title: 2017–18 Liverpool F.C. season

text: Liverpool opened a busy December with a game at the Falmer Stadium against Brighton & Hove Albion on 2 December. Two goals within a minute of each other, first from Can (who was playing at centre back) then Firmino, gave Liverpool a 0–2 lead and they finished the game winning 1–5 thanks to additional goals from Firmino, Coutinho, and a Dunk own goal. Brighton's only goal came from Glenn Murray who scored from the penalty spot. The next game was the final game of the Champions League group stage, a home bout against Spartak Moscow on 6 December. Liverpool needed a result to make it to the next round so tensions were running high at Anfield. However, the Reds dispatched Spartak 7–0, with goals coming from Firmino, Salah, a double from Mane and a hat trick for Coutinho and finished the group at the top. The next fixture was the first league installment of the season of the Merseyside derby against crosstown rivals Everton on 10 December at Anfield. Liverpool maintained control throughout the first half and Salah's curling effort in the 42nd minute gave Liverpool the lead. Liverpool continued to dominate but a dubious penalty decision against Lovren saw Wayne Rooney converted a penalty in the 77th to tie the game at 1–1 where it finished. Klopp said following the game about the controversial penalty incident, "In my understanding, it's not a penalty." The next game was yet another held at Anfield where Liverpool hosted West Brom on 13 December. The game was a 0–0 stalemate against West Brom at Anfield, with the most notable event being an 82nd minute Solanke goal was disallowed for a handball drawing conversation on whether or not the correct call was made. On 17 December at the Vitality Stadium, Liverpool took on Bournemouth. The Reds bounced back in the next game winning 0–4 with goals from Coutinho, Lovren, and Salah before the half, and Firmino after. The next game was against Arsenal at the Emirates on 22 December. In an exciting affair, Liverpool went 0–2 up through Coutinho in the 26th and Salah in the 52nd minute, but Arsenal took the lead with three goals in five minutes through goals from Alexis Sánchez, Granit Xhaka (on a long shot in which goalie Mignolet was heavily criticized for not doing better) and Mesut Özil. The Reds evened the score at 3–3 with a 71st-minute goal from Firmino giving the team their 8th league draw in 19 games, at the time the second most in the league. Liverpool then returned to Anfield for their Boxing Day fixture against bottom-place Swansea City. Coutinho gave the Liverpool early in the first half and the game stood at 1–0 at half, but with a goal from Firmino in the 52nd, one from Alexander-Arnold in the 65th, another from Firmino in the 66th, and a capper from Oxlade-Chamberlain in the 82nd gave the Reds a 5–0 victory. On 27 December, ahead of the New Year, Liverpool also welcomed the news of long-term target Virgil van Dijk, signed for a generally reported fee going up to £75 million. With their new signing in attendance, Liverpool played their final match of the calendar year on 30 December against Leicester at Anfield. Vardy gave the Foxes a 0–1 lead in the 3rd where it stood until the 52nd with a Salah equalizer. Salah scored again in the 76th giving Liverpool a 2–1 victory and ensuring the Reds would end 2017 in the top four.


title: 2017–18 Liverpool F.C. season

text: The Reds opened their 2018 on the first day of the year by traveling to Turf Moor to take on Burnley. Mane broke the deadlock in the 61st with a goal but Jóhann Berg Guðmundsson leveled the score in the 87th minute. The Reds, however, were able to get all three points off a Ragnar Klavan header in the 94th minute with a 1–2 final. Following the triumph in the league, the Reds hosted Everton for the second time in under 30 days, this time in the third round of the 2017–18 FA Cup on 5 January. While Everton received the hotly contested penalty in the first meeting, Liverpool was the one to benefit from a controversial penalty call as Mason Holgate brought Lallana down inside the box and Milner converted the penalty in the 35th minute. The derby match also featured Holgate and Firmino getting into a verbal altercation shortly before the end of the first half following a push from Holgate to Firmino that sent the latter over the advertising boards. In the 67th minute, Gylfi Sigurðsson scored on a counterattack to equalize the game at one. In the 84th minute, however, van Dijk in his Liverpool debut scored off a corner kick making it 2–1 and marking a second game in a row with a late headed goal from a defender to win the game. The day after, on 6 January, the club made the official announcement that (subject to a medical and personal terms) Coutinho would be leaving for Barcelona on a deal that Paul Joyce of "The Times" reported could reach up to £142 million. Coutinho was subsequently announced by Barcelona that day. On 14 January, Liverpool took on the undefeated Manchester City at Anfield in hopes of deal City their first loss in the league as well as a measure of revenge for the 0–5 loss the Reds were dealt in the reverse fixture. Liverpool started off strong with an Oxlade-Chamberlain goal in the ninth minute, but City scored an equalizer through in the 40th through a Leroy Sane effort. From the 59th to the 68th, Liverpool extended the lead to 4–1 through goals from Firmino, Mane, and Salah in a thrilling ten minutes of action. City got one back in the 84th from Bernardo Silva and another from İlkay Gündoğan in the 91st put it at 4–3, but the Reds held on and doled City their first loss of the league season. The next game for the Reds was a 22 January meeting in South Wales against Swansea and recently placed manager Carlos Carvalhal. Alfie Mawson scored the lone goal of the match in the 40th minute and the bottom place Swans took all three from the Reds with a 1–0 defeat given to the visitors. In the fourth round proper of the FA Cup, on 27 January, Liverpool took on West Brom. Firmino's chip in the fifth gave the early lead, but a four-minute double to Jay Rodriguez put West Brom up 1–2 in the 11th. Video assistant referee replay played a crucial first half role as it denied Craig Dawson a goal to make the game 1–3, then awarded a penalty to Liverpool, which was subsequently missed by Firmino. West Brom added a third with an own goal from Matip late in first half added time. Salah put the Reds within one in the 78th, but the 2–3 scoreline stood and the Reds were stunned at home by the second from bottom Baggies in the cup. The final fixture of the month was on 30 January where the Reds visited John Smith's Stadium and Huddersfield Town. Emre Can's long range effort in the 26th put the Reds up 0–1 early, and Firmino added a second right before the break. Salah's 78th minute spot kick made it 0–3 and Liverpool finished January with a comfortable victory.


title: 2017–18 Liverpool F.C. season

text: February's first fixture occurred on the 4th when the Reds welcomed Tottenham to Anfield. Liverpool were off to a flying start following Salah's goal in the third minute giving Liverpool an early 1–0 lead. The score stayed this way until a screamer from Victor Wanyama in the 80th set off a frenetic close to the game. The 85th minute saw goalie Loris Karius come out and attempt to slide tackle the ball away from Harry Kane, however referee Jon Moss awarded a controversial penalty to Spurs for an infraction where some fans and pundits claimed Kane dived in hopes to win a call. Kane took, and subsequently missed, the kick in the 87th and in the 91st minute, Salah gave an outstanding solo effort to find a seeming winner for the Reds, but yet again a controversial penalty was given when van Dijk attempted to clear the ball from the box but missed and hit Erik Lamela. Kane took this penalty as well and converted in the 95th leaving the game level at 2–2. A frustrated Klopp stated following the game, "I don't understand either of the penalty situations. The first one was offside and the second, I know already what the ref and his assistant will say. There was a touch, a little touch. But Lamela has jumped into him and wanted the touch and to go down." Spurs manager Mauricio Pochettino saw the incidents differently saying, "Both were a penalty and it is not controversial. Sometimes people complain about the referee, but when they are right it is good to tell everyone." The Reds had a week off until their trip to St Mary's Stadium in Southampton on 11 February. In winter signing van Dijk's first match back in Southampton, the Reds won the match 0–2 with goals from Firmino in the sixth and Salah in the 42nd.Although Van Dijk did receive a hostile reception. The next fixture for Liverpool was on Valentine's Day in Portugal where the Reds played in the round of 16 of the Champions League for the first time since 2009. Against Porto, the Reds opened scoring in the 25th through a Mane goal that was also mishandled by Porto keeper José Sá. Salah added another goal in the 29th to take the lead to 0–2, where it stood at the halftime whistle. In the second half, the goals continued as Mane added a second in the 53rd, Firmino scored his first of the game in the 69th, and Mane got his hat-trick goal in the 85th to give the Reds a 0–5 first leg victory. Following a four-day mini camp in Marbella the Reds returned home for their final fixture of the month on 24 February against West Ham. Can opened the scoring with a header off a corner in the 29th, and Salah in the 51st and Firmino in the 57th added on to the lead. Michail Antonio added one for the Hammers in the 59th to put the score at 3–1, but a Mane goal in the 77th to make it 4–1 put the game away and, for the day, the Reds moved into second place.


title: 2017–18 Liverpool F.C. season

text: Liverpool's first match of the month was a home bout on 3 March against Newcastle, as the Reds welcomed back manager Rafa Benítez, who won the 2005 Champions League with the club. Salah opened the scoring in the 40th minute and Mane put in another in the 55th to give the Reds a comfortable 2–0 victory over the Magpies. The Reds then played mid-week at home on 6 March against Porto in the return fixture of the Champions League round of 16. It was a quiet affair, Mane had a chance that hit the post and Danny Ings had a strong effort saved, but the game ended 0–0 and Liverpool moved on to the quarterfinals. Following these matches, on 10 March Liverpool traveled to Old Trafford in another iteration of the Northwest Derby against Manchester United. Marcus Rashford scored twice in ten minutes to give United a 2–0 lead within 25 minutes, were the score stood till the half. An Eric Bailly own goal put Liverpool back in business in the 66th, but it was not enough and a 2–1 scoreline was final. The loss put the Reds five points back of second place. On 16 March, the Reds learned that their Champions League quarterfinal opponent would be the only other English team remaining, Manchester City. The fixtures were set for 4 April at Anfield and 10 April at the Etihad. The following day, Liverpool returned to Anfield to square off with Watford and, in stylish fashion, dispatched the Hornets 5–0. Salah had his first English hat trick as he scored in the 4th, 43rd, and 77th, and then added one more for good measure in the 85th. Firmino added in one of his own in the 49th. The final fixture of the month occurred on 31 March at Selhurst Park against Crystal Palace. Palace opened the scoring in the 13th with a Luka Milivojević spot kick and the 1–0 scoreline held into halftime. Just four minutes into the second half, however, Liverpool struck back with a Mane goal off a Milner cross. The 1–1 deadlock was broken as Salah slotted home another in the 84th and the Reds took a 1–2 victory out of London.


title: 2017–18 Liverpool F.C. season

text: Liverpool opened up the month of April of the fourth as they took on Manchester City at Anfield in the first leg of the Champions League quarter-finals. The Reds got off to a flying start with goals from Salah in the 12th, Oxlade-Chamberlain off a brilliant effort from outside the box in the 21st, and finally Mane in the 31st. The Reds finished with a comfortable 3–0 victory and for the second time this season defeated City at home. In between the first and second legs, Liverpool traveled across the river to take on Merseyside rivals Everton at Goodison Park on 7 April. The affair ended 0–0, with the best effort coming from Yannick Bolasie, who tried a curling effort only for it to be saved well by Karius. The Reds could not find a goal, and their opportunity to go second in the table was missed. Up next was the second leg of the quarter-finals at the Etihad against Manchester City on 10 April. City needed at least three goals, and they found one almost immediately from Gabriel Jesus in just the second minute. The Reds seemed slightly wobbled, and chances from Bernardo Silva and a goal ruled offside from Leroy Sane highlighted that. Following the half, however, with City manager Pep Guardiola sent to the stands during the break, Liverpool found their away goal in the 56th from Salah, and another in the 77th from Firmino. The Reds would win 1–2 and advance 5–1 on aggregate to the semi-finals. Liverpool returned home to Anfield to take on Bournemouth on 14 April, and they celebrated their advancement with a strong 3–0 showing. The goals came from Mane in the 7th, Salah in the 69th, and Firmino with a 90th minute addition to the scoreline. Next came a match with bottom-place West Brom on 21 April. The Baggies, coming off a victory at Manchester United to clinch the title in favor of Manchester City, had already forced Liverpool to drop points at Anfield and defeated them in the FA Cup. Liverpool found another early goal through Danny Ings, his first since the final match of Brendan Rodgers' tenure as Liverpool manager. Salah added another in the 72nd, and the Reds seemed on their way to all three points. However, a 79th-minute goal from Jake Livermore and an 88th-minute leveler from Salomón Rondón to make it 2–2 meant the points would be shared. Liverpool could not dwell on this result as the final European night at Anfield was on deck on 24 April in the Champions League semi-finals against A.S. Roma. The first key action of the game was not a goal, but rather an injury as Oxlade-Chamberlain went down with what was eventually ruled as a knee ligament injury. The Reds could not find a breakthrough until a sparkling 36th-minute effort from Salah against his former team put the Reds ahead. Salah added another in the first minute of added time of the first half and the Reds carried a 2–0 lead into the second half. The Reds would not stop as Mane added a third in the 56th and Firmino had an eight-minute double to make the lead 5–0. Roma, however, got two key away goals back through Edin Džeko in the 81st and Diego Perotti from the penalty spot after a James Milner handball in the 85th. Regardless, the Reds walked away with a 5–2 and the driver's seat of the second leg. The next day, the club would announce that Oxlade-Chamberlain was set to miss the remainder of the season as well as the 2018 World Cup for England. The final fixture of the month was at Anfield against 19th place Stoke City on 28 April. Liverpool had the best of the chances: a Salah miss on a one-on-one with the keeper in the fifth, an Ings effort ruled out for offside in the 40th, and a controversial potential handball on Erik Pieters in the 87th, but neither team could find the net and the final score was 0–0.


title: 2017–18 Liverpool F.C. season

text: Liverpool's May began with the second leg of the Champions League semi-finals against Roma on 2 May. Liverpool quickly got an away goal from Mane in the ninth minute, striking first in the match. Just six minutes later, however, in the 15th minute, Roma would see one back after an attempted Lovren clearance struck Milner directly in the face and back into the Liverpool net. The Reds then saw a second goal in the 25th minute off a Wijnaldum header on a corner kick, marking his first away goal for Liverpool. The match entered the half 1–2 and with Liverpool in strong position to advance, however Roma continue to attack. Dzeko scored in the 52nd to level the match score, then Radja Nainggolan hit an exceptional long shot in the 86th. Finally, Klavan was penalized for Liverpool and Nainggolan achieved a brace off a spot kick in the 94th, but with Roma needed one more for extra time it was too little, too late. The final whistle sounded and Liverpool, while losing 4–2, advanced on an aggregate score of 6–7 and would see Real Madrid in the Champions League Final. That weekend, Liverpool would take on Chelsea on 6 May at Stamford Bridge, with a win sealing top four and Champions League for the next season. Alas, in the 32nd minute, it was Chelsea striker Olivier Giroud who found the lone goal of the game and Chelsea won 1–0, giving them an opportunity to be level with Liverpool on points on the last match-day. This, however, was not the case for Chelsea as they stumbled to Huddersfield 1–1 on 9 May, meaning Liverpool would need, barring a massive goal differential swing, just a draw regardless of Chelsea's final day result to clinch fourth place. Liverpool's final Premier League match of the season took place at Anfield against Brighton & Hove Albion on 13 May. The Reds wasted little time in finding the breakthrough as Salah scored in the 26th minute and sealed the record for most goals in a 38-game Premier League season, with 32. Just five minutes before halftime, Lovren doubled the Reds lead with a massive header. Liverpool continued forward as Solanke and Andy Robertson scored their first Liverpool goals in the 53rd and 85th minutes as Liverpool cruised to a 4–0 victory and, as a result, fourth place in the Premier League.


title: 2017–18 Liverpool F.C. season

text: Kyiv's Olimpiyskiy National Sports Complex hosted the Champions League final on 26 May against the two-time defending champions in Madrid. Liverpool suffered an early blow as Salah sustained what Klopp later specified as a serious injury to "either the collarbone or the shoulder" after just 30 minutes of play. Regardless, the score was 0–0 at the half but in the 51st minute, Karim Benzema pounced on a Karius roll-out of the ball and ultimately get a foot to direct the ball net-bound and give Madrid the 1–0 lead. Liverpool equalized in the 55th through Mane off a corner kick, but nine minutes after that Gareth Bale came off the bench and deliver a stunning bicycle kick to break the deadlock again. Bale found his second of the game and Madrid's third in the 83rd off a long shot that Karius mishandled into his own net. Madrid went on to win the Champions League 3–1 and Karius found harsh criticism for mistakes described as part of a "horror show" of a night for the Liverpool keeper. A few days after the game, Karius was diagnosed with a concussion which likely occurred in a clash between him and Sergio Ramos a few minutes before Madrid's first goal. Despite the season-ending heartbreak, this was Liverpool's best Champions League performance since 2007 and widely considered another step in the right direction for Liverpool as a whole.


title: 2017–18 Liverpool F.C. season

text: As of 15 June 2017, Liverpool have announced four pre-season friendlies against Hertha BSC, Athletic Bilbao Tranmere Rovers and Wigan Athletic.


title: Jevons paradox

text: In economics, the Jevons paradox (; sometimes Jevons effect) occurs when technological progress or government policy increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost of use increases its demand, increasing, rather than reducing, resource use. The Jevons' effect is perhaps the most widely known paradox in environmental economics. However, governments and environmentalists generally assume that efficiency gains will lower resource consumption, ignoring the possibility of the effect arising.


title: Jevons paradox

text: In 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption.


title: Jevons paradox

text: The issue has been re-examined by modern economists studying consumption rebound effects from improved energy efficiency. In addition to reducing the amount needed for a given use, improved efficiency also lowers the relative cost of using a resource, which increases the quantity demanded. This counteracts (to some extent) the reduction in use from improved efficiency. Additionally, improved efficiency increases real incomes and accelerates economic growth, further increasing the demand for resources. The Jevons' effect occurs when the effect from increased demand predominates, and the improved efficiency results in a faster rate of resource utilization.


title: Jevons paradox

text: Considerable debate exists about the size of the rebound in energy efficiency and the relevance of the Jevons' effect to energy conservation. Some dismiss the effect, while others worry that it may be self-defeating to pursue sustainability by increasing energy efficiency. Some environmental economists have proposed that efficiency gains be coupled with conservation policies that keep the cost of use the same (or higher) to avoid the Jevons' effect. Conservation policies that increase cost of use (such as cap and trade or green taxes) can be used to control the rebound effect.


title: Jevons paradox

text: The Jevons' effect was first described by the English economist William Stanley Jevons in his 1865 book "The Coal Question". Jevons observed that England's consumption of coal soared after James Watt introduced the Watt steam engine, which greatly improved the efficiency of the coal-fired steam engine from Thomas Newcomen's earlier design. Watt's innovations made coal a more cost-effective power source, leading to the increased use of the steam engine in a wide range of industries. This in turn increased total coal consumption, even as the amount of coal required for any particular application fell. Jevons argued that improvements in fuel efficiency tend to increase (rather than decrease) fuel use, writing: "It is a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth."


title: Jevons paradox

text: At that time, many in Britain worried that coal reserves were rapidly dwindling, but some experts opined that improving technology would reduce coal consumption. Jevons argued that this view was incorrect, as further increases in efficiency would tend to increase the use of coal. Hence, improving technology would tend to increase the rate at which England's coal deposits were being depleted, and could not be relied upon to solve the problem.


title: Jevons paradox

text: The Jevons' effect is perhaps the most widely known pitfall in environmental economics. Although Jevons originally focused on the issue of coal, the concept has since been extended to the use of any resource, including, for example, water usage and interpersonal contact. Although the concept of rebound effect was developed from the original theory by Jevons, the contemporary economics have traversed, to expand the scope of what is meant by rebound effects and to provide Jevons' effect a more concise definition. The concept of rebound effects has taken various iterations in different disciplines and has come to encompass several spheres of challenges and negative externalities. Walnum et al. carried out a systematic study of rebound effect research and observed the presence of seven viewpoints in which each provides unique interpretations and suppositions on the phenomenon: psychological study, ecological economics, energy economics, ecological economics, socio-technological discipline, evolutionary economics and urban planning. An eighth important position, that of industrial ecology, was also identified in further studies. The expansion of slavery in the United States following the invention of the cotton gin has also been cited as an example of the effect. The Jevons' effect is also found in socio-hydrology, in the safe development paradox called the "reservoir effect", where construction of a reservoir to reduce the risk of water shortage can instead exacerbate that risk, as increased water availability leads to more development and hence more water consumption.


title: Jevons paradox

text: Economists have observed that consumers tend to travel more when their cars are more fuel efficient, causing a 'rebound' in the demand for fuel. An increase in the efficiency with which a resource (e.g. fuel) is used causes a decrease in the cost of using that resource when measured in terms of what it can achieve (e.g. travel). Generally speaking, a decrease in the cost (or price) of a good or service will increase the quantity demanded (the law of demand). With a lower cost for travel, consumers will travel more, increasing the demand for fuel. This increase in demand is known as the rebound effect, and it may or may not be large enough to offset the original drop in fuel use from the increased efficiency. The Jevons' effect occurs when the rebound effect is greater than 100%, exceeding the original efficiency gains.


title: Jevons paradox

text: The size of the direct rebound effect is dependent on the price elasticity of demand for the good. In a perfectly competitive market where fuel is the sole input used, if the price of fuel remains constant but efficiency is doubled, the effective price of travel would be halved (twice as much travel can be purchased). If in response, the amount of travel purchased more than doubles (i.e. demand is price elastic), then fuel consumption would increase, and the Jevons' effect would occur. If demand is price inelastic, the amount of travel purchased would less than double, and fuel consumption would decrease. However, goods and services generally use more than one type of input (e.g. fuel, labour, machinery), and other factors besides input cost may also affect price. These factors tend to reduce the rebound effect, making the Jevons' effect less likely to occur.


title: Jevons paradox

text: In the 1980s, economists Daniel Khazzoom and Leonard Brookes revisited the Jevons' effect for the case of society's energy use. Brookes, then chief economist at the UK Atomic Energy Authority, argued that attempts to reduce energy consumption by increasing energy efficiency would simply raise demand for energy in the economy as a whole. Khazzoom focused on the narrower point that the potential for rebound was ignored in mandatory performance standards for domestic appliances being set by the California Energy Commission.


title: Jevons paradox

text: In 1992, the economist Harry Saunders dubbed the hypothesis that improvements in energy efficiency work to increase (rather than decrease) energy consumption the "Khazzoom–Brookes postulate", and argued that the hypothesis is broadly supported by neoclassical growth theory (the mainstream economic theory of capital accumulation, technological progress and long-run economic growth). Saunders showed that the Khazzoom–Brookes postulate occurs in the neoclassical growth model under a wide range of assumptions.


title: Jevons paradox

text: According to Saunders, increased energy efficiency tends to increase energy consumption by two means. First, increased energy efficiency makes the use of energy relatively cheaper, thus encouraging increased use (the direct rebound effect). Second, increased energy efficiency increases real incomes and leads to increased economic growth, which pulls up energy use for the whole economy. At the microeconomic level (looking at an individual market), even with the rebound effect, improvements in energy efficiency usually result in reduced energy consumption. That is, the rebound effect is usually less than 100%. However, at the macroeconomic level, more efficient (and hence comparatively cheaper) energy leads to faster economic growth, which increases energy use throughout the economy. Saunders argued that taking into account both microeconomic and macroeconomic effects, the technological progress that improves energy efficiency will tend to increase overall energy use. Besides the neoclassical interpretation, hypotheses generated from heterodox economics also are consistent with the existence of the Jevons effect.


title: Jevons paradox

text: Jevons warned that fuel efficiency gains tend to increase fuel use. However, this does not imply that improved fuel efficiency is worthless if the Jevons' effect occurs; higher fuel efficiency enables greater production and a higher material quality of life. For example, a more efficient steam engine allowed the cheaper transport of goods and people that contributed to the Industrial Revolution. Nonetheless, if the Khazzoom–Brookes postulate is correct, increased fuel efficiency, by itself, will not reduce the rate of depletion of fossil fuels.


title: Jevons paradox

text: There is considerable debate about whether the Khazzoom-Brookes Postulate is correct, and of the relevance of the Jevons' effect to energy conservation policy. Most governments, environmentalists and NGOs pursue policies that improve efficiency, holding that these policies will lower resource consumption and reduce environmental problems. Others, including many environmental economists, doubt this 'efficiency strategy' towards sustainability, and worry that efficiency gains may in fact lead to higher production and consumption. They hold that for resource use to fall, efficiency gains should be coupled with other policies that limit resource use. However, other environmental economists point out that, while the Jevons' effect may occur in some situations, the empirical evidence for its widespread applicability is limited.


title: Jevons paradox

text: The Jevons' effect is sometimes used to argue that energy conservation efforts are futile, for example, that more efficient use of oil will lead to increased demand, and will not slow the arrival or the effects of peak oil. This argument is usually presented as a reason not to enact environmental policies or pursue fuel efficiency (e.g. if cars are more efficient, it will simply lead to more driving). Several points have been raised against this argument. First, in the context of a mature market such as for oil in developed countries, the direct rebound effect is usually small, and so increased fuel efficiency usually reduces resource use, other conditions remaining constant. Second, even if increased efficiency does not reduce the total amount of fuel used, there remain other benefits associated with improved efficiency. For example, increased fuel efficiency may mitigate the price increases, shortages and disruptions in the global economy associated with peak oil. Third, environmental economists have pointed out that fuel use will unambiguously decrease if increased efficiency is coupled with an intervention (e.g. a fuel tax) that keeps the cost of fuel use the same or higher.


title: Jevons paradox

text: The Jevons' effect indicates that increased efficiency by itself may not reduce fuel use, and that sustainable energy policy must rely on other types of government interventions as well. As the imposition of conservation standards or other government interventions that increase cost-of-use do not display the Jevons' effect, they can be used to control the rebound effect. To ensure that efficiency-enhancing technological improvements reduce fuel use, efficiency gains can be paired with government intervention that reduces demand (e.g. green taxes, cap and trade, or higher emissions standards). The ecological economists Mathis Wackernagel and William Rees have suggested that any cost savings from efficiency gains be "taxed away or otherwise removed from further economic circulation. Preferably they should be captured for reinvestment in natural capital rehabilitation." By mitigating the economic effects of government interventions designed to promote ecologically sustainable activities, efficiency-improving technological progress may make the imposition of these interventions more palatable, and more likely to be implemented.


title: Jevons paradox

text: Reducing the price of food can increase consumption, regardless of whether the change applies to cheap or expensive (often calorie-dense) foods. This additional consumption can manifest as overeating. Making food cheaper is often suggested as a way to make people less poor. However, it can have the adverse effect of promoting obesity, which comes with an economic cost.


title: Jevons paradox

text: In the United States of America, in 2012, less than 10% of income was spent on food, compared to 14% in 1984. Obesity from 1984 onwards to 2014 increased for all demographic groups. From 1974 to 2012, sugary foods became more available than ever before, with food consumption outside of one's home becoming more and more common.


title: Jevons paradox

text: Reducing the cost of production of meat, or dairy, may cause a problem, and increase overall consumption in countries where consumption is low at least so far and availability is relatively low as well. Increasing the efficiency of crop farming may increase pressure to deforest even more land for such production as well. Overall it would be an ecological loss.


title: Jevons paradox

text: Reducing prices per GB of 5G compared to 4G, they also have a lower cost in electricity per unit of data, but the rebound effect threatens to turn it against a reduction of consumption and instead create an increase of consumption.


title: Jevons paradox

text: Economic development may mitigate population growth rates, tending to lower reproductive rates by channeling women into the workplace, but it leads to an increase in energy use, as more cars are used, more electricity is generated, and more greenhouse emissions are sent into the atmosphere. Richard Heinberg wrote that China since the 1990s lifted hundreds of millions of its inhabitants out of poverty but in the process became the world's biggest producer and consumer of coal.


title: A Man Named Scott

text: A Man Named Scott is a 2021 documentary film centered on American musician and actor Kid Cudi, directed by Robert Alexander. It was released on Amazon Prime Video on November 5, 2021. The title of the film, which is reminiscent of Cudi's 2008 breakout mixtape "A Kid Named Cudi", is borrowed from his scrapped 2011 mixtape of the same name.


title: A Man Named Scott

text: The film follows the career of Kid Cudi (born Scott Mescudi), beginning with the release of his influential 2009 debut album "", which featured songs that dealt with depression, anxiety and loneliness. The film explores his creative process over the past decade, as well as his struggles and breakthroughs.


title: A Man Named Scott

text: The promotional trailer for the film was released on October 26, 2021. The film was released on Prime Video on November 5, 2021.


title: A Man Named Scott

text: Chris Azzopardi of "The New York Times" wrote, "This film about Kid Cudi is that rare musician-focused documentary, one as sensitive, fully formed and noble in its intentions as the artist himself." Jude Dry of "IndieWire" wrote that the film "rightfully highlights Cudi's contribution to culture as an emotional truth teller," but added that it "lacks the artistic vision of Cudi's musical talents, despite its best efforts." Lovia Gyarkye of "The Hollywood Reporter" commented on how the film's ending would “start to feel like forced attempts at profundity, as if Cudi's testimony alone hasn't always been enough.”


title: Speech recognition

text: Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers with the main benefit of searchability. It is also known as automatic speech recognition (ASR), computer speech recognition or speech to text (STT). It incorporates knowledge and research in the computer science, linguistics and computer engineering fields. The reverse process is speech synthesis.


title: Speech recognition

text: Some speech recognition systems require "training" (also called "enrollment") where an individual speaker reads text or isolated vocabulary into the system. The system analyzes the person's specific voice and uses it to fine-tune the recognition of that person's speech, resulting in increased accuracy. Systems that do not use training are called "speaker-independent" systems. Systems that use training are called "speaker dependent".


title: Speech recognition

text: Speech recognition applications include voice user interfaces such as voice dialing (e.g. "call home"), call routing (e.g. "I would like to make a collect call"), domotic appliance control, search key words (e.g. find a podcast where particular words were spoken), simple data entry (e.g., entering a credit card number), preparation of structured documents (e.g. a radiology report), determining speaker characteristics, speech-to-text processing (e.g., word processors or emails), and aircraft (usually termed direct voice input).


title: Speech recognition

text: The term "voice recognition" or "speaker identification" refers to identifying the speaker, rather than what they are saying. Recognizing the speaker can simplify the task of translating speech in systems that have been trained on a specific person's voice or it can be used to authenticate or verify the identity of a speaker as part of a security process.


title: Speech recognition

text: From the technology perspective, speech recognition has a long history with several waves of major innovations. Most recently, the field has benefited from advances in deep learning and big data. The advances are evidenced not only by the surge of academic papers published in the field, but more importantly by the worldwide industry adoption of a variety of deep learning methods in designing and deploying speech recognition systems.


title: Speech recognition

text: Raj Reddy was the first person to take on continuous speech recognition as a graduate student at Stanford University in the late 1960s. Previous systems required users to pause after each word. Reddy's system issued spoken commands for playing chess.


title: Speech recognition

text: Around this time Soviet researchers invented the dynamic time warping (DTW) algorithm and used it to create a recognizer capable of operating on a 200-word vocabulary. DTW processed speech by dividing it into short frames, e.g. 10ms segments, and processing each frame as a single unit. Although DTW would be superseded by later algorithms, the technique carried on. Achieving speaker independence remained unsolved at this time period.


title: Speech recognition

text: During the late 1960s Leonard Baum developed the mathematics of Markov chains at the Institute for Defense Analysis. A decade later, at CMU, Raj Reddy's students James Baker and Janet M. Baker began using the Hidden Markov Model (HMM) for speech recognition. James Baker had learned about HMMs from a summer job at the Institute of Defense Analysis during his undergraduate education. The use of HMMs allowed researchers to combine different sources of knowledge, such as acoustics, language, and syntax, in a unified probabilistic model.


title: Speech recognition

text: Much of the progress in the field is owed to the rapidly increasing capabilities of computers. At the end of the DARPA program in 1976, the best computer available to researchers was the PDP-10 with 4 MB ram. It could take up to 100 minutes to decode just 30 seconds of speech.


title: Speech recognition

text: By this point, the vocabulary of the typical commercial speech recognition system was larger than the average human vocabulary. Raj Reddy's former student, Xuedong Huang, developed the Sphinx-II system at CMU. The Sphinx-II system was the first to do speaker-independent, large vocabulary, continuous speech recognition and it had the best performance in DARPA's 1992 evaluation. Handling continuous speech with a large vocabulary was a major milestone in the history of speech recognition. Huang went on to found the speech recognition group at Microsoft in 1993. Raj Reddy's student Kai-Fu Lee joined Apple where, in 1992, he helped develop a speech interface prototype for the Apple computer known as Casper.


title: Speech recognition

text: Lernout & Hauspie, a Belgium-based speech recognition company, acquired several other companies, including Kurzweil Applied Intelligence in 1997 and Dragon Systems in 2000. The L&H speech technology was used in the Windows XP operating system. L&H was an industry leader until an accounting scandal brought an end to the company in 2001. The speech technology from L&H was bought by ScanSoft which became Nuance in 2005. Apple originally licensed software from Nuance to provide speech recognition capability to its digital assistant Siri.


title: Speech recognition

text: In the 2000s DARPA sponsored two speech recognition programs: Effective Affordable Reusable Speech-to-Text (EARS) in 2002 and Global Autonomous Language Exploitation (GALE). Four teams participated in the EARS program: IBM, a team led by BBN with LIMSI and Univ. of Pittsburgh, Cambridge University, and a team composed of ICSI, SRI and University of Washington. EARS funded the collection of the Switchboard telephone speech corpus containing 260 hours of recorded conversations from over 500 speakers. The GALE program focused on Arabic and Mandarin broadcast news speech. Google's first effort at speech recognition came in 2007 after hiring some researchers from Nuance. The first product was GOOG-411, a telephone based directory service. The recordings from GOOG-411 produced valuable data that helped Google improve their recognition systems. Google Voice Search is now supported in over 30 languages.


title: Speech recognition

text: In the United States, the National Security Agency has made use of a type of speech recognition for keyword spotting since at least 2006. This technology allows analysts to search through large volumes of recorded conversations and isolate mentions of keywords. Recordings can be indexed and analysts can run queries over the database to find conversations of interest. Some government research programs focused on intelligence applications of speech recognition, e.g. DARPA's EARS's program and IARPA's Babel program.


title: Speech recognition

text: In the early 2000s, speech recognition was still dominated by traditional approaches such as Hidden Markov Models combined with feedforward artificial neural networks.


title: Speech recognition

text: Today, however, many aspects of speech recognition have been taken over by a deep learning method called Long short-term memory (LSTM), a recurrent neural network published by Sepp Hochreiter & Jürgen Schmidhuber in 1997. LSTM RNNs avoid the vanishing gradient problem and can learn "Very Deep Learning" tasks that require memories of events that happened thousands of discrete time steps ago, which is important for speech.


title: Speech recognition

text: Around 2007, LSTM trained by Connectionist Temporal Classification (CTC) started to outperform traditional speech recognition in certain applications. In 2015, Google's speech recognition reportedly experienced a dramatic performance jump of 49% through CTC-trained LSTM, which is now available through Google Voice to all smartphone users.


title: Speech recognition

text: The use of deep feedforward (non-recurrent) networks for acoustic modeling was introduced during the later part of 2009 by Geoffrey Hinton and his students at the University of Toronto and by Li Deng and colleagues at Microsoft Research, initially in the collaborative work between Microsoft and the University of Toronto which was subsequently expanded to include IBM and Google (hence "The shared views of four research groups" subtitle in their 2012 review paper). A Microsoft research executive called this innovation "the most dramatic change in accuracy since 1979". In contrast to the steady incremental improvements of the past few decades, the application of deep learning decreased word error rate by 30%. This innovation was quickly adopted across the field. Researchers have begun to use deep learning techniques for language modeling as well.


title: Speech recognition

text: In the long history of speech recognition, both shallow form and deep form (e.g. recurrent nets) of artificial neural networks had been explored for many years during 1980s, 1990s and a few years into the 2000s.


title: Speech recognition

text: But these methods never won over the non-uniform internal-handcrafting Gaussian mixture model/Hidden Markov model (GMM-HMM) technology based on generative models of speech trained discriminatively. A number of key difficulties had been methodologically analyzed in the 1990s, including gradient diminishing and weak temporal correlation structure in the neural predictive models. All these difficulties were in addition to the lack of big training data and big computing power in these early days. Most speech recognition researchers who understood such barriers hence subsequently moved away from neural nets to pursue generative modeling approaches until the recent resurgence of deep learning starting around 2009–2010 that had overcome all these difficulties. Hinton et al. and Deng et al. reviewed part of this recent history about how their collaboration with each other and then with colleagues across four groups (University of Toronto, Microsoft, Google, and IBM) ignited a renaissance of applications of deep feedforward neural networks to speech recognition.


title: Speech recognition

text: By early 2010s "speech" recognition, also called voice recognition was clearly differentiated from "speaker" recognition, and speaker independence was considered a major breakthrough. Until then, systems required a "training" period. A 1987 ad for a doll had carried the tagline "Finally, the doll that understands you." – despite the fact that it was described as "which children could train to respond to their voice".


title: Speech recognition

text: In 2017, Microsoft researchers reached a historical human parity milestone of transcribing conversational telephony speech on the widely benchmarked Switchboard task. Multiple deep learning models were used to optimize speech recognition accuracy. The speech recognition word error rate was reported to be as low as 4 professional human transcribers working together on the same benchmark, which was funded by IBM Watson speech team on the same task.


title: Speech recognition

text: Both acoustic modeling and language modeling are important parts of modern statistically based speech recognition algorithms. Hidden Markov models (HMMs) are widely used in many systems. Language modeling is also used in many other natural language processing applications such as document classification or statistical machine translation.


title: Speech recognition

text: Modern general-purpose speech recognition systems are based on hidden Markov models. These are statistical models that output a sequence of symbols or quantities. HMMs are used in speech recognition because a speech signal can be viewed as a piecewise stationary signal or a short-time stationary signal. In a short time scale (e.g., 10 milliseconds), speech can be approximated as a stationary process. Speech can be thought of as a Markov model for many stochastic purposes.


title: Speech recognition

text: Another reason why HMMs are popular is that they can be trained automatically and are simple and computationally feasible to use. In speech recognition, the hidden Markov model would output a sequence of "n"-dimensional real-valued vectors (with "n" being a small integer, such as 10), outputting one of these every 10 milliseconds. The vectors would consist of cepstral coefficients, which are obtained by taking a Fourier transform of a short time window of speech and decorrelating the spectrum using a cosine transform, then taking the first (most significant) coefficients. The hidden Markov model will tend to have in each state a statistical distribution that is a mixture of diagonal covariance Gaussians, which will give a likelihood for each observed vector. Each word, or (for more general speech recognition systems), each phoneme, will have a different output distribution; a hidden Markov model for a sequence of words or phonemes is made by concatenating the individual trained hidden Markov models for the separate words and phonemes.


title: Speech recognition

text: Described above are the core elements of the most common, HMM-based approach to speech recognition. Modern speech recognition systems use various combinations of a number of standard techniques in order to improve results over the basic approach described above. A typical large-vocabulary system would need context dependency for the phonemes (so phonemes with different left and right context have different realizations as HMM states); it would use cepstral normalization to normalize for a different speaker and recording conditions; for further speaker normalization, it might use vocal tract length normalization (VTLN) for male-female normalization and maximum likelihood linear regression (MLLR) for more general speaker adaptation. The features would have so-called delta and delta-delta coefficients to capture speech dynamics and in addition, might use heteroscedastic linear discriminant analysis (HLDA); or might skip the delta and delta-delta coefficients and use splicing and an LDA-based projection followed perhaps by heteroscedastic linear discriminant analysis or a global semi-tied co variance transform (also known as maximum likelihood linear transform, or MLLT). Many systems use so-called discriminative training techniques that dispense with a purely statistical approach to HMM parameter estimation and instead optimize some classification-related measure of the training data. Examples are maximum mutual information (MMI), minimum classification error (MCE), and minimum phone error (MPE).


title: Speech recognition

text: Decoding of the speech (the term for what happens when the system is presented with a new utterance and must compute the most likely source sentence) would probably use the Viterbi algorithm to find the best path, and here there is a choice between dynamically creating a combination hidden Markov model, which includes both the acoustic and language model information and combining it statically beforehand (the finite state transducer, or FST, approach).


title: Speech recognition

text: A possible improvement to decoding is to keep a set of good candidates instead of just keeping the best candidate, and to use a better scoring function (re scoring) to rate these good candidates so that we may pick the best one according to this refined score. The set of candidates can be kept either as a list (the N-best list approach) or as a subset of the models (a lattice). Re scoring is usually done by trying to minimize the Bayes risk (or an approximation thereof): Instead of taking the source sentence with maximal probability, we try to take the sentence that minimizes the expectancy of a given loss function with regards to all possible transcriptions (i.e., we take the sentence that minimizes the average distance to other possible sentences weighted by their estimated probability). The loss function is usually the Levenshtein distance, though it can be different distances for specific tasks; the set of possible transcriptions is, of course, pruned to maintain tractability. Efficient algorithms have been devised to re score lattices represented as weighted finite state transducers with edit distances represented themselves as a finite state transducer verifying certain assumptions.


title: Speech recognition

text: Dynamic time warping is an approach that was historically used for speech recognition but has now largely been displaced by the more successful HMM-based approach.


title: Speech recognition

text: Dynamic time warping is an algorithm for measuring similarity between two sequences that may vary in time or speed. For instance, similarities in walking patterns would be detected, even if in one video the person was walking slowly and if in another he or she were walking more quickly, or even if there were accelerations and deceleration during the course of one observation. DTW has been applied to video, audio, and graphics – indeed, any data that can be turned into a linear representation can be analyzed with DTW.


title: Speech recognition

text: A well-known application has been automatic speech recognition, to cope with different speaking speeds. In general, it is a method that allows a computer to find an optimal match between two given sequences (e.g., time series) with certain restrictions. That is, the sequences are "warped" non-linearly to match each other. This sequence alignment method is often used in the context of hidden Markov models.


title: Speech recognition

text: Neural networks emerged as an attractive acoustic modeling approach in ASR in the late 1980s. Since then, neural networks have been used in many aspects of speech recognition such as phoneme classification, phoneme classification through multi-objective evolutionary algorithms, isolated word recognition, audiovisual speech recognition, audiovisual speaker recognition and speaker adaptation.


title: Speech recognition

text: Neural networks make fewer explicit assumptions about feature statistical properties than HMMs and have several qualities making them attractive recognition models for speech recognition. When used to estimate the probabilities of a speech feature segment, neural networks allow discriminative training in a natural and efficient manner. However, in spite of their effectiveness in classifying short-time units such as individual phonemes and isolated words, early neural networks were rarely successful for continuous recognition tasks because of their limited ability to model temporal dependencies.


title: Speech recognition

text: One approach to this limitation was to use neural networks as a pre-processing, feature transformation or dimensionality reduction, step prior to HMM based recognition. However, more recently, LSTM and related recurrent neural networks (RNNs) and Time Delay Neural Networks(TDNN's) have demonstrated improved performance in this area.


title: Speech recognition

text: Deep Neural Networks and Denoising Autoencoders are also under investigation. A deep feedforward neural network (DNN) is an artificial neural network with multiple hidden layers of units between the input and output layers. Similar to shallow neural networks, DNNs can model complex non-linear relationships. DNN architectures generate compositional models, where extra layers enable composition of features from lower layers, giving a huge learning capacity and thus the potential of modeling complex patterns of speech data.


title: Speech recognition

text: A success of DNNs in large vocabulary speech recognition occurred in 2010 by industrial researchers, in collaboration with academic researchers, where large output layers of the DNN based on context dependent HMM states constructed by decision trees were adopted.


title: Speech recognition

text: One fundamental principle of deep learning is to do away with hand-crafted feature engineering and to use raw features. This principle was first explored successfully in the architecture of deep autoencoder on the "raw" spectrogram or linear filter-bank features, showing its superiority over the Mel-Cepstral features which contain a few stages of fixed transformation from spectrograms.


title: Speech recognition

text: The true "raw" features of speech, waveforms, have more recently been shown to produce excellent larger-scale speech recognition results.


title: Speech recognition

text: Since 2014, there has been much research interest in "end-to-end" ASR. Traditional phonetic-based (i.e., all HMM-based model) approaches required separate components and training for the pronunciation, acoustic, and language model. End-to-end models jointly learn all the components of the speech recognizer. This is valuable since it simplifies the training process and deployment process. For example, a n-gram language model is required for all HMM-based systems, and a typical n-gram language model often takes several gigabytes in memory making them impractical to deploy on mobile devices. Consequently, modern commercial ASR systems from Google and Apple () are deployed on the cloud and require a network connection as opposed to the device locally.


title: Speech recognition

text: The first attempt at end-to-end ASR was with Connectionist Temporal Classification (CTC)-based systems introduced by Alex Graves of Google DeepMind and Navdeep Jaitly of the University of Toronto in 2014. The model consisted of recurrent neural networks and a CTC layer. Jointly, the RNN-CTC model learns the pronunciation and acoustic model together, however it is incapable of learning the language due to conditional independence assumptions similar to a HMM. Consequently, CTC models can directly learn to map speech acoustics to English characters, but the models make many common spelling mistakes and must rely on a separate language model to clean up the transcripts. Later, Baidu expanded on the work with extremely large datasets and demonstrated some commercial success in Chinese Mandarin and English. In 2016, University of Oxford presented LipNet, the first end-to-end sentence-level lipreading model, using spatiotemporal convolutions coupled with an RNN-CTC architecture, surpassing human-level performance in a restricted grammar dataset. A large-scale CNN-RNN-CTC architecture was presented in 2018 by Google DeepMind achieving 6 times better performance than human experts.


title: Speech recognition

text: An alternative approach to CTC-based models are attention-based models. Attention-based ASR models were introduced simultaneously by Chan et al. of Carnegie Mellon University and Google Brain and Bahdanau et al. of the University of Montreal in 2016. The model named "Listen, Attend and Spell" (LAS), literally "listens" to the acoustic signal, pays "attention" to different parts of the signal and "spells" out the transcript one character at a time. Unlike CTC-based models, attention-based models do not have conditional-independence assumptions and can learn all the components of a speech recognizer including the pronunciation, acoustic and language model directly. This means, during deployment, there is no need to carry around a language model making it very practical for applications with limited memory. By the end of 2016, the attention-based models have seen considerable success including outperforming the CTC models (with or without an external language model). Various extensions have been proposed since the original LAS model. Latent Sequence Decompositions (LSD) was proposed by Carnegie Mellon University, MIT and Google Brain to directly emit sub-word units which are more natural than English characters; University of Oxford and Google DeepMind extended LAS to "Watch, Listen, Attend and Spell" (WLAS) to handle lip reading surpassing human-level performance.


title: Speech recognition

text: Typically a manual control input, for example by means of a finger control on the steering-wheel, enables the speech recognition system and this is signaled to the driver by an audio prompt. Following the audio prompt, the system has a "listening window" during which it may accept a speech input for recognition.


title: Speech recognition

text: Simple voice commands may be used to initiate phone calls, select radio stations or play music from a compatible smartphone, MP3 player or music-loaded flash drive. Voice recognition capabilities vary between car make and model. Some of the most recent car models offer natural-language speech recognition in place of a fixed set of commands, allowing the driver to use full sentences and common phrases. With such systems there is, therefore, no need for the user to memorize a set of fixed command words.


title: Speech recognition

text: In the health care sector, speech recognition can be implemented in front-end or back-end of the medical documentation process. Front-end speech recognition is where the provider dictates into a speech-recognition engine, the recognized words are displayed as they are spoken, and the dictator is responsible for editing and signing off on the document. Back-end or deferred speech recognition is where the provider dictates into a digital dictation system, the voice is routed through a speech-recognition machine and the recognized draft document is routed along with the original voice file to the editor, where the draft is edited and report finalized. Deferred speech recognition is widely used in the industry currently.


title: Speech recognition

text: One of the major issues relating to the use of speech recognition in healthcare is that the American Recovery and Reinvestment Act of 2009 (ARRA) provides for substantial financial benefits to physicians who utilize an EMR according to "Meaningful Use" standards. These standards require that a substantial amount of data be maintained by the EMR (now more commonly referred to as an Electronic Health Record or EHR). The use of speech recognition is more naturally suited to the generation of narrative text, as part of a radiology/pathology interpretation, progress note or discharge summary: the ergonomic gains of using speech recognition to enter structured discrete data (e.g., numeric values or codes from a list or a controlled vocabulary) are relatively minimal for people who are sighted and who can operate a keyboard and mouse.


title: Speech recognition

text: A more significant issue is that most EHRs have not been expressly tailored to take advantage of voice-recognition capabilities. A large part of the clinician's interaction with the EHR involves navigation through the user interface using menus, and tab/button clicks, and is heavily dependent on keyboard and mouse: voice-based navigation provides only modest ergonomic benefits. By contrast, many highly customized systems for radiology or pathology dictation implement voice "macros", where the use of certain phrases – e.g., "normal report", will automatically fill in a large number of default values and/or generate boilerplate, which will vary with the type of the exam – e.g., a chest X-ray vs. a gastrointestinal contrast series for a radiology system.


title: Speech recognition

text: Prolonged use of speech recognition software in conjunction with word processors has shown benefits to short-term-memory restrengthening in brain AVM patients who have been treated with resection. Further research needs to be conducted to determine cognitive benefits for individuals whose AVMs have been treated using radiologic techniques.


title: Speech recognition

text: Substantial efforts have been devoted in the last decade to the test and evaluation of speech recognition in fighter aircraft. Of particular note have been the US program in speech recognition for the Advanced Fighter Technology Integration (AFTI)/F-16 aircraft (F-16 VISTA), the program in France for Mirage aircraft, and other programs in the UK dealing with a variety of aircraft platforms. In these programs, speech recognizers have been operated successfully in fighter aircraft, with applications including setting radio frequencies, commanding an autopilot system, setting steer-point coordinates and weapons release parameters, and controlling flight display.


title: Speech recognition

text: Working with Swedish pilots flying in the JAS-39 Gripen cockpit, Englund (2004) found recognition deteriorated with increasing g-loads. The report also concluded that adaptation greatly improved the results in all cases and that the introduction of models for breathing was shown to improve recognition scores significantly. Contrary to what might have been expected, no effects of the broken English of the speakers were found. It was evident that spontaneous speech caused problems for the recognizer, as might have been expected. A restricted vocabulary, and above all, a proper syntax, could thus be expected to improve recognition accuracy substantially.


title: Speech recognition

text: The Eurofighter Typhoon, currently in service with the UK RAF, employs a speaker-dependent system, requiring each pilot to create a template. The system is not used for any safety-critical or weapon-critical tasks, such as weapon release or lowering of the undercarriage, but is used for a wide range of other cockpit functions. Voice commands are confirmed by visual and/or aural feedback. The system is seen as a major design feature in the reduction of pilot workload, and even allows the pilot to assign targets to his aircraft with two simple voice commands or to any of his wingmen with only five commands.


title: Speech recognition

text: Speaker-independent systems are also being developed and are under test for the F35 Lightning II (JSF) and the Alenia Aermacchi M-346 Master lead-in fighter trainer. These systems have produced word accuracy scores in excess of 98%.


title: Speech recognition

text: The problems of achieving high recognition accuracy under stress and noise are particularly relevant in the helicopter environment as well as in the jet fighter environment. The acoustic noise problem is actually more severe in the helicopter environment, not only because of the high noise levels but also because the helicopter pilot, in general, does not wear a facemask, which would reduce acoustic noise in the microphone. Substantial test and evaluation programs have been carried out in the past decade in speech recognition systems applications in helicopters, notably by the U.S. Army Avionics Research and Development Activity (AVRADA) and by the Royal Aerospace Establishment (RAE) in the UK. Work in France has included speech recognition in the Puma helicopter. There has also been much useful work in Canada. Results have been encouraging, and voice applications have included: control of communication radios, setting of navigation systems, and control of an automated target handover system.


title: Speech recognition

text: As in fighter applications, the overriding issue for voice in helicopters is the impact on pilot effectiveness. Encouraging results are reported for the AVRADA tests, although these represent only a feasibility demonstration in a test environment. Much remains to be done both in speech recognition and in overall speech technology in order to consistently achieve performance improvements in operational settings.


title: Speech recognition

text: Training for air traffic controllers (ATC) represents an excellent application for speech recognition systems. Many ATC training systems currently require a person to act as a "pseudo-pilot", engaging in a voice dialog with the trainee controller, which simulates the dialog that the controller would have to conduct with pilots in a real ATC situation. Speech recognition and synthesis techniques offer the potential to eliminate the need for a person to act as a pseudo-pilot, thus reducing training and support personnel. In theory, Air controller tasks are also characterized by highly structured speech as the primary output of the controller, hence reducing the difficulty of the speech recognition task should be possible. In practice, this is rarely the case. The FAA document 7110.65 details the phrases that should be used by air traffic controllers. While this document gives less than 150 examples of such phrases, the number of phrases supported by one of the simulation vendors speech recognition systems is in excess of 500,000.


title: Speech recognition

text: The USAF, USMC, US Army, US Navy, and FAA as well as a number of international ATC training organizations such as the Royal Australian Air Force and Civil Aviation Authorities in Italy, Brazil, and Canada are currently using ATC simulators with speech recognition from a number of different vendors.


title: Speech recognition

text: ASR is now commonplace in the field of telephony and is becoming more widespread in the field of computer gaming and simulation. In telephony systems, ASR is now being predominantly used in contact centers by integrating it with IVR systems. Despite the high level of integration with word processing in general personal computing, in the field of document production, ASR has not seen the expected increases in use.


title: Speech recognition

text: The improvement of mobile processor speeds has made speech recognition practical in smartphones. Speech is used mostly as a part of a user interface, for creating predefined or custom speech commands.


title: Speech recognition

text: For language learning, speech recognition can be useful for learning a second language. It can teach proper pronunciation, in addition to helping a person develop fluency with their speaking skills.


title: Speech recognition

text: Students who are blind (see Blindness and education) or have very low vision can benefit from using the technology to convey words and then hear the computer recite them, as well as use a computer by commanding with their voice, instead of having to look at the screen and keyboard.


title: Speech recognition

text: Students who are physically disabled , have a Repetitive strain injury/other injuries to the upper extremities can be relieved from having to worry about handwriting, typing, or working with scribe on school assignments by using speech-to-text programs. They can also utilize speech recognition technology to enjoy searching the Internet or using a computer at home without having to physically operate a mouse and keyboard.


title: Speech recognition

text: Speech recognition can allow students with learning disabilities to become better writers. By saying the words aloud, they can increase the fluidity of their writing, and be alleviated of concerns regarding spelling, punctuation, and other mechanics of writing. Also, see Learning disability.


title: Speech recognition

text: The use of voice recognition software, in conjunction with a digital audio recorder and a personal computer running word-processing software has proven to be positive for restoring damaged short-term memory capacity, in stroke and craniotomy individuals.


title: Speech recognition

text: People with disabilities can benefit from speech recognition programs. For individuals that are Deaf or Hard of Hearing, speech recognition software is used to automatically generate a closed-captioning of conversations such as discussions in conference rooms, classroom lectures, and/or religious services.


title: Speech recognition

text: Speech recognition is also very useful for people who have difficulty using their hands, ranging from mild repetitive stress injuries to involve disabilities that preclude using conventional computer input devices. In fact, people who used the keyboard a lot and developed RSI became an urgent early market for speech recognition. Speech recognition is used in deaf telephony, such as voicemail to text, relay services, and captioned telephone. Individuals with learning disabilities who have problems with thought-to-paper communication (essentially they think of an idea but it is processed incorrectly causing it to end up differently on paper) can possibly benefit from the software but the technology is not bug proof. Also the whole idea of speak to text can be hard for intellectually disabled person's due to the fact that it is rare that anyone tries to learn the technology to teach the person with the disability.


title: Speech recognition

text: This type of technology can help those with dyslexia but other disabilities are still in question. The effectiveness of the product is the problem that is hindering it from being effective. Although a kid may be able to say a word depending on how clear they say it the technology may think they are saying another word and input the wrong one. Giving them more work to fix, causing them to have to take more time with fixing the wrong word.


title: Speech recognition

text: The performance of speech recognition systems is usually evaluated in terms of accuracy and speed. Accuracy is usually rated with word error rate (WER), whereas speed is measured with the real time factor. Other measures of accuracy include Single Word Error Rate (SWER) and Command Success Rate (CSR).


title: Speech recognition

text: Speech recognition by machine is a very complex problem, however. Vocalizations vary in terms of accent, pronunciation, articulation, roughness, nasality, pitch, volume, and speed. Speech is distorted by a background noise and echoes, electrical characteristics. Accuracy of speech recognition may vary with the following:


title: Speech recognition

text: As mentioned earlier in this article, the accuracy of speech recognition may vary depending on the following factors:


title: Speech recognition

text: With discontinuous speech full sentences separated by silence are used, therefore it becomes easier to recognize the speech as well as with isolated speech.


title: Speech recognition

text: With continuous speech naturally spoken sentences are used, therefore it becomes harder to recognize the speech, different from both isolated and discontinuous speech.


title: Speech recognition

text: e.g. Known word pronunciations or legal word sequences, which can compensate for errors or uncertainties at a lower level;


title: Speech recognition

text: Analysis of four-step neural network approaches can be explained by further information. Sound is produced by air (or some other medium) vibration, which we register by ears, but machines by receivers. Basic sound creates a wave which has two descriptions: amplitude (how strong is it), and frequency (how often it vibrates per second).


title: Speech recognition

text: Accuracy can be computed with the help of word error rate (WER). Word error rate can be calculated by aligning the recognized word and referenced word using dynamic string alignment. The problem may occur while computing the word error rate due to the difference between the sequence lengths of the recognized word and referenced word.


title: Speech recognition

text: Speech recognition can become a means of attack, theft, or accidental operation. For example, activation words like "Alexa" spoken in an audio or video broadcast can cause devices in homes and offices to start listening for input inappropriately, or possibly take an unwanted action. Voice-controlled devices are also accessible to visitors to the building, or even those outside the building if they can be heard inside. Attackers may be able to gain access to personal information, like calendar, address book contents, private messages, and documents. They may also be able to impersonate the user to send messages or make online purchases.


title: Speech recognition

text: Two attacks have been demonstrated that use artificial sounds. One transmits ultrasound and attempt to send commands without nearby people noticing. The other adds small, inaudible distortions to other speech or music that are specially crafted to confuse the specific speech recognition system into recognizing music as speech, or to make what sounds like one command to a human sound like a different command to the system.


title: Speech recognition

text: Popular speech recognition conferences held each year or two include SpeechTEK and SpeechTEK Europe, ICASSP, Interspeech/Eurospeech, and the IEEE ASRU. Conferences in the field of natural language processing, such as ACL, NAACL, EMNLP, and HLT, are beginning to include papers on speech processing. Important journals include the IEEE Transactions on Speech and Audio Processing (later renamed IEEE Transactions on Audio, Speech and Language Processing and since Sept 2014 renamed IEEE/ACM Transactions on Audio, Speech and Language Processing—after merging with an ACM publication), Computer Speech and Language, and Speech Communication.


title: Speech recognition

text: Books like "Fundamentals of Speech Recognition" by Lawrence Rabiner can be useful to acquire basic knowledge but may not be fully up to date (1993). Another good source can be "Statistical Methods for Speech Recognition" by Frederick Jelinek and "Spoken Language Processing (2001)" by Xuedong Huang etc., "Computer Speech", by Manfred R. Schroeder, second edition published in 2004, and "Speech Processing: A Dynamic and Optimization-Oriented Approach" published in 2003 by Li Deng and Doug O'Shaughnessey. The updated textbook "Speech and Language Processing" (2008) by Jurafsky and Martin presents the basics and the state of the art for ASR. Speaker recognition also uses the same features, most of the same front-end processing, and classification techniques as is done in speech recognition. A comprehensive textbook, "Fundamentals of Speaker Recognition" is an in depth source for up to date details on the theory and practice. A good insight into the techniques used in the best modern systems can be gained by paying attention to government sponsored evaluations such as those organised by DARPA (the largest speech recognition-related project ongoing as of 2007 is the GALE project, which involves both speech recognition and translation components).


title: Speech recognition

text: A good and accessible introduction to speech recognition technology and its history is provided by the general audience book "The Voice in the Machine. Building Computers That Understand Speech" by Roberto Pieraccini (2012).


title: Speech recognition

text: The most recent book on speech recognition is "Automatic Speech Recognition: A Deep Learning Approach" (Publisher: Springer) written by Microsoft researchers D. Yu and L. Deng and published near the end of 2014, with highly mathematically oriented technical detail on how deep learning methods are derived and implemented in modern speech recognition systems based on DNNs and related deep learning methods. A related book, published earlier in 2014, "Deep Learning: Methods and Applications" by L. Deng and D. Yu provides a less technical but more methodology-focused overview of DNN-based speech recognition during 2009–2014, placed within the more general context of deep learning applications including not only speech recognition but also image recognition, natural language processing, information retrieval, multimodal processing, and multitask learning.


title: Speech recognition

text: In terms of freely available resources, Carnegie Mellon University's Sphinx toolkit is one place to start to both learn about speech recognition and to start experimenting. Another resource (free but copyrighted) is the HTK book (and the accompanying HTK toolkit). For more recent and state-of-the-art techniques, Kaldi toolkit can be used. In 2017 Mozilla launched the open source project called Common Voice to gather big database of voices that would help build free speech recognition project DeepSpeech (available free at GitHub), using Google's open source platform TensorFlow. When Mozilla redirected funding away from the project in 2020, it was forked by its original developers as Coqui STT using the same open-source license.


title: Murder of Scott Amedure

text: Scott Bernard Amedure (January 26, 1963 – March 9, 1995) was an American murder victim. During a taping of "The Jenny Jones Show", a television talk show, Amedure revealed that he was attracted to an acquaintance, Jonathan Schmitz (born ). Three days later, Schmitz confronted Amedure and shot him twice in the chest. He confessed to the killing and was found guilty of second-degree murder. The Amedure family successfully sued "The Jenny Jones Show" for wrongful death, but the judgment was subsequently overturned by the Michigan Court of Appeals. The episode was never broadcast, although segments of it were played for television news programs.


title: Murder of Scott Amedure

text: Amendure was born in 1963 in Pittsburgh, Pennsylvania, and grew up in Lake Orion, Michigan. He served in the army, where he came out as gay.


title: Murder of Scott Amedure

text: On March 6, 1995, Amedure videotaped an episode of "The Jenny Jones Show", in which he admitted to being a secret admirer of Jonathan Schmitz, who lived near him in Lake Orion, Michigan. Until the taping, Schmitz did not know who would be revealed as his secret admirer. Schmitz stated that he participated in the show due to curiosity, and he claimed later that the producers implied that his admirer was a woman, although the producers of the show claim that they did tell Schmitz that the admirer could be male or female.


title: Murder of Scott Amedure

text: During the segment, Amedure was encouraged by Jones to share his fantasies about Schmitz, after which Schmitz was brought onstage. According to "The Washington Post", "[t]he two men exchanged an awkward embrace before the host dropped her bombshell." In response to Amedure's disclosure, Schmitz laughed, then stated that he was "definitely heterosexual".


title: Murder of Scott Amedure

text: According to footage of the murder trial, it was stated later by a friend of Amedure's that Amedure and Schmitz went out drinking together the night after the taping and an alleged sexual encounter occurred. According to the testimony at the murder trial, three days after the taping, Amedure left a "suggestive" note at Schmitz's house. After finding the note, Schmitz withdrew money from a bank, purchased a shotgun, and then went to Amedure's mobile home. He then asked Amedure if he was the one that left the note. According to court documents, Amedure responded with a smile. Schmitz then returned to his car, got his gun, and returned to Amedure's trailer. He then shot Amedure twice in the chest, killing him. After killing Amedure, Schmitz left the residence, telephoned 9-1-1, and confessed to the killing.


title: Murder of Scott Amedure

text: At trial, defense attorneys argued that Schmitz, who had been diagnosed with manic depression and Graves' disease, was caused to commit homicide by mental illness and humiliation, by way of the "gay panic defense". Schmitz was found guilty of second-degree murder in 1996 and sentenced to 25–50 years in prison, but his conviction was overturned on appeal. Upon retrial, he was found guilty of the same charge once again and his sentence was reinstated. Schmitz was released from prison on August 22, 2017, after being granted parole.


title: Murder of Scott Amedure

text: In 1999, the Amedure family, retaining Geoffrey Fieger as lawyer, sued "The Jenny Jones Show", Telepictures, and Warner Bros. for the ambush tactics and, as the Amedure family considered it, their negligent actions that resulted in Amedure's death. In May, the jury awarded the Amedures $29,332,686.


title: Murder of Scott Amedure

text: The jury found that "The Jenny Jones Show" was both irresponsible and negligent, contending that the show intentionally created an unpredictable situation without due concern for the possible consequences. Time Warner's defense attorney later claimed the verdict would cause a "chilling effect" on the industry.


title: Murder of Scott Amedure

text: The judgment was later overturned by the Michigan Court of Appeals in a 2-to-1 decision. The Michigan Supreme Court declined to hear the case.


title: Murder of Scott Amedure

text: The podcast "Criminal" included the murder of Scott Amedure and following trial of Jonathan Schmitz in their episode "Panic Defense" about the gay panic defense.


title: Murder of Scott Amedure

text: The Jenny Jones controversy was also covered as the first episode in the Netflix series "Trial by Media".


title: Murder of Scott Amedure

text: In 2021, the controversy was covered in season 6 of the series "How It Really Happened" on the US TV network HLN in an episode titled "The Jenny Jones Show: Fatal Attraction".


title: Jumong (TV series)

text: Jumong (; lit. "The Book of the Three Hans: The Chapter of Jumong") is a South Korean historical series that aired on MBC from 2006 to 2007 as the network's 45th anniversary special. Originally scheduled for 60 episodes, MBC extended it to 81 because of its popularity.


title: Jumong (TV series)

text: The series examines the life of Jumong, founder of the kingdom of Goguryeo. The fantastic elements surrounding the original Jumong legend (such as those concerning his birth) have been replaced with events more grounded in reality. "Jumong" is considered part of the Korean Wave ("Hallyu"), with viewer ratings in Iran exceeding 80 percent.


title: Jumong (TV series)

text: Following the conquest of Gojoseon by Han China in 108 BCE, the surviving tribes and city-states of Manchuria and the northern Korean Peninsula are harshly subjugated as tributaries to the Han, who are portrayed as ruling with an iron fist from the Four Commanderies. Haemosu, the leader of the local resistance in the form of the Damul Army, covertly teams up with Prince Geumwa of Buyeo to defend and rescue Gojoseon refugees throughout the land. After being injured in a battle, Haemosu is rescued by Lady Yuhwa of the Habaek tribe (to whom Geumwa has taken a fancy), and they fall in love. Haemosu is subsequently ambushed and captured by Han forces (and after falling off a cliff is presumed dead by the outside world), and Lady Yuhwa is forced to seek shelter in Buyeo, where she becomes Geumwa's concubine and gives birth to a son, Jumong. They maintain that Geumwa is Jumong's father, when in fact Haemosu is his father.


title: Jumong (TV series)

text: Twenty years later, the young Jumong is a weak and cowardly prince overshadowed and scorned by his elder "half-brothers" Daeso and Youngpo, who are vying for inheritance of the Buyeo throne from their father (the now-King Geumwa). Because they believe Jumong is Geumwa's son, they assume that he has a justifiable claim to the throne, and their mother's hatred of Lady Yuhwa reinforces a feud between the half-brothers who aren't really brothers at all. This culminates in an assassination attempt by his brothers, setting in motion a sequence of events that leads to Jumong leaving the palace and, by a twist of fate, encounters his father, the now-elderly and blind Haemosu. Jumong becomes skilled in combat under Haemosu's covert tutelage, but is unaware of their father-son relationship. At the same time, Jumong forms a close relationship with Lady Soseono of the Gyeru trading clan of Jolbon. Following Haemosu's assassination by Daeso and Youngpo, Jumong learns the truth and vows to avenge his father and drive out the Han. He returns to Geumwa and leads the Buyeo army in a campaign against the Lintun and Zhenfan Commanderies, but is reported missing in action and presumed dead following an injury in battle. Subsequently, Daeso seizes power in Buyeo by colluding with Xuantu Commandery and forces Soseono to be his wife. In desperation, Soseono weds her trading partner Wootae (not knowing Jumong is still alive). Jumong, however, is rescued by the Hanbaek tribe and nursed back to health by Lady Yesoya, whom he weds. They return to Buyeo and Jumong feigns servitude to Daeso, thereby earning his trust. With Daeso's guard down, Jumong and his men manage to intercept and lead a large group of Gojoseon refugees into the wilds of Mount Bongye, where they establish a fortress and re-form the Damul Army, against Daeso's wishes, who holds Lady Yuhwa and a pregnant Yesoya hostage in the palace. After a solar eclipse, Geumwa regains the power with the help of the Prime Minister. He tries to convince Jumong to come back to palace and disband the Damul Army as part of the conditions given by the Prime minister in exchange for his reinstatement. Jumong refuses the offer and the Prime Minister tries to eliminate him and his men.


title: Jumong (TV series)

text: Over the next three years, the Damul Army grows and begins uniting various local tribes, to the discomfort of Buyeo and Han. Following Wootae's death in battle, Jumong and Soseono form an alliance and unite the five clans of Jolbon and the Damul Army into a single powerful entity, which succeeds in conquering the Xuantu Commandery and establishing the Kingdom of Goguryeo. When Yesoya and Yuri are reported missing from Buyeo (and presumed dead), a grieving Jumong weds Soseono and they become King and Queen of the new nation.


title: Jumong (TV series)

text: After ruling Goguryeo for fifteen years, Jumong succeeds in reuniting with Yesoya and Yuri (who had been living in exile after escaping from the palace). Following Geumwa's assassination by Han mercenaries, the newly-crowned King Daeso forms an alliance with Jumong, and the combined armies of Goguryeo and Buyeo succeed in conquering Liaodong Commandery with utter annihilation of the Han army in Manchuria. With Jumong's lifelong mission finally complete and in order to prevent internal strife due to Yuri's return, Soseono departs from Goguryeo and heads south with the pro-Jolbon faction and her teenage sons Biryu and Onjo, who subsequently becomes the founder of the Kingdom of Baekje on the Korean Peninsula. Buyeo eventually collapses following the battlefield death of Daeso at the hands of Jumong's grandson Muhyul. Jumong continues battling against Han China to consolidate his realm, and dies at the age of 40 after passing the crown of Goguryeo to Yuri.


title: Jumong (TV series)

text: "Jumong" was filmed on location at Yongin Daejanggeum Park in Cheoin District, Yongin, Gyeonggi Province, where other period dramas (such as "Dong Yi", "Moon Embracing the Sun" and "Queen Seondeok") were also filmed.


title: Jumong (TV series)

text: Broadcast rights for "Jumong" were sold to Iran (Channel 3), Turkey, Romania (TVR1), Kazakhstan, Georgia (Imedi TV), Armenia, Japan (Fuji TV), Mongolia, Taiwan, Hong Kong, Vietnam (VTV1), Singapore (Mediacorp Channel U), Indonesia, Thailand (Channel 3), Malaysia, Brunei, Philippines (GMA Network), Fiji (Fiji One), Iraqi Kurdistan, Afghanistan, Uzbekistan, Cambodia (Cambodian Television Network), United States (AZN Television), Myanmar (Myawaddy TV & MRTV-4), and Sri Lanka (Sri Lanka Rupavahini Corporation).


title: Jumong (TV series)

text: According to Reuters the most popular episodes of "Jumong" attracted over 90% of Iranian audience (compared to 40% in South Korea), propelling its lead actor Song Il-gook to superstar status in Iran.


title: Jumong (TV series)

text: Asia Television bought the Hong Kong broadcast rights; however, controversy surrounding its translation escalated debate about ATV's editorial independence in news and drama. The controversy primarily surrounded the cutting of certain segments, the alternative translation of place names and the alternative of a character's occupation. The changing of the word "nation" (in reference to Goguryeo) to "tribe" and the translation of the Han Dynasty as the "heavenly dynasty" has generated controversy about the station's editorial independence. This is related to controversies involving the governments of China and South Korea over the version of history of Goguryeo.


title: Coliform bacteria

text: Coliform bacteria are defined as either motile or non-motile Gram-negative non-spore forming Bacilli that possess β-galactosidase to produce acids and gases under their optimal growth temperature of 35-37°C. They can be aerobes or facultative aerobes, and are a commonly used indicator of low sanitary quality of foods, milk, and water. Coliforms can be found in the aquatic environment, in soil and on vegetation; they are universally present in large numbers in the feces of warm-blooded animals as they are known to inhabit the gastrointestinal system. While coliform bacteria are not normally causes of serious illness, they are easy to culture, and their presence is used to infer that other pathogenic organisms of fecal origin may be present in a sample, or that said sample is not safe to consume. Such pathogens include disease-causing bacteria, viruses, or protozoa and many multicellular parasites.


title: Coliform bacteria

text: "Escherichia coli" ("E. coli") can be distinguished from most other coliforms by its ability to ferment lactose at 44 °C in the fecal coliform test, and by its growth and color reaction on certain types of culture media. When cultured on an eosin methylene blue (EMB) plate, a positive result for "E. coli" is metallic green colonies on a dark purple medium. Also can be cultured on Tryptone Bile X-Glucuronide (TBX) to appear as blue or green colonies after incubation period of 24 hours. Escherichia coli have an incubation period of 12–72 hours with the optimal growth temperature being 37 °C. Unlike the general coliform group, "E. coli" are almost exclusively of fecal origin and their presence is thus an effective confirmation of fecal contamination. Most strains of "E. coli" are harmless, but some can cause serious illness in humans. Infection symptoms and signs include bloody diarrhea, stomach cramps, vomiting and occasionally, fever. The bacteria can also cause pneumonia, other respiratory illnesses and urinary tract infections.


title: Coliform bacteria

text: An easy way to differentiate between different types of coliform bacteria is by using an eosin methylene blue agar plate. This plate is partially inhibitory to Gram (+) bacteria, and will produce a color change in the Gram (-) bacterial colonies based on lactose fermentation abilities. Strong lactose fermenters will appear as dark blue/purple/black, and "E.coli" (which also ferments lactose) colonies will be dark colored, but will also appear to have a metallic green sheen. Other coliform bacteria will appear as thick, slimy colonies, with non-fermenters being colorless, and weak fermenters being pink.


title: Coliform bacteria

text: As of November 15th 2021, seven states in the USA declared ten cases of illnesses from an "E. coli" O157:H7 strain. These cases were reported from October 15, 2021 through October 27, 2021 and an investigation was carried out by the Minnesota Department of Agriculture and FDA. It was concluded that packages of spinach collected from homes of infected people were contaminated with a strain of "E. coli" that matched the strain causing illness. This was determined by performing whole genome sequencing on the strain extracted from the spinach and comparing it to the strain taken from infected individuals.


title: Coliform bacteria

text: As of February 7th, 2022, the provinces of Alberta and Saskatchewan in Canada reported a collective fourteen confirmed cases of "E. coli" O157 strain illnesses. These were reported between December 2021 and January 2022, and the Public Health Agency of Canada (PHAC), the Canadian Food Inspection Agency (CFIA), and Health Canada were able to determine a specific brand of Original Kimchi to be the source of the organism. On January 28, 2022 and February 6, 2022, the CFIA issued a recall on Hankook Original Kimchi.


title: Coliform bacteria

text: Amplification of the beta-galactosidase gene is used to detect coliforms in general, because all coliform organisms produce this compound. The amplification of the beta-D glucuronidase is used to detect "E. coli," or the amplification of their verotoxin gene(s) to detect verotoxin-producing "E. coli."


title: Coliform bacteria

text: Specific areas of the 16S rRNA in the "Enterobacteriaceae" genus are bound by oligonucleotide probes, which aids in monitoring the quality of drinking water. Specifically, "E. coli" is labelled with a soybean peroxidase-labeled peptide nucleic acid (PNA) probes that bind to a specific sequence in their 16S rRNA. When used in conjunction with a chemiluminescent substrate, light is produced where each colony of "E. coli" is located, indicating that they are present in the sample.


title: Coliform bacteria

text: The solid medium is used to grow lactose-fermenting coliforms and utilizes a neutral red pH indicator. Pink colonies appear when lactose is fermented and are surrounded by bile that has precipitated out. To confirm if these colonies are coliforms, they are transferred to brilliant green lactose bile (BGLB) and incubated. If gas is visible after incubation, it can be confirmed that the sample had coliforms present.


title: Coliform bacteria

text: Test samples are filtered through standard filter paper and then transferred to M-endo or LES Endo Agar mediums. Colonies appear pinkish-red with green metallic sheen after 22-24 hours of incubation. These colonies can be confirmed as coliforms if they are inoculated in Lauryl Tryptose (LST), produce gas, and then inoculated in BGLB. If there is gas production in the BGLB tubes, the test is positive for the presence of coliform bacteria.


title: Treaty of Lisbon

text: The Treaty of Lisbon (initially known as the Reform Treaty) is an international agreement that amends the two treaties which form the constitutional basis of the European Union (EU). The Treaty of Lisbon, which was signed by the EU member states on 13 December 2007, entered into force on 1 December 2009. It amends the Maastricht Treaty (1992), known in updated form as the Treaty on European Union (2007) or TEU, as well as the Treaty of Rome (1957), known in updated form as the Treaty on the Functioning of the European Union (2007) or TFEU. It also amends the attached treaty protocols as well as the Treaty establishing the European Atomic Energy Community (EURATOM).


title: Treaty of Lisbon

text: Prominent changes included the move from unanimity to qualified majority voting in at least 45 policy areas in the Council of Ministers, a change in calculating such a majority to a new double majority, a more powerful European Parliament forming a bicameral legislature alongside the Council of Ministers under the ordinary legislative procedure, a consolidated legal personality for the EU and the creation of a long-term President of the European Council and a High Representative of the Union for Foreign Affairs and Security Policy. The Treaty also made the Union's bill of rights, the Charter of Fundamental Rights, legally binding. For the first time, the treaty gave member states the explicit legal right to leave the EU, and established a procedure by which to do so.