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SML

Standard ML (SML) is a general-purpose, modular language featuring compile-time type checking, polymorphic , and garbage collection, designed to promote safe and expressive . Originating as the Meta Language (ML) in the 1970s at the for use in the LCF automated theorem prover, it evolved to address inconsistencies across early implementations and was formally standardized in 1990, with a revised definition published in 1997. SML's core strengths lie in its strict evaluation semantics, support for higher-order functions with lexical scoping, for concise data handling, and a sophisticated system comprising structures, signatures, and parametric functors that enable and large-scale composition. These elements facilitate immutable data structures by default alongside limited imperative features like mutable references and arrays, balancing purity with practicality for tasks such as symbolic computation and compiler construction. Its , proven formally sound, prevents common errors like dereferences or type mismatches at runtime, enhancing reliability in verification-heavy domains. Notable implementations include (SML/NJ), which provides an interactive environment and , and MLton, focused on whole-program optimization for high performance. SML's innovations in type polymorphism, modules, and have profoundly shaped subsequent languages and paradigms, underscoring its enduring role in advancing theory and practice.

Computing and technology

Standard ML

Standard ML (SML) is a general-purpose, statically typed language that supports through parametric modules, , and a combination of functional and imperative features. It features strong type checking at , automatic polymorphic , and garbage collection, making it suitable for developing reliable software in research, teaching, and industry applications. The language's design prioritizes mathematical rigor, with a formal definition providing for both static type checking and dynamic evaluation. SML originated from the Meta Language (ML), developed in 1973 by Robin Milner and his group at the University of Edinburgh as a proof-checking component for the LCF theorem-proving system. Early implementations, such as Edinburgh ML and Luca Cardelli's "ML under VMS" compiler released in June 1981, highlighted dialect variations, prompting standardization efforts starting with the first design meeting in April 1983, organized by Milner. Subsequent meetings in 1984 and 1985 refined the core language and module system, with David MacQueen's contributions on modules finalized in October 1985. The initial formal Definition of Standard ML was published in 1990 by MIT Press, authored by Milner, Robert Harper, and Mads Tofte, following iterative technical reports from 1986 onward. A revised definition appeared in 1997, addressing limitations in the type system (e.g., introducing the value restriction for polymorphism) and module matching, with input from MacQueen. The Standard ML Basis Library, specifying a portable standard library, was formalized in 2004 by Emden Gansner and John Reppy. Core features of SML include:
  • Type system: Hindley-Milner polymorphism with , enabling types like 'a -> 'a for functions without explicit annotations; algebraic datatypes for recursive structures, such as datatype 'a [tree](/page/Tree) = Leaf of 'a | Node of 'a [tree](/page/Tree) * 'a [tree](/page/Tree).
  • Expressions and control: Higher-order functions, via case expressions, and imperative constructs like references (ref) and sequencing (;), balanced by in pure functional subsets.
  • Module system: Structures for code organization, signatures for interfaces, and s for generic modules, e.g., a applying a operation to containers; supports sharing and opaque/as signatures for abstraction.
Programs consist of declarations binding values, types, exceptions, and modules in a top-level environment, evaluated strictly left-to-right. Syntax emphasizes conciseness, with curried functions by default (e.g., fun add x y = x + y has type int -> int -> int) and list comprehensions via library functions. Major implementations include Standard ML of New Jersey (SML/NJ), an interactive compiler with native code generation and extensions like the visible compiler for metaprogramming, started in the late 1980s at Bell Labs; MLton, a whole-program optimizing compiler producing efficient native binaries; Poly/ML, supporting multicore parallelism and POSIX threads; and others like Moscow ML and MLKit for bytecode or research use. These conform to the 1997 revision and Basis Library, ensuring portability. SML has influenced functional language design, notably in the module systems of and F# derivatives, and in languages like ; its formal semantics advanced denotational and operational models in . Despite limited commercial adoption, it remains active in academia for theorem proving, compilers, and verification tools.

Service Modeling Language

The Service Modeling Language (SML) is an XML-based specification designed to model complex IT services and systems by defining their structure, constraints, policies, and best practices. It enables the creation of interrelated XML documents that represent IT resources such as hardware, software, applications, and services, facilitating validation and management across multi-vendor environments. SML models consist of definition documents (schemas and rules) and instance documents, allowing for reusable building blocks to describe service hierarchies and dependencies. Development of SML began with a public review initiated on July 31, 2006, by a consortium of technology companies including , , Cisco Systems, , , , , , and . The effort aimed to standardize IT resource modeling to reduce management complexity and costs, addressing inconsistencies in proprietary formats used for configuration, , and deployment. Version 1.0 was submitted to the W3C in March 2007, with Version 1.1 advancing through candidate and proposed recommendation stages before becoming a W3C Recommendation on May 12, 2009. The specification was produced by the W3C Service Modeling Language , which has since closed. SML builds on 1.0 for structural definitions and Schematron for rule-based constraints, extending with mechanisms for cross-document references using URIs and the smlfn:deref() function. Core constructs include reference attributes like sml:ref and sml:uri for linking elements, constraint annotations such as sml:acyclic to prevent cycles and sml:targetRequired to enforce presence, and identity constraints via sml:key, sml:unique, and sml:keyref elements supporting selectors. These features allow models to enforce policies and relationships, such as ensuring compatibility in service compositions, while supporting localization of natural language content through standardized schemes. Validation in SML involves checking instance documents against definition models, confirming reference resolution, , and schema compliance, often using tools that process the entire model graph. The Service Modeling Language Interchange Format (SML-IF), also a W3C Recommendation from May 12, 2009, provides a serialized XML format for exchanging complete SML models, including definitions, instances, and , to enable between tools and systems. Following its recommendation, SML saw calls for implementations from W3C in November 2008, but documented adoption remains limited, with references primarily in academic and vendor explorations of model-based IT rather than widespread commercial deployment. The specification has been positioned as a potential successor to earlier IT modeling approaches, yet no major updates or active standards maintenance have occurred since the working group's closure.

Structured Modeling Language

The Structured Modeling Language (SML) is an executable modeling language designed to support the semantic framework of Structured Modeling (SM), a formal approach to representing complex models in management science, operations research, and related fields. SM treats models as hierarchical collections of distinct elements—including primitive entities (basic objects without definitions), compound entities (aggregations of other elements), attributes (properties with defined values), functions (computable expressions), and tests (boolean conditions)—organized into modular genera and structured as directed acyclic graphs of definitional dependencies. SML enables the precise specification of these elements, their attributes, and interrelationships, facilitating model instantiation, computation, and analysis while distinguishing between the objective model structure and subjective user tasks such as optimization or querying. Developed by Arthur M. Geoffrion at the , SML emerged in the late as part of efforts to overcome limitations in existing algebraic modeling languages, which often lacked robust support for , genericity, and semantic transparency. Geoffrion formalized SM's theoretical foundations in 1989, with SML detailed in subsequent works around 1992, building on an initial SM introduction from 1987. The language features four escalating levels of expressive power: basic definitional systems at Level 1, up to sparse relational models with complex index sets and generic calling sequences at Level 4, allowing representation of diverse paradigms from to . Early prototypes, such as FW/SM implemented by 1990, demonstrated SML's viability for practical model building. SML's strengths lie in its alignment with SM's modular —where are grouped into semantically related genera forming a rooted —and its capacity for rules that apply across model instances, enhancing reusability and . For instance, it supports elemental detail tables for specifying instance data and for generic structures, as seen in examples like feedmix optimization models. However, critiques note complexities in mechanisms, prompting refinements like the index-free SFL variant in for improved readability and database storage. Applications have spanned industries including consumer appliances, , and , where SML-aided models improved decision support productivity. Future enhancements proposed include typing, units of measure, and graphical extensions to boost and integration with object-oriented or paradigms.

Geography and places

Smith Mountain Lake

is a man-made located in south-central , primarily within , , and Pittsylvania counties, approximately 30 miles west of Lynchburg. Formed by the damming of the Roanoke River at Smith Mountain Gap, it serves as the upper in a pumped-storage hydroelectric system operated by Appalachian Power Company, a subsidiary of . The lake covers a surface area of 20,600 acres and extends about 40 miles in length, with a shoreline exceeding 500 miles. Construction of the Smith Mountain Dam, a arch structure 816 feet long and 235 feet high above the streambed, began in 1960 and concluded in November 1962, with reservoir filling commencing on September 24, 1963. The lake attained its full pond elevation of 795 feet above sea level on March 7, 1966, after displacing over 750 families and submerging more than 33,000 acres of former farmland and forest. The project, costing approximately $68 million at the time, integrates with the downstream Leesville Dam and Reservoir to facilitate and storage, producing up to 730 megawatts during by pumping water between the two reservoirs. Physically, the lake has an average depth of 55 feet and a maximum depth of 250 feet, with a total water volume of about 2.3 million acre-feet. Water levels are regulated between 793 and 795 feet for , supporting while maintaining ecological stability. The surrounding terrain features rolling hills and mixed hardwood forests, contributing to a diverse that influences and loads. Recreationally, Smith Mountain Lake supports boating, fishing, swimming, and watersports, bolstered by public access points including Smith Mountain Lake State Park, which offers , trails, and a . It hosts a robust managed by the Department of Wildlife Resources, featuring species such as , , , and , with annual stockings to sustain populations. Economically, the lake drives , residential development, and related industries, generating significant local revenue through marinas, resorts, and , while the hydroelectric operations provide reliable baseload power to the regional grid.

Stella Maris Airport

Stella Maris Airport (IATA: SML, ICAO: MYLS) is a small civil situated near the community of on in , serving primarily and regional charter flights. Located at coordinates approximately 23°34′59″N 075°16′08″W and an elevation of 10 feet (3 meters) above , the facility supports tourism to the area's resorts and supports private pilot operations. The was constructed in by Jack Henry Cordery, who was hired by the Estate after emigrating from to oversee the project as part of early resort development on . The runway has since been extended and paved, reaching a length of 3,999 feet (1,219 meters), enabling operations for small aircraft. It remains open to the public with no reported landing fees for , though foreign civil government aircraft may incur diplomatic clearances. Operations focus on scheduled and charter services connecting to , on , and other Bahamian s, with carriers like Makers Air providing twice-weekly flights and Stella Maris Resort Air Service handling regional routes. The handles low-volume traffic, emphasizing efficient for private and small commercial arrivals, and lacks major commercial airline service due to its remote location and limited infrastructure. Weather and navigation aids include standard provisions, with no approaches reported.

Organizations and businesses

SML Group

SML Group Limited is a multinational corporation headquartered in Kowloon, Hong Kong, specializing in end-to-end radio-frequency identification (RFID) and brand identification solutions. The company develops, manufactures, and sells products including labels, hangtags, packaging trims, and RFID tags, primarily serving the apparel, retail, and logistics sectors. Founded in 1985 as a supplier of woven labels for the apparel industry, SML Group expanded operations into southern shortly thereafter and gradually shifted toward advanced technologies like item-level RFID solutions. By the early , it had acquired software suites such as Clarity (originally Xterprise) in 2013, enhancing its RFID encoding and management capabilities, which were rebranded as ClarityRFID in 2025. The company's evolution reflects a from traditional labeling to integrated digital solutions, with RFID adoption driven by demands for accuracy and anti-counterfeiting. SML Group maintains production facilities and offices in over 20 countries across Asia, Europe, and the Americas, enabling localized services, reduced lead times, and 24/7 support for clients. It reported revenue of approximately $330 million in recent filings and employs thousands globally, with a focus on scalable RFID implementations for brands seeking supply chain visibility. Sustainability initiatives include Operation Green for waste reduction, EcoInspire™ materials derived from recycled sources, and a commitment to net-zero emissions by 2050, supported by certifications in responsible sourcing. In September 2025, SML Group attracted interest from firms in a potential $600 million transaction, underscoring its position in the growing RFID market amid digital transformation. The company continues to invest in precision-engineered tags and software for applications like tracking, though its reliance on apparel clients exposes it to sector .

Student Math League

The Student Mathematics League (SML) is a national competition organized by the American Mathematical Association of Two-Year Colleges (AMATYC) for students enrolled in two-year colleges across the . The competition aims to assess participants' problem-solving abilities through challenging problems and to foster excellence in at the community college level. Founded in 1970 by in , the SML was formally adopted by AMATYC in 1981, expanding its scope to a nationwide event. The SML consists of two annual rounds: Round 1 in the fall semester and Round 2 in the spring semester. Each round features a one-hour, proctored exam comprising 20 multiple-choice questions, typically with at least four response options per question, covering precalculus-level topics with an emphasis on nonstandard, creative problem-solving rather than rote computation. Exams are administered on college campuses during a specified window, such as October 25 to November 8, 2025, for Round 1 of the 2025-2026 season and February 28 to March 14, 2026, for Round 2. Institutions must register their teams in advance via AMATYC and pay a fee to participate, with no limit on the number of students who may take the exam per school. Competition occurs at both individual and team levels. Individual scores are calculated based on correct answers, with no partial credit awarded; a score of around 50% is considered strong given the exam's difficulty. Team scores are determined by summing the top five individual scores from each participating institution for that round, allowing different students to contribute to team performance across rounds. Participating colleges are grouped into eight regions for preliminary recognition, though national rankings determine overall standings. Prizes, including recognition for top individual performers and the Glen Smith Memorial Team Championship for the highest-scoring teams, are awarded based on national results published by AMATYC. Past champions and scoreboards are maintained on the AMATYC website, with preparation resources such as archived questions available to faculty for practice sessions. The competition promotes engagement in without requiring advanced calculus knowledge, making it accessible yet rigorous for students.

Entertainment and media

SuperMarioLogan

SuperMarioLogan (SML) is a produced for , created and primarily performed by Logan Thirtyacre, featuring live-action skits with custom puppets depicting anthropomorphic characters in absurd, often crude scenarios. The series originated on December 8, 2007, with early episodes utilizing plush toys of franchise characters like , initially produced in collaboration with Thirtyacre's brother, Lance Thirtyacre. By 2015, the content shifted toward custom puppets and more mature humor, including the introduction of the character —a dim-witted, helmet-wearing child figure that became central to the series and drove significant viewership growth, with the main channel accumulating over 9 million subscribers at its peak. The series' reliance on Nintendo intellectual property led to legal challenges, including a lawsuit filed by against Thirtyacre for unauthorized use of characters, prompting a rebranding in 2023 to original figures such as Marvin (replacing ) and avoiding direct references to protected names. This transition followed cease-and-desist actions, resulting in the privatization of related channels like superluigilogan. Across Thirtyacre's combined channels, the SML maintains approximately 20 million subscribers as of recent counts, with individual videos routinely garnering tens of millions of views despite policy restrictions. Content evolution drew for incorporating , sexual innuendos, and stereotypical portrayals, contributing to YouTube's demonetization of the on December 12, 2017, and age-restriction of over 150 videos, even those lacking explicit elements. Thirtyacre reported substantial revenue losses from these measures, as noted in media coverage highlighting the platform's crackdown on non-family-friendly kids' content amid broader concerns like the scandal. The series has faced additional backlash for elements perceived as promoting racial stereotypes and inappropriate themes targeted at young audiences, though it retains a dedicated fanbase.

Economics and regulations

Specific Migration Limit

The specific migration limit (SML) refers to the maximum quantity of an individual substance, or a group of similar substances, permitted to migrate from a food contact material or article into the or food simulant it contacts, expressed in milligrams per kilogram of (mg/kg). This limit ensures that exposure to potentially harmful migrants remains below thresholds established through toxicological assessments, prioritizing consumer safety in applications. SML values are listed in Annex I of Commission Regulation (EU) No 10/2011, which governs materials intended for contact, with substances authorized only if they comply with these restrictions or demonstrate no risk at detected levels. For substances lacking a dedicated SML in the , a default generic limit of 60 mg/kg applies, serving as a conservative threshold unless further data justifies otherwise. In cases involving groups of substances, a total specific migration limit (SML(T)) may be specified, capping the combined from related compounds. is verified through laboratory testing using food simulants under conditions mimicking real-use scenarios, such as temperature and time, or via validated mathematical modeling for diffusion-based predictions, as outlined in regulatory guidelines. These methods account for factors like material composition, contact duration, and partitioning coefficients between the material and food. SML differs from the overall migration limit (OML), which caps the total mass of all non-volatile substances migrating from the material at 10 mg per square decimeter (mg/dm²) of surface area, equivalent to 60 mg/kg, without regard to individual identities. While OML addresses general inertness, SML targets specific toxicological concerns for authorized monomers, additives, or impurities, often set far lower—such as 0.05 mg/kg for certain dual-use additives posing risks. For instance, a precautionary SML of 40 µg/kg (0.00004 mg/kg) has been proposed for styrene monomer in , reflecting updated safety evaluations amid ongoing dairy product contamination studies. Enforcement relies on national authorities monitoring compliance, with recent amendments to food contact regulations, effective March 16, 2025, refining SMLs for select substances based on emerging data from the (EFSA). Violations can lead to product recalls or bans, underscoring the limits' role in causal risk mitigation rather than mere precautionary symbolism. Modeling tools, incorporating , enable pre-market predictions of SML adherence in multilayer packaging, reducing reliance on exhaustive physical testing while maintaining empirical rigor.

Slang and informal usage

Screw my life

"Screw my life," abbreviated as SML, is an expression used to articulate , , or exasperation over personal misfortunes or challenging situations. The typically appears in casual digital contexts such as text messages, posts, and online forums, where it conveys a sense of life's unfairness without the explicit of comparable phrases. For instance, an individual might post "SML" after experiencing a series of setbacks like missing a deadline or encountering unexpected car trouble, signaling resignation to bad luck. As a milder variant of the more profane "FML" ( my life), SML emerged in online vernacular to provide a euphemistic option suitable for broader audiences or moderated platforms. While FML emphasizes intense dismay often tied to dramatic or extreme events, SML adopts a toned-down tone, aligning with efforts to sanitize language in public or family-friendly settings. This distinction reflects evolving norms in digital etiquette, where users opt for less offensive alternatives to maintain accessibility, though both acronyms share roots in early 2000s humor and complaint-sharing communities like forums and sites. The phrase's adoption lacks a documented singular origin but aligns with the proliferation of acronym-based in the mid-2010s, fueled by platforms like and (now X), where concise expressions of emotion proliferated. Usage from slang aggregators indicate SML's in youth-oriented communication, often interchangeable with "story of my life" in relatable complaint narratives, though the "screw my life" interpretation predominates in contexts of acute irritation. Critics of such argue it fosters a culture of exaggerated victimhood, yet proponents view it as a harmless outlet for venting everyday stressors.

So much love

"SML" as an for "so much love" functions as to convey affection, gratitude, or strong emotional attachment in informal digital communications, such as text messages, emails, or interactions. This usage emerged from the trend of condensing phrases in early and online chatting to save characters and time, allowing senders to express warmth succinctly without full phrasing. It is typically appended at the end of a to someone close, akin to traditional sign-offs like "best regards" but with a more personal, endearing tone. The phrase implies deep appreciation or / fondness, often in response to , gifts, or shared experiences; for instance, after receiving assistance, one might write, "You saved the day—SML!" to blend thanks with endearment..html) Unlike more neutral acronyms, "SML" in this context carries positive emotional weight, distinguishing it from ironic or negative interpretations of the same letters. Its adoption appears widespread in English-speaking online communities since at least the mid-2000s, coinciding with the rise of mobile texting, though exact origins remain anecdotal due to the informal nature of evolution. While versatile across platforms like messaging apps and comment sections, this meaning of "SML" is context-dependent and may confuse recipients unfamiliar with acronym multiplicity, prompting clarification in mixed audiences. No formal linguistic studies quantify its prevalence, but acronym databases consistently catalog it under texting and love-related categories, underscoring its niche but recognized role in casual expression.

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