Mo
Mohammed Amer (born July 24, 1981), professionally known as Mo Amer, is a Palestinian-American stand-up comedian, actor, writer, and producer born in Kuwait to Palestinian refugee parents who fled to Houston, Texas, during the Gulf War when he was nine years old.[1][2][3] He rose to prominence through comedy specials such as Relative (2016) and The Vagabond (2018) on Netflix, becoming the first Arab American to headline a one-hour televised stand-up special, and for voicing a character in the animated film Ron's Gone Wrong (2021).[4][5] Amer created, co-wrote, executive produced, and stars in the Netflix semi-autobiographical comedy-drama series Mo (2022–present), portraying a fictionalized version of himself as a Palestinian refugee in Houston struggling with asylum delays, cultural clashes, family obligations, and daily hustles amid statelessness.[6][7][8] The series, which draws directly from his experiences including navigating U.S. immigration bureaucracy without citizenship, has been noted for its blend of humor and realism in depicting refugee life, earning praise for authenticity while facing scrutiny over its portrayal of Palestinian identity in politically charged contexts.[9][10]Science and technology
Chemistry
Molybdenum is a chemical element with atomic number 42 and symbol Mo in the periodic table. It is classified as a transition metal in group 6, period 5, characterized by its silvery-white appearance and ductile nature in pure form.[11] The element was first identified in 1778 by Swedish chemist Carl Wilhelm Scheele through analysis of molybdena, a lead ore mineral, and subsequently isolated as a distinct metal in 1781 by Peter Jacob Hjelm via reduction of molybdic acid with carbon.[12] Key physical properties of molybdenum include a high melting point of 2623 °C, boiling point of 4639 °C, and density of 10.28 g/cm³ at room temperature, making it one of the refractory metals suitable for high-temperature applications.[13] Chemically, it exhibits valence states from -1 to +6, with common oxidation states of +4 and +6; it is relatively inert at room temperature but reacts with oxidizing acids and forms stable oxides like MoO₃ upon heating in air.[11] Its corrosion resistance stems from the formation of protective oxide layers, particularly in acidic environments, though it can suffer pitting in chloride solutions.[14] Molybdenum occurs naturally primarily as the sulfide mineral molybdenite (MoS₂), the chief ore from which it is extracted, often as a byproduct of copper mining in porphyry deposits.[15] Global mine production reached approximately 300,000 metric tons of contained molybdenum in 2023, with China, Chile, the United States, Peru, and Mexico accounting for over 90% of output.[16] Biologically, molybdenum serves as an essential trace element, functioning as a cofactor in enzymes such as nitrogenase, which catalyzes the reduction of atmospheric N₂ to ammonia in nitrogen-fixing bacteria and plants, supporting global nitrogen cycles.[17] Deficiencies manifest in ruminants as molybdenosis, characterized by diarrhea and reduced weight gain due to impaired copper metabolism, while human correlations include potential links to esophageal cancer in low-Mo regions, though causality remains debated.[18] Industrial applications leverage molybdenum's strength-enhancing properties, primarily as an alloying agent in steels (up to 10% addition) to improve hardenability, tensile strength, and resistance to wear and corrosion, as seen in high-speed tool steels and stainless variants.[19] It also acts as a catalyst in petroleum hydrodesulfurization, converting sulfur compounds to hydrogen sulfide, and in chemical processes like epoxidation; other uses include dry lubricants (as MoS₂) and pigments.[20] These roles underscore its causal importance in enabling durable materials and efficient refining, with demand driven by steel production exceeding 80% of consumption.[16]Computing
Mo's algorithm is an offline query processing technique employed in competitive programming to efficiently answer range queries on static arrays, such as frequency counts or distinct elements within subarrays, by sorting queries into blocks to minimize pointer movements.[21][22] The method divides the array into blocks of size typically √N, where N is the array length, and sorts queries first by the block of the left endpoint L and second by the right endpoint R within each block; this ordering ensures that transitions between consecutive queries involve small adjustments to the current range [cl, cr], with add/remove operations applied incrementally to maintain the query state.[23][24] The time complexity of Mo's algorithm is O((N + Q) √N ⋅ F), where Q is the number of queries and F is the time cost of adding or removing an element from the current range, often O(1) for simple operations like frequency updates using an array or map.[23][22] This arises because there are O(Q / B) block changes (each costing O(N) to adjust pointers) and O(Q ⋅ B / N) intra-block movements (each O(1)), optimized with block size B ≈ √N; it outperforms naive O(N Q) approaches for large N and Q up to 10^5.[21][24] Pseudocode for the core sorting and processing is as follows:Add and remove functions update the state (e.g., frequency array) and the aggregate answer.[22][23] In software localization, .mo files serve as compiled binary formats for message catalogs generated from .po source files using GNU gettext tools, enabling efficient runtime translation lookups in applications by storing hashed string mappings.[25][26] These machine object files include a magic number (0x950412de or byte-swapped 0xde120495) followed by metadata like revision (0x00000000 for format 0) and string counts, with data sections for original strings, translations, hash tables, and indices to support O(1) average-case lookups via hashing.[25] The format prioritizes speed over human readability, contrasting editable .po files, and is integral to internationalizing open-source software like Linux distributions.[26][27]block_size = sqrt(N) sort queries by (L / block_size, R) current_L = 0, current_R = -1 for each query in sorted order: while current_L > query.L: add(--current_L) while current_R < query.R: add(++current_R) while current_L < query.L: remove(current_L++) while current_R > query.R: remove(current_R--) answers[query.index] = current_answerblock_size = sqrt(N) sort queries by (L / block_size, R) current_L = 0, current_R = -1 for each query in sorted order: while current_L > query.L: add(--current_L) while current_R < query.R: add(++current_R) while current_L < query.L: remove(current_L++) while current_R > query.R: remove(current_R--) answers[query.index] = current_answer