboration features. <snippet id="S_yvm9XpN">Users find the Pro subscription valuable for research and casual searches</snippet>, though some report <snippet id="S_yvm9XpN">restricted programming support and challenges with long-form content generation</snippet> compared to competitors.
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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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