The mullets or grey mullets are a family of ray-finned fish found worldwide in coastal temperate and tropical waters, some species in fresh water. Mullets have served as an important source of food in Mediterranean Europe since Roman times; the family includes about 78 species in 20 genera. Mullets are distinguished by the presence of two separate dorsal fins, small triangular mouths, the absence of a lateral line organ, they feed on detritus, most species have unusually muscular stomachs and a complex pharynx to help in digestion. A common noticeable behavior in mullet is the tendency to leap out of the water. There are two distinguishable types of leaps: a straight, clean slice out of the water to escape predators and a slower, lower jump while turning to its side that results in a larger, more distinguishable, splash; the reasons for this lower jump are disputed, but have been hypothesized to be in order to gain oxygen rich air for gas exchange in a small organ above the pharynx. Taxonomically, the family is treated as the sole member of the order Mugiliformes, but as Nelson says, "there has been much disagreement concerning the relationships" of this family.
The presence of fin spines indicates membership in the superorder Acanthopterygii, in the 1960s, they were classed as primitive perciforms, while others have grouped them in Atheriniformes. They are classified as an order, within the subseries Ovalentaria of the clade Percomorpha in the 5th Edition of Fishes of the World. In North America, "mullet" by itself refers to Mugilidae. In Europe, the word "mullet" is qualified, the "grey mullets" being Mugilidae and the "red mullets" or "surmullets" being Mullidae, notably members of the genus Mullus, the red mullets. Outside Europe, the Mullidae are called "goatfish". Fish with common names including the word "mullet" may be a member of one family or the other, or unrelated such as the freshwater white sucker; the following genera were accepted as making up the Mugilidae: However, recent taxonomic work has reorganised the family and the following genera as make up the Mugilidae: J. S. Nelson, Fishes of the World. ISBN 978-0-471-25031-9. Froese and Daniel Pauly, eds..
"Mugilidae" in FishBase. June 2012 version. Sepkoski, Jack. "A compendium of fossil marine animal genera". Bulletins of American Paleontology. 364: 560. Retrieved 2011-05-19. SPECIES BY FAMILY/SUBFAMILY IN THE CATALOG OF FISHES Video: Mullet Dursey Sound May 2010, West Cork, Ireland
Carl Adolf Engström was a Finnish engineer and vuorineuvos. Engström got familiar at early age with large machinery and engineering workshop environment due to his stepfather's work as engineer in the Finnish State Railways. After completing his mechanical engineering studies in Helsinki Polytechnic School in 1877, Engström went to gain experience abroad in Sweden, United Kingdom and United States. Upon his return in 1884, Engström got vacance in the State Railways, he took part in steam locomotive designing, followed by railway projects in Savonia and Karelia. He worked as director for stone company Ab Granit in 1889–1895, after which he returned to State Railways for another five years. Engström was appointed manager of Hietalahti Shipyard and Engineering Works in 1900. During his time the company developed and the sales increased largely due to Russo-Japanese War and the First World War. On the other hand, the time was difficult due to increased strikes and confrontation between the workers and employers.
Engström left his position as company manager in 1918. Adolf Engström was born in Ostrobothnia, his parents were land surveyor Leonhard Engström and Adolfina née Taxell, daughter of Messukylä vicar Jonas Gabriel Taxell. The couple had sons Adolf and Otto. Leonhard Engström died when Adolf was four years old, the widow married her late husband's older brother Carl Petter Engström, Mechanical Engineer; the family moved to Helsinki in 1862, the Ostrobothnian boy had to adopt to a new environment. The stepfather worked for the Finnish State Railways, that way Adolf got familiar with engineering workshops and large machinery during his childhood. C. P. Engström became Chief Engineer in the State Railways in 1870 and during 1877–1890 he was board member in railway administration. Engström graduated from Helsinki Swedish Normal Lyceum in 1874 and continued his studies in Helsinki Polytechnic School and graduated Mechanical Engineer in 1877, he wanted to gain abroad useful practical experience abroad, which he could use for developing his home country.
Engström first worked for Motala Engineering Works in Sweden as draftsman, in Germany for Hannoversche Maschinenbau AG and Hohenzollern Locomotive Works. He went next to England, where he worked for Beyer Co in Manchester. Engström's following step was the United States. In 1884 Engström returned for State Railways, to take part in a locomotive project; the target was to design a locomotive suitable for Oulu railway. Engström made the structure more robust; this locomotive type was produced total 104 units. After the Oulu railway was built, Engström continued in Karelian railway projects, he worked for State Railways until 1889. Engström returned to State Railways for 1895–1900 to work as engineering workshop manager's assistant; as there were no new railway development projects, Engström sought for new opportunities. In 1889 he was appointed director and technical manager of Ab Granit, a stone company in Hanko; the company had gained foothold in construction business in Helsinki and grown amongst 30 largest companies of Finland.
At the turn of the 1890s the company employed 268 people. The 1894 erected Tsar Alexander II statue in Senate Square, of which foundation was constructed by Granit, promoted the company's sales in Russia. Engström was appointed manager of Sandvikens Skeppsdocka och Mekaniska Verkstads Ab in 1900, he followed engineer Edvin Bergroth, the first manager of the company, re-established after bankruptcy. Bergroth had developed the operations through investments, Engström received leadership of a financially solid company, which he continued developing determinedly. Engström sometimes faced situations which needed quick decisions – he for example received repair work of a shipwrecked vessel, too large to the dock; the Russo-Japanese War in 1904–1905 led to increased order intake of torpedo boats for the Imperial Russian Navy. During 1900 -- 1914 the company built total about 60 motor vessels. In addition to shipbuilding, the company produced large number of ship engines, steam boilers and railway wagons.
Engström's personal contribution was significant in the rolling stock production, the wagon projects balanced the wintertime docking workload drop. Engström modernised the shipyard; the dock was further extended in 1910 and 1912 and a new brass foundry was taken into use in 1914. Two years a new main engineering workshop was opened. Prior to the First World War, the company employed 597 people and the annual sales reached 2.4 million marks. The First World War increased the business again. Engström had further plans which did not actualise, such as a new dock layout, that would have enabled building many large ships simultaneously. All the investments were funded by company profit, the company did not collect capital from outside during that. By 1919, when Engström left his position, the share capital had grown from half million to six million marks. Engström's era as shipyard leader was the time of organisation of labour and employers; the yard experienced some occasional strikes at the late 19th century, after the yard faced larger strikes and c
Moran is a city in Allen County, United States. As of the 2010 census, the city population was 558. Moran had its start in the year 1881 by the building of the Missouri Pacific Railroad through that territory; the Kansas City Pacific (later known as the Kansas City subdivision of the Missouri-Kansas-Texas Railroad built through the town. Moran is located at 37°54′58″N 95°10′15″W. According to the United States Census Bureau, the city has a total area of 0.42 square miles, all land. The climate in this area is characterized by hot, humid summers and mild to cool winters. According to the Köppen Climate Classification system, Moran has a humid subtropical climate, abbreviated "Cfa" on climate maps; as of the census of 2010, there were 558 people, 219 households, 142 families living in the city. The population density was 1,328.6 inhabitants per square mile. There were 247 housing units at an average density of 588.1 per square mile. The racial makeup of the city was 93.7% White, 2.0% African American, 1.3% Native American, 0.2% Pacific Islander, 0.2% from other races, 2.7% from two or more races.
Hispanic or Latino of any race were 1.1% of the population. There were 219 households of which 34.2% had children under the age of 18 living with them, 43.4% were married couples living together, 10.5% had a female householder with no husband present, 11.0% had a male householder with no wife present, 35.2% were non-families. 28.8% of all households were made up of individuals and 14.6% had someone living alone, 65 years of age or older. The average household size was 2.36 and the average family size was 2.75. The median age in the city was 45.4 years. 23.7% of residents were under the age of 18. The gender makeup of the city was 45.7% male and 54.3% female. As of the census of 2000, there were 562 people, 224 households, 140 families living in the city; the population density was 1,351.3 people per square mile. There were 255 housing units at an average density of 613.1 per square mile. The racial makeup of the city was 96.44% White, 0.36% African American, 1.96% Native American, 1.25% from two or more races.
Hispanic or Latino of any race were 0.36% of the population. There were 224 households out of which 28.6% had children under the age of 18 living with them, 48.7% were married couples living together, 9.4% had a female householder with no husband present, 37.5% were non-families. 31.3% of all households were made up of individuals and 19.6% had someone living alone, 65 years of age or older. The average household size was 2.34 and the average family size was 2.99. In the city, the population was spread out with 24.7% under the age of 18, 7.7% from 18 to 24, 21.9% from 25 to 44, 20.5% from 45 to 64, 25.3% who were 65 years of age or older. The median age was 42 years. For every 100 females, there were 90.5 males. For every 100 females age 18 and over, there were 80.8 males. The median income for a household in the city was $30,179, the median income for a family was $37,750. Males had a median income of $25,729 versus $19,028 for females; the per capita income for the city was $14,080. About 8.7% of families and 13.1% of the population were below the poverty line, including 6.7% of those under age 18 and 25.3% of those age 65 or over.
Moran is a part of USD 256 Marmaton Valley Schools. The district high school is Marmaton Valley High School located in Moran. Marmaton Valley High School mascot is Wildcats. Debra Dene Barnes, 1968 Miss America Marmaton Valley High School CountyAtlas and plat book of Allen County, Kansas. Plat book of Allen County, Kansas. CityCity of Moran Moran - Directory of Public OfficialsSchoolsUSD 256, local school districtMapsMoran City Map, KDOT
In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems, assuming intelligence is computational, is equivalent to that of solving the central artificial intelligence problem—making computers as intelligent as people, or strong AI. To call a problem AI-complete reflects an attitude that it would not be solved by a simple specific algorithm. AI-complete problems are hypothesised to include computer vision, natural language understanding, dealing with unexpected circumstances while solving any real world problem. AI-complete problems cannot be solved with modern computer technology alone, but would require human computation; this property could be useful, for example, to test for the presence of humans as CAPTCHAs aim to do, for computer security to circumvent brute-force attacks. The term was coined by Fanya Montalvo by analogy with NP-complete and NP-hard in complexity theory, which formally describes the most famous class of difficult problems.
Early uses of the term are in Erik Mueller's 1987 Ph. D. dissertation and in Eric Raymond's 1991 Jargon File. AI-complete problems are hypothesized to include: AI peer review Bongard problems Computer vision Natural language understanding Dealing with unexpected circumstances while solving any real world problem, whether it's navigation or planning or the kind of reasoning done by expert systems. To translate a machine must be able to understand the text, it must be able to follow the author's argument, so it must have some ability to reason. It must have extensive world knowledge so that it knows what is being discussed — it must at least be familiar with all the same commonsense facts that the average human translator knows; some of this knowledge is in the form of facts that can be explicitly represented, but some knowledge is unconscious and tied to the human body: for example, the machine may need to understand how an ocean makes one feel to translate a specific metaphor in the text. It must model the authors' goals and emotional states to reproduce them in a new language.
In short, the machine is required to have wide variety of human intellectual skills, including reason, commonsense knowledge and the intuitions that underlie motion and manipulation and social intelligence. Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it. Current AI systems can solve simple and/or restricted versions of AI-complete problems, but never in their full generality; when AI researchers attempt to "scale up" their systems to handle more complicated, real world situations, the programs tend to become excessively brittle without commonsense knowledge or a rudimentary understanding of the situation: they fail as unexpected circumstances outside of its original problem context begin to appear. When human beings are dealing with new situations in the world, they are helped immensely by the fact that they know what to expect: they know what all things around them are, why they are there, what they are to do and so on.
They can adjust accordingly. A machine without strong AI has no other skills to fall back on. Computational complexity theory deals with the relative computational difficulty of computable functions. By definition it does not cover problems whose solution is unknown or has not been characterised formally. Since many AI problems have no formalisation yet, conventional complexity theory does not allow the definition of AI-completeness. To address this problem, a complexity theory for AI has been proposed, it is based on a model of computation that splits the computational burden between a computer and a human: one part is solved by computer and the other part solved by human. This is formalised by a human-assisted Turing machine; the formalisation defines algorithm complexity, problem complexity and reducibility which in turn allows equivalence classes to be defined. The complexity of executing an algorithm with a human-assisted Turing machine is given by a pair ⟨ Φ H, Φ M ⟩, where the first element represents the complexity of the human's part and the second element is the complexity of the machine's part.
The complexity of solving the following problems with a human-assisted Turing machine is: Optical character recognition for printed text: ⟨ O, p o l y ⟩ Turing test: for an n -sentence conversation where the oracle remembers the conversation history: ⟨ O, O ⟩ for an n -sentence conversation where the conversation history must be retransmitted: ⟨ O, O ⟩ for an n -sentence conversation where the conversation history must be retransmitted and the person takes linear time to read the query: ⟨ O ( n
The Siege of Svetigrad began on 14 May 1448 when an Ottoman army, led by Sultan Murad II, besieged the fortress of Svetigrad. After the many failed Ottoman expeditions into Albania against the League of Lezhë, a confederation of Albanian Principalities created in 1444 and headed by Skanderbeg, Murad II decided to march an army into Skanderbeg's dominions in order to capture the key Albanian fortress of Svetigrad; the fortress lay on an important route between present-day North Macedonia and Albania, thus its occupation would give the Ottomans easy access into Albania. The force prepared by Murad was the largest force with which the Ottomans had attacked Skanderbeg. Murad planned to take the fortress, march into the Albanian interior, capture the main citadel of Krujë, thus crushing the Albanian League. At the same time, Skanderbeg had been at war with Venice. Realizing the magnitude of his challenge, Skanderbeg attempted to relieve the garrison by engaging in skirmishes with the Ottoman army.
His forces succeeded in inflicting heavy casualties on the Turkish forces through guerrilla-style attacks. Efforts were made by Skanderbeg to use intelligence forces, operating as far as Constantinople, to gather information on Murad's plans of action. Meanwhile, near Scutari, he had been able to defeat a Venetian force and managed to weaken the Venetian presence in Albania. Despite these efforts, on 31 July the garrison of Svetigrad surrendered due to a disruption in the water supply; the garrison was spared and a force of Ottoman Janissaries was stationed inside the fortress instead. Two years Murad would march against Krujë, only to suffer a heavy defeat. In 1444 the major princes of the Albanian Principalities, which up to that point had been vassals of the Ottoman Empire and formed the League of Lezhë, an anti-Ottoman confederacy under Skanderbeg's lead; as a result, the Ottoman Empire sought to re-establish control over Albania. As of 1448, all Ottoman expeditions into Albania had failed and Murad II chose lead a force in person into Albanian territory and fragment the League.
The sultan decided to capture the fortress of Svetigrad. This fortress served the strategic purpose of protecting the Albanian eastern frontier, while allowing the Albanians to launch their own assaults on Ottoman territory. In late 1447, war began between Venice and the League, but had not yet escalated into full-scale conflict. Skanderbeg had declared war on Venice as a result of a diplomatic impasse; this left him open to invasion from the East. Albanian intelligence groups informed Skanderbeg—the main leader of the revolt—that a large Ottoman army was preparing to march into Albania, the number of, reported by some as being as high as 170,000; this army, however, is to have contained no more than 80,000 soldiers. Murad marched his army into Monastir. Skanderbeg urgently called for material aid Venice; the answer, was negative. Instead, the only aid received came from the Neapolitans and the Ragusans. Nonetheless, Murad soon marched into Black Drin valley, traveling near Svetigrad. In response, Skanderbeg strengthened the garrisons of Krujë, Stellushi and Berat by ordering the populations around these fortress to take up arms.
Shortly before the Ottoman siege began, Skanderbeg positioned himself, 4,000 cavalry, 7 miles from the Turkish camp. The force included 8,000 other soldiers. Skanderbeg ordered. Moisi Arianit Golemi and Muzaka of Angelina were ordered, with thirty horsemen, to dress as peasants and enter the fortress; the plot was discovered and the company was attacked, but the attackers were driven off. Upon returning to the main Ottoman camp, one of the commanding pashas saw that this was one of Skanderbeg's plots and sent 4,000 horsemen to find out where Skanderbeg was camping by following Moisi's band. Moisi led the Ottoman force into a valley, Skanderbeg, ready for such an enterprise, surrounded the valley with his forces; when the Ottoman force was within distance, the Albanians sprung the ambush and the Ottoman force was annihilated. This happened on 14 May 1448, after. Murad's force contained 80,000 men and two cannons, which could fire 200 pounds balls, his army contained a fresh corps of Janissaries, 3,000 debtors and bankrupts fighting to regain their freedom.
The Count of Gurrica persuaded Skanderbeg to incorporate a scorched earth strategy, by destroying all supplies that might be used by the Ottoman army. The Ottoman force paraded around the fortress and offered 300,000 aspras to those who would open the gate and let the Ottoman army in the fortress without a fight; the heralds proposing these offers went into the fortress at night time and the garrison commanders gave them a splendid dinner, so that they would get the impression that the enemy was well prepared for a lengthy siege. After the dinner their offers were rejected and they were sent back to the Sultan; the size of the Ottoman army troubled Skanderbeg because of the effects it could have on the morale of his soldiers and on the local population which supported the princes. Skanderbeg thus moved from village to village, disguised as a common soldier, invoked the fighting spirit of the population; as a result of this activity, the local chieftains agreed to fight the Ottomans and persuaded Skanderbeg to draw up his plans in concert with theirs.
To relieve the garrison of Svetigrad, Skanderbeg continually harassed the Ottoman army. Many of these attacks had been surprise ambushes of isolated Ottoman forces. Hoping to evade Ottoman patrols, Skanderbeg moved towards the Ottoman camp. On 22 June Skanderbeg led
Purshia mexicana is a species of perennial flowering small tree in the rose family known by the common name Mexican cliffrose. It is native to western-northern Mexico, the region of the Sierra Madre Occidental cordillera. Purshia stansburyana, native to the southwestern United States, has sometimes been included within P. mexicana. In its mountainous, or higher elevation habitat, it grows in woodlands and plateau habitat. Stenophyllanin A, a tannin, can be found in P. mexicana. The range of Mexican Cliffrose is from the western Mexican Plateau in the south, the southern Sierra Madre Occidental cordillera north to a small region of northwest Sonora; the plant is browsed by deer and sheep, is important to these species during the winter. Native Americans made ropes and clothing from the bark, fashioned arrow shafts from the stems. Little, Elbert L.. "Map 55-SW, Map 55-N, Cowania mexicana". Minor Western Hardwoods. Atlas of United States Trees. 3. US Government Printing Office. LCCN 79-653298. Cronquist, A..