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Stonington - Pine Point School announced Thursday that Head of School Stephen Bennhoff has stepped down, effective immediately.
The board said Thursday that it and "Mr. Bennhoff agreed that it was in the best interest of the school at this point in time for Mr. Bennhoff to step down from his role. This joint decision was an amicable one between the Board and Mr. Bennhoff. The Pine Point School appreciates deeply Mr. Bennhoff's efforts at the School during his tenure, and we wish him well in his future professional endeavors."
Bennhoff, who came to Pine Point three years ago from Rowland Hall School in Salt Lake City, Utah, could not be reached for comment. He replaced Paul Geise, who resigned after 12 years to be the headmaster of the Stanwich School in Greenwich.
Bennhoff's departure comes one week after the school announced the controversial firing of Susan Kozel, a 35-year staff member who was the head of Pine Point's Lower School. The decision angered some parents and staff members. The board said Thursday the two decisions were not connected.
Middle School Head Diana Owen, who will assume Kozel's duties, has now been named acting head of school. The school said it will immediately begin a search to name an interim head of school and then a permanent head of school, which has 62 staff members and 236 students from preschool to ninth grade.
A Thursday letter co-signed by Bennhoff and Board of Trustees President Jennifer Schwindt, and addressed to the "Pine Point School Community," stated that it was their charge to always act in the short and long-term interests of the school.
They wrote that the past three years have been "a dynamic period in the life of Pine Point" with retirements and hirings, ratification of a strategic plan and the earning of a 10-year reaccreditation from the Connecticut Association of Independent Schools.
The letter said there had also been "the unfortunate yet necessary" elimination of some part-time teaching positions because of smaller number of students, but school finances had stabilized and it can now be proud to offer the highest faculty salaries in the school's history.
"It has been a challenging yet inspiring period in the life of the school, resulting in the increased health of the school and a future that could only be described as bright," the letter states.
"We both believe in Pine Point's current and future strength. Pine Point's commitment to intimate classroom settings, rigorous curriculum, and a robust academic program of arts and athletics makes it the first choice of preschool - 9th grade for students in our region. Whoever is Head of School, our school remains committed to nurturing ethical global citizens who will be positive change-agents of tomorrow," it states.
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30 Seconds to Mars
On the '90s show My So-Called Life, Jared Leto courted Claire Danes via acoustic guitar. Leto has enjoyed heartthrob status ever since, appearing in small movies and Tiger Beat centerfolds. What My So-Called Life never revealed -- before being canceled because Claire was too big for the small screen -- was that dreamy Jared became a big Nine Inch Nails and Incubus fan.
For sure, Leto's NIN-styled, the-band-is-me moniker, 30 Seconds to Mars, looks cooler on an album cover than "Jared Leto" would. Like NIN, Jared keeps a four-piece in tow for live shows. Jared Leto doesn't want 30 Seconds to Mars to succeed or fail just because he's Jared Leto. This is evidenced by his tendency to lean into his microphone with Reznoresque urgency under the cover of a beautiful blond mane thick enough to make Fabio blush.
There aren't any properly developed songs here, just plenty of riffs every bit as catchy as they were the first time you heard them elsewhere. Supplementing 30 Seconds' scarcity of melody is a bevy of computerized effects and mechanized drum fills that reek of Nonpoint and BT. White male mid-adolescents will love this from start to finish, albeit with guilty smiles across their faces. It's all pretty silly, really, but Leto's charisma makes it competent enough to offer an emotional break to those given to taking music a little too seriously -- the type with Wilco and Coldplay wearing out welcomes in their changer.
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Restaurants in Albuquerque, Santa Fe and Northern New Mexico, searchable by cuisine and location, with ratings and reviews. Get educated before you eat!
Chen's Chinese Food Restaurant
235 Juan Tabo NENortheast Heights)
Albuquerque NM
(505) 298-9214
Mon-Thurs: 11am-9pm Fri-Sat: 11am-10pm Sun: noon-9pm (hours can change without notice)
Cuisine: Chinese
Chen's Chinese Food RestaurantThis little family-owned joint is a diamond in the rough. It kinda looks like hell on the outside but definitely tastes like heaven on the inside. This is where we go for the best egg drop soup and egg rolls. Plus, the waitstaff is extra friendly. (Alibi Staff, August 11, 2010)
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Each month various local small businesses, primarily lead by women, set up shop selling anything from terrariums and '60s dresses to the perfect red lipstick.
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For this Koyel there are 55 different names on Yasni.
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Denver, CO 80218
- Monday through Thursday 10 a.m. to 2 a.m.; Friday 10 a.m. to 4 a.m.; Saturday 8 a.m. to 4 a.m.; Sunday 8 a.m. to 2 a.m.
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The origins of the cliché that "everyone loves a villain" are not entirely clear, but it is clear that Hollywood loves portraying Wall Street's internal betrayal as well as the duping of Main Street on the big screen. The latest vintage of films are dedicated to recounting the financial debacle that occurred between 2007 and 2009, but tales of greed, excess and betrayal have been common themes over the years. Below are four films that are especially entertaining in lending insight into Wall Street's more extreme side.
TUTORIAL: Investing 101
Margin Call
This latest Wall Street caper was released on October 21, and follows a current string of films dedicated to recounting the credit crisis. According to online movie authority IMDb.com, the film "revolves around the key people at an investment bank over a 24-hour period during the early stages of the financial crisis." Related films include "Too Big to Fail," that covered late 2008 and the period in which Bear Stearns and Lehman Brothers ceased to exist, as well as "Inside Job" that, according to Netflix, set out to chronicle "deep-rooted corruption that led to the global economic meltdown of 2008." (These indicators can illuminate the depth and severity of problems in the credit markets. For more, see 5 Signs Of A Credit Crisis.)
Oliver Stone's Wall Street
The quintessential Wall Street movie was released in 1987 by Oliver Stone and aptly entitled "Wall Street." In it, and again according to IMDb.com, Charlie Sheen played a "young and impatient stockbroker … willing to do anything to get to the top, including trading on illegal inside information taken through a ruthless and greedy corporate raider who takes the youth under his wing."
The antagonist corporate raider was played by Michael Douglas and the character in question was none other than Gordon Gekko, who has become one of the greatest Wall Street villains ever on the silver screen. Now-famous quotes offered by the fictional Gekko since 1987, include the mention that "greed, for lack of a better word, is good" and that "if you need a friend, get a dog."
Douglas was able to reprise his role as Gekko 23 years later in Stone's follow-up to the original. "Wall Street: Money Never Sleeps" caught up with Gekko after a stint in prison for insider trading, and saw him rebuild his empire at the hands of the credit crisis in 2008. Charlie Sheen made a brief cameo in the second film but the primary protégé in this film was Shia LaBeouf.
Boiler Room
Boiler Room was released in 2000, and caught Wall Street in the midst of greed and excess related to the build-up of the dot-com bubble. Movie rating website Metacritic.com describes the film as "a riveting expose of one of the biggest and most lucrative scams in American history - and a dramatic look at a generation obsessed with the speed of wealth and success." (For related reading, see 5 Successful Companies That Survived The Dotcom Bubble.)
Starring Giovanni Ribisi and Vin Diesel, the movie followed a group of budding stock brokers using high-pressure sales tactics to dupe wealthy investors into buying stocks of now-defunct firms. Ribisi plays Seth Davis who ends up breaking the law to appease his boss and pursue his millions in commissions, but ends up helping the FBI bring down the fictional brokerage firm JT Marlin.
The Bottom Line
As with most Hollywood films, the main purpose of Wall Street flicks is to entertain and drive ticket sales. Of course, there are always instances where real life is as sensational as the worlds that directors and producers create through their camera lenses. For the most part, as with any other profession, the vast majority of individuals are ethical and law-abiding citizens that prefer an honest paycheck over striking it rich by any means possible.
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text:
|Publication number
|Publication type
|Application number
|Publication date
|May 15, 2001
|Filing date
|Jul 6, 1999
|Priority date
|Jul 6, 1998
|Fee status
|Also published as
|Publication number
|Martin M. Morici
|Original Assignee
|Alliedsignal Inc.
|Export Citation
|BiBTeX, EndNote, RefMan
|Patent Citations (11), Referenced by (60), Classifications (17), Legal Events (6)
|External Links: USPTO, USPTO Assignment, Espacenet
This application claims priority from U.S. Provisional Application No. 60/092,026, filed Jul. 6, 1998, which is hereby incorporated by reference for all purposes.
The present invention relates generally to aircraft positioning systems, and more particularly to a system and method for validating a position of an aircraft with cross-referenced information sources.
A major cause of aircraft accidents is the failure of an aircraft's positioning systems to adequately alert pilots of their true position, especially relative to variations in the terrain around them, such as with hills and mountains. Recent advances in aircraft navigation systems have done much to alleviate the problem of making a pilot aware an aircraft's position relative to terrain elements. Specifically, U.S. Pat. No. 5,839,080, owned by AlliedSignal, describes a terrain awareness system (TAS) to alert a pilot to terrain threats within a proximity of the aircraft. Further, Allied Signal's Enhanced Ground Proximity Warning System (EGPWS) provides a display of potentially hazardous terrain in an area surrounding a position of the aircraft as that position is reported by the flight management system (FMS) and/or other on-board navigation systems, such as a global positioning system (GPS) receiver. The terrain data is retrieved from a terrain database, such as a digital terrain elevation database (DTED).
Two sources of error may exist in conventional aircraft positioning systems. First, there may be errors in the terrain database. Second, there may be errors in the aircraft's reported position.
The present invention solves the problems of the prior art by utilizing an aircraft radar and a terrain database to correlate aircraft position information. The present invention can also use terrain data gathered from the aircraft radar to correlate and verify the data stored in a terrain database.
According to one aspect of the present invention an aircraft radar is utilized to obtain terrain reflectivity data. The terrain reflectivity data is then compared to terrain data stored in a terrain data base using a test statistic. The test statistic indicates the degree to which the radar terrain reflectivity data and the terrain data base data agree.
According to another aspect of the present invention, the invention utilizes an aircraft weather radar obtain the terrain radar reflectivity data. Use of the weather radar eliminates the need for separate dedicated radar and the additional cost and weight penalties associated therewith.
According to yet another aspect of the present invention, the invention further includes a tilt management system and/or method. The tilt management system permits the radar tilt angle to be set for optimal scanning of the terrain. The tilt management system also reduces pilot workload by avoiding the need to manually set the tilt.
According to still another aspect of the present invention, the present invention includes a scan interleaving function that permits the weather radar to scan for weather on certain sweeps and for terrain on other sweeps. The interleaving and tilt management function maximizes the utilization of the weather radar and automates the terrain data collection process, while not compromising the collection of weather data.
FIG. 1 is a simplified block diagram of a position validation system according to an embodiment of the present invention.
FIG. 2 is a process diagram to illustrate the major steps of a hypothesis testing method according to an embodiment of the present invention;
FIG. 3 is a simplified process diagram of a method of validating a position of an aircraft according to an embodiment of the present invention;
FIG. 4 is a process diagram showing a step of correlating flight position sensor data with a terrain database according to the present invention.
FIGS. 5A-C show examples of correlated data according to an embodiment of the present invention.
FIG. 6 shows the tilt angle offset reference as a function of altitude for take-off and landing according to the present invention.
FIG. 7 shows an example flow diagram for the computation of the antenna's tilt angle relative to the aircraft's local horizontal plane according to an embodiment of the present invention.
In the apparatus of FIG. 1, in an aircraft positioning system 100, a position validation apparatus is generally identified with the reference number 110. As will be discussed in more detail below, the position validation system accumulates position information from active sensors such as a radar system 120 and/or a ladar system 130, a navigational system (NAV) 140, and/or a flight management system (FMS) 150. Data accumulated from the navigational and positional systems are correlated with information provided by a digital terrain elevation database (DTED) in a process described in greater detail below.
Description of Inputs
The radar data from radar system 120 is preferably provided by a scanning, airborne weather radar. The data is collected at a set of uniformly spaced azimuth angles as the antenna is scanned in azimuth about the nose of the aircraft, at relatively shallow grazing angles (i.e. <15�). The radar produces a map of signal strength as a function of range and azimuth. The range is determined by the radar's range scale (RS) setting and the azimuth (AZ) is determined by the position of the scanning antenna at the time the pulse is transmitted. Pulsed repetition frequencies (PRF) ranging from 190 Hz to 6 KHz are preferably used in the correlation processing algorithm. The radar signal returns should be kept unambiguous in range. Consistent with typical weather radar displays, the signals provided to the correlation algorithm may be quantized in 10 dB steps relative to a sensitivity time control (STC) curve. This STC curve maintains a target of constant cross section to be maintained at the same quantization level independent of range to the target. A minimum threshold is set at approximately 10−4 to maintain a maximum probability of detecting a noise sample as a signal detection. Any cell exceeding this threshold is classified as a ground clutter return. Any cell not exceeding this threshold is classified as a noise return. In a preferred embodiment, the antenna's 3 dB beamwidth is ˜3� in both azimuth and elevation. The radar's range resolution is dependent on the radar's range scale and varies from 150 m to 2700 m.
The laser detection and ranging (ladar) data from the ladar system 130 is provided in an alternative embodiment, the data from which is provided in a similar manner as the radar data.
The FMS 150 provides positional information, and utilizes inputs from a satellite-based navigational system such as global positioning system (GPS) 155 that provides data such as the aircraft's longitude, latitude, altitude, groundtrack, and ground space. The FMS 150 may also be an FMS/IRS navigational system that is updated by the GPS, VOR/DME, and/or DME/DME. A terrain database, and/or an airport database, which are not shown, may also be part of the aircraft's on board systems. Additional sources of altitude data include the radar altimeter and barometric altimeter, also not shown for ease of illustration.
The NAV data includes aircraft dynamics such as roll, pitch and heading, roll rate, pitch rate, and heading rate. In a preferred embodiment, the navigation systems data is updated at 64 Hz increments.
The digital terrain elevation database (DTED) 160 identifies the maximum terrain height within a database cell size. Typical cell sizes for the database are 15 arc seconds, 30 arc seconds and 60 arc seconds in both latitude and longitude. In a preferred embodiment, the database is maintained in the WGS-84 system using latitude, longitude and elevations are maintained in meters above sea level. The terrain data may also be contained within and provided by a preexisting aircraft device, such as, for example, an Enhanced Ground Proximity Warning System (EGPWS) described above.
Hypothesis Testing
There is no way to definitely confirm an aircraft's reported position due to the statistical nature of the radar signals. However, by accumulating evidence from a variety of positional systems, it is possible to reject the aircraft's reported position as an unlikely event given active sensor data and DTED data. The method of the present invention is based on the statistical concept of hypothesis testing. A test statistic is defined which is used to determine if there is sufficient evidence to reject the conjecture that the information in the DTED along with the outputs from the aircraft's NAV, and FMS are consistent with the active sensor readings. This method is applicable to real beam radars, monopulse radars, and laser radars.
According to one embodiment of the present invention, the first step in the hypothesis-testing algorithm is to identify a null hypothesis (HO) and an alternative hypothesis (HA) where:
H0=the radar data; NAV data, FMS data and/or DTED data are consistent with the reported position;
HA=the radar data; NAV data, FMS data and/or DTED data are inconsistent with the reported position.
If any of the inputs are inconsistent with the others, to a predetermined degree, the null hypothesis should be rejected. FIG. 2 shows the major steps in a hypothesis testing method 200 according to an embodiment of the present invention.
At step 210 the Null (H0) and Alternative Models (HA) are identified. At step 220, a test statistic (t) is selected. The test statistic is defined as the fraction of the total number of classified radar map cells (signal or noise) that cannot be explained by the NAV data, FMS data, DTED data and radar system impulse response. The process by which cells are classified as unexplained noise or unexplained signal is described in the flow diagram in FIG. 4.
At step 230, a sample space for t is defined, and at step 240, a probability ρ is chosen, where ρ is the probability of falsely rejecting the Null Model H0. At step 250 the sample space is divided into acceptance and rejection regions such that
P(Rejection|H0)<ρ; and
P(Acceptance|HA) is as small as possible.
At step 260 a test statistic value=t is obtained and observed. At step 270 a processing decision is made, where if t is an element of the rejection region, H0 is rejected and HA will be concluded (or a rare event will be concluded to have occurred). If t is an element of the acceptance region, there is insufficient evidence to reject H0, or in other words, the data is consistent with H0 and the reported position is not rejected.
FIG. 3 illustrates a method 300 of validating a position of an aircraft according to an embodiment of the present invention. At step 310, signals representative of a reported position of the aircraft are received. The reported position is an approximation of an actual position and includes values representative of the positional data described above in reference to the data inputs. At step 320 active sensor signals are received that are representative of terrain of a map area surrounding the actual position of the aircraft. The actual position is unknown. At step 330 a database of terrain information, such as from DTED, for example, is accessed. The accessed area of interest for the terrain information corresponds to the map area provided by the active sensor in step 320. At step 340 the radar signals are correlated with the terrain information to compute a difference therebetween. The process of correlating is described in much greater detail with reference to FIG. 4. According to the information computed at step 340 a decision will be made at step 350 whether or not to reject the reported position according to a predetermined threshold.
A step in the hypothesis testing of the present invention is determining a suitable test statistic t. A preferred process 400 for determining t will now be described and with reference to FIG. 4. A data interface 401 collects data from one or more position information sources (402, 403 and 404). In particular, the data interface accesses a database 404 of terrain information that is cross-referenced to map area provided by the radar bus 403. The first step 405 in the computation of the test statistic is to down sample the radar data such that a pixel and/or cell resolution of the radar data is substantially matched to that of the terrain database. A sliding maximum filter is used in both range and azimuth to preferably achieve a 2:1 oversampling of the radar data to the terrain database at the maximum range of the radar range scale.
The define dilation filter step 415 receives radar parameters 410 from the active sensor source, and computes the radar's impulse response as a function of range and azimuth. The impulse response is then sorted into descending amplitude order and maintaining offsets in both range and azimuth, and listed in a memory of the position validation system. This ordered list will be used to determine if a signal cell can be explained by the radar's impulse response pattern. Next, at step 420, the azimuth range map is converted to terrain database pixels, by mapping the azimuth and range to a terrain database pixel position in the local ground plane.
At step 425 an upper & lower bound terrain database height is estimated for each range azimuth cell in the radar map. The upper bound is defined as the terrain database pixel height corresponding to the position of the center of the radar's range azimuth cell. The lower bound is defined as the minimum of the 4-connected cells in the terrain database surrounding the center of the radar's range azimuth cell less the DTED database quantization stepsize. A "Lake Test" is performed on the terrain database cell at step 430. A terrain database cell is declared to be "lake like" if its 8-connected neighbors are all of the same height. This is also true if the cell is known to be water, such as a lake or ocean, in anticipation of radar returns of terrain features that exhibit no significant elevation variation. Returns from small lakes, rivers and roadways cover a small fraction of the azimuth beam width, and are therefore "filled in" by antenna impulse response from the adjacent terrain returns. The radar returns from large bodies of water and paved surfaces at shallow grazing angles are characterized by a very small radar cross section (σo<−30 dBsm). These areas can be incorrectly interpreted as shadow regions or regions outside the antenna's elevation beam width if not accounted for specifically as in step 430.
For each range azimuth cell in the radar map, an upper bound and lower bound angle to the terrain database cell is computed using the upper and lower bound height estimates computed in step 435. The range gate (RG) position of each upper and lower bound angle estimate is corrected for the difference between ground range and slant range. The "lake-like" data determined in step 430 is also corrected for ground range to slant range conversion.
At step 440 the optimal tilt of the radar angle is computed, the result of which is provided back to the radar bus 403. A method of computing an optimal tilt angle is the subject of copending patent application No. 60/092,025, owned by AlliedSignal, incorporated by reference herein for all purposes. Two methods for use with the preferred embodiment of the present invention is described below with reference to FIGS. 6 and 7.
In the tilt angle schedule of FIG. 6, the tilt angle is established as a function of aircraft flight phase and altitude. In FIG. 6 the angle given provides the angle best suited to view atmospheric conditions with no or minimal ground clutter. This schedule can be used to provide a tilt angle offset reference for use by the present invention to tilt the weather radar an additional amount to view terrain.
FIG. 7 describes an alternate method for selecting tilt angle utilizing a terrain data base. The algorithm cam compute the terrain viewing angle directly for use during the terrain viewing radar scan, or as in the embodiment of FIG. 6, an offset angle based on the tilt angle utilized to view weather can be employed.
At step 445, several masks of the cells are defined. First, an edge mask is defined for determining a radar's sweep range, and therefore reliable cell sample size. For each cell, a designation of "true" is applied if the current cell is within half the effective azimuth beam width of the edge of the radar's azimuth sweep, or if the current cell is within half the effective range resolution of the maximum range. These "true" cells are declared to be unreliable sources of unexplained signal. This is due to the uncertainty of the presence of signal sources outside the radar's range azimuth coverage that could be the source of signal returns within this area. Second, a binary signal mask is defined where a particular cell is designated as "true" if the cell is greater than a minimum predetermined signal threshold; otherwise it is set to "false." A "true" value indicates that this cell contains signal returns. A "false" value indicates that this cell contains noise.
At step 450, a region of interest is determined. This step identifies the first radar range gate in each azimuth radial where signal is present, and where that signal corresponds to an angle to the terrain which is within the Null-to-Null beam width of the radar's elevation beam. This step also identifies the last range gate in each azimuth radial where a signal is present.
At step 455 an elevation angle to near-range detections is calculated. This step determines the upper and lower bound angles to the terrain which corresponds to the first N range gates beyond the first radar range gate defined in 3.3.8. The variable N represents the number of radar range samples within the range impulse response of the radar. In radials in which there is no signal present, the upper and lower bound angles are interpolated based on a median fit of the upper and lower bound angles in the radials containing valid data.
A region of interest mask is computed at step 460. During this step, a cell is sets to "true" if the cell is within the near range and far range limits defined in step 445. A separate mask sets a cell to "true" if the cell is within the near range and far range+N range cells as defined in step 450. The additional N cells represent an area of noise cells beyond the last signal cell that should be present to indicate a signal-to-noise transition area. If the far range+N cells exceeds a maximum predetermined range, the mask is only set to the maximum range gate available in the range azimuth map. In a preferred embodiment, N is 3� the range resolution of the radar.
At step 465, a number of signal cells is computed. This number, Nsignal, represents number of signal cells present in the radar range azimuth map and excluding the cells around the edges.
For the range of interest determined above, a number of visible cells is determined by defining two masks, at step 470. The first mask sets a cell to "true" if it is not shadowed by any other cell that contains radar signal return. If this is the case, the cell is considered visible along a direct line of sight of the aircraft. The step compares the lower bound angle to the current cell that contains signal against the maximum upper bound angle of all cells containing signal that are nearer in range than the current cell and in the same azimuth radial. This first mask will be used to determine if noise cells are unexplained due to direct line of sight visibility.
The second mask in step 470 sets a cell to "true" if it is possibly visible along a direct line of sight. The computation compares the upper bound angle to the current cell that contains signal against the maximum lower bound angle of all cells containing signal that are nearer in range than the current cell and in the same azimuth radial. This second mask will be used to determine if signal cells are unexplained due to the absence of even a possible direct line of sight.
In-beam and out-of-beam masks are computed at step 475 by defining two masks. The first mask sets a cell to "true" if the upper bound angle to the current cell is within the minimum beam width of the radar relative to the upper bound angle to the near cells as they are defined in step 455. This "In-Beam" mask will be used to determine if a noise cell is unexplained. The minimum beam width is preferably the 3 dB beam-width of the radar's elevation beam, but may be range scale dependent as well.
The second mask sets a cell to "true" if the upper bound angle to the cell is within the maximum beam width of the radar relative to the upper bound angle to the near cells defined in step 455. This "Out-Of-Beam" mask will be used to determine if a signal cell is unexplained. The maximum beam width is preferably the Null-to-Null beam-width of the radar's elevation beam.
At step 480, an explained signal mask is defined. For a cell to be declared an explained signal, Nexsig, signal must be present, as shown in step 445, the cell must at least possibly visible as determined by step 470, and the angle to the cell must not be "Out-of-Beam" as defined by the previous step. The total number of explained signals which are not near the edges, as defined in step 445, are maintained for use in the computation of the test statistic.
If a particular cell that contains signal cannot be explained by step 480, then a final test checks these cells' proximity to an explained cell, at step 485. This is done by progressing down the impulse response, step 415, from each explained signal cell, step 480, in order. Given a cell at point P with amplitude Q, it is expected that each step down the impulse response will reduce the amplitude due to point P. Once the amplitude of the test cell drops below the minimum signal strength, the area of support due to the point P ends. To compensate for the effects of receiver noise, the search is continued for an additional N dB once the minimum signal strength has been detected in the search pattern. All cells within this area of support that were previously unexplained are now explained by the radar's impulse response and recorded in a separate mask.
At step 490, unexplained signal cells, Nunexsig, are determined. This step identifies all signal cells that are not explained as in step 480, not determined as lake-like at step 430, and not edge cells as determined by step 445. For each unexplained signal cell, a weighting factor corresponding to the signal level in the unexplained signal cell is accumulated to indicate a score. This score is used in the final computation of the test statistic.
At step 495, all noise cells, Nnoise, for example non-signal cells that are within the region of interest, as determined by 450 and including the additional N range gates beyond the last signal cell. The number of these cells that are not edge cells is counted and are used in the computation of the test statistic.
Based on the number of noise cells determined in step 495, a number of unexplained noise cells, Nunexnoise, are identified, as shown in step 500. This step identifies all cells in the region of interest, including the additional N range gates beyond the last signal cell, that are "In-Beam", directly visible, and that correspond to the Noise cells identified in step 495.
At step 505, the number of unambiguous, unexplained noise cells is computed. This step identifies all unexplained noise cells in the region of interest that are not edge cells and are lake-like. Due to the fact that terrain cells covered with water can either behave as a reflective surface, for example choppy water, or non-reflective surface, for example calm water, such cells are ambiguous as to whether or not they are acceptable. These cells are counted and removed from the total number of noise cells to be used in the computation of the test statistic, Nambnoise.
Also at step 505, a second mask is created to identify all noise cells that are unexplained, and unambiguous. This mask is computed by identifying all non-lake-like cells that are not edge cells, and identified as unexplained Noise cells. The total number of unambiguous unexplained noise cells will be used in the computation of the test statistic, Nunexnoise.
At step 510, a number of cells outside the range of interest that should be seen as signal, Nsbesig, is computed. Step 505 identified all of the noise samples within the extended region of interest that are unambiguous and unexplained noise cells. Step 510 now identifies all of those noise samples in the forward region; those closer to the aircraft in range than the near range cells identified earlier in step 450. The purpose of this step is to identify noise cells that should have shadowed signal cells in the region of interest. The computation of this step is based on the upper bound angle to a cell in the forward region. This angle is compared to the upper bound angle at the signal leading edge. After removing lake-like cells, which should be noise anyway, and edge cells, the number of noise cells in the forward region that should have shadowed signal cells in the area of interest, is counted and provided for the Test Statistic computation at step 520.
The computation of the final test statistic step 520 is given by:
The denominator includes:
1) the total number of signal cells present in the entire range azimuth map, plus;
2) the total number of noise cells in the region of interest, plus
3) the total number of noise cells which should be signal in the forward region, minus
4) the total number of ambiguous noise cells, minus
5) the number of signal cells explained by line of sight computations.
The test statistic denominator ideally includes a minimum number of cells. Test statistic including fewer than the minimum number are of questionable accuracy. A preferred number of cells is 200, and is dependent on the radar's range scale.
The numerator is computed by summing the weighted number of all unexplained cells. This includes:
1) the weighted number of unexplained signal cells, plus
2) the total number of unexplained noise cells, plus
3) the total number of should be signal cells.
The test statistic of the present invention has several advantages. Specifically, the test statistic of the present invention will not reject an aircraft position given no discriminating ground information. The test statistic may reject or not reject the null hypothesis with limited discriminating ground information and in highly complex mountainous terrain, may be used to not only reject the aircraft position but may be used to correct the aircraft position relative to the terrain database reference.
With little or no variation in the ground within the radar map area, the test statistic is indifferent to latitude and longitude errors yet the algorithm is still sensitive to altitude errors. With the aircraft flying over level terrain, no CFIT-type danger is present to the aircraft even with aircraft position errors in latitude and longitude. No warnings are provided unless the altitude is significantly in error. With the aircraft flying over moderately hilly terrain, warnings are only produced if sufficient evidence has accumulated in the test statistic to reject the current aircraft position as a highly unlikely or rare event. When flying over unique terrain features, it is possible to not only reject the current aircraft position estimate but also to search the local DTED for the most probable aircraft position. Multiple acceptable positions can then be ruled out based on additional scans until only one alternative remains.
Another advantage of the algorithm of the present invention is its ability to exploit quantized radar signal levels. Areas that would typically be shadowed in the presence of small cross section targets can return signal when a large cross section target is present. By searching down the impulse response, it is possible to discriminate between a signal caused by a few local scattering centers or by an isolated large cross section target. Further, this enables the validation of position with radar antenna ranging in size from greater than 30″ diameter down to less than 12″ in diameter. The discrimination in this case is reduced as the antenna size is reduced due to beam broadening effects but the fill effects of the wider beam are also handled by the impulse response processing.
It is preferable that returns from ground clutter be detectable if they are visible along the line of sight (LOS) from the true aircraft position. Therefore, radar parameters are ideally selected to generate sufficient signal strength to exceed a clutter detection threshold on clutter-with-clutter cross sections (σ�) greater than −40 dBsm.
For clutter returns with RCS less than −40 dBsm, additional information can be used which does not depend on the amplitude of specific ground cells. Monopulse techniques known to those of skill in the art such as, for example, monopulse, sequential monopulse, amplitude lobing, and lobe on receive, that are used to determine sub-beam angle measurements, can be used with the present algorithm for rejecting terrain cells that are not consistent with the reported aircraft position and DTED height estimate. U.S. Pat. No. 5,831,570 to the same assignee describes one such monopulse technique.
Weather returns have the effect of raising the background noise level in a radar map. These weather returns are often characterized as having a Doppler component that distinguishes these returns as non-terrain features. By dynamically filtering the radar signal returns outside of main beam clutter, these reflecting free space features can be reduced significantly. The remaining weather features in the map will increase the probability of detecting noise as terrain reflections. The terrain signal threshold must be set sufficiently high to eliminate these weather returns to avoid false terrain signal readings caused by slow moving weather.
The known presence of water, for example oceans and very large lakes, can be strong features to rely upon especially in coastal areas. These features can also be incorporated into the test statistic in much the same way as the lake-like features are included, with the exception that noise aligned with a lake represents an explained noise sample—not an ambiguous unexplained noise sample. This has the effect of increasing the denominator and thus reducing the fraction in the test statistic, making this a more acceptable alignment than without knowing the position of lakes and large waterways.
FIGS. 5A-5C show examples of correlated data according to an embodiment of the present invention. FIG. 5A is a simulated radar data display showing four levels of display date where level 1 data is in the 10 dB signal band, level 2 is the 10 dB to 20 dB signal and level 3>20 dB signal level. FIG. 5B is simulated radar data superimposed on terrain database data at the aircraft's true location. Yellow contours indicate explained signal, Red contours indicate unexplained signal, Green contours indicate unexplained noise. The correlation score of 0.0 indicates all signal and noise cells explained by INS data, Radar Display Data, Terrain Database and Radar Parameters. FIG. 5C is simulated radar data superimposed on terrain database data with the aircraft position reported wit a 1 nmi error north and a 2 nmi error east of the aircraft's true location. Yellow contours indicate explained signal, Red contours indicate unexplained signal, Green contours indicate unexplained noise. The correlation score of 0.588 indicates a position error has been detected.
Tilt Angle Management and Sensor Orientation
The radar, lidar, weather radar employed as a terrain sensor is oriented relative to the terrain in a manner such that the sensor detects the terrain during its scan. A tilt angle set too high will cause the sensor to overshoot the terrain and no terrain data will be obtained. A tilt angle set too low may prevent the sensor from detecting high peaks located ahead of the aircraft. The tilt angle is therefore preferably automated to maximize the terrain data return. Furthermore, when the sensor is an aircraft weather radar automatic tilt management reduces pilot workload and enhances the ability of the weather radar to perform these multiple tasks. In addition, when a weather radar is used as the sensor of the present invention, the radar scans are preferably interleaved such that weather is obtained during certain scans and terrain data is obtained on other scans. U.S. Pat. No. 5,831,570, also describes one interleaving procedure useful for this purpose and said patent is incorporated herein by reference for all purposes.
One method for controlling tilt angle can be accomplished using an altitude schedule. In such an embodiment the tilt angle to view terrain is defined as a function of phase of flight and height above terrain. For Example, the radar tilt angle can be set at specified angle for take off and slewed down a predetermined number of degrees for each 1000 feet of altitude gain during climb out. The procedure can be reversed during descent.
According to another embodiment of the present invention, the terrain database itself is used to automatically calculate the tilt angle. One such database is included in the Enhanced Ground Proximity Warning System (EGPWS) manufactured by AlliedSignal. Other databases may be used. This embodiment of the invention utilizes the inputs described below. FIG. 6 describes a tilt angle schedule using these inputs to one embodiment of the invention.
1. aircraft altitude for example, relative to sea level (alt)
2. aircraft position for example, in latitude (lat)
3. aircraft position for example, in longitude (lng)
4. terrain database [trn (ilat, ilng)] where ilat represents the latitude index and ilng represents the longitude index
5. radar range scale in for example, nautical miles (10, 20, 40, 80, 160, 320) (RS)
6. database cell size in for example, nautical miles (0.25, 0.5, 1.0, 2.0, 4.0) (CS)
7. half-power elevation beam width of the weather radar for example, in degrees (i.e., the angular distance from the main antenna axis—measured in the vertical plane containing the main antenna axis—at which the signal strength falls to half the maximum value) (elbw)
8. aircraft heading relative to north (where positive is clockwise from north) (hdg)
The schedule of FIG. 7 first determines the values of the aircraft position variables. Then, for each latitude index within the radar range scale and within 90 degrees of the aircraft heading, the minimum and maximum longitude indices within those same limits are determined. The latitude index is then set to the minimum latitude index within the range scale and within 90 degrees of the aircraft heading and the longitude index is set to the minimum longitude index within the range scale and within 90 degrees of the aircraft heading and intersecting the latitude index. A maximum angle variable (MaxAng) is created and set to negative 90 degrees. The schedule of FIG. 7 then computes the distance between the aircraft and the terrain database point that corresponds to the latitude and longitude indices.
Compensating for earth curvature and radar diffraction according to techniques known to those of skill in the art, the elevation angle between the aircraft and the terrain database cell (ElAng) is measured and compared to the maximum angle variable. If the elevation angle is greater than the maximum angle, the maximum angle is set equal to the elevation angle. If the elevation angle is not greater than the maximum angle, the longitude index is increased by one. The longitude index is then compared to the maximum longitude index within the range scale and within 90 degrees of the aircraft heading and intersecting the latitude index. If the longitude index is not greater than the maximum longitude index, then the algorithm loops back to the computation of the distance between the aircraft and the terrain database point that corresponds to the latitude and longitude indices. If the longitude index is greater than the maximum longitude index, then the latitude index is increased by one. The latitude index is then compared to the maximum latitude index within the range scale and within 90 degrees of the aircraft heading. If the latitude index is not greater than the maximum latitude index, then longitude index is set equal to the minimum longitude index within the range scale and within 90 degrees of the aircraft heading and intersecting the latitude index and the method loops back to the computation of the distance between the aircraft and the terrain database point that corresponds to the latitude and longitude indices. If the latitude index is greater than the maximum latitude index, then the tilt angle is calculated by adding the maximum angle to the half-power elevation beam width of the weather radar.
According to one embodiment of the present invention, the weather radar's antenna tilt angle is recomputed each time the aircraft moves outside of a database cell, changes range scale or makes a change in aircraft heading.
The foregoing description of specific embodiments is provided to enable any person skilled in the art to make or use the present invention. The various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without the use of the inventive faculty. For example, the test statistic calculation may be performed in an on-board flight computer. Similarly, the invention may be embodied completely in software code residing in a computer memory and executed by a processor. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest possible scope consistent with the principles and novel features disclosed herein, and as defined by the following claims.
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|U.S. Classification
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|International Classification
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|European Classification
|Sep 30, 1999
Owner name: ALLIED SIGNAL INC., NEW JERSEY
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MORICI, MARTIN M.;REEL/FRAME:010279/0975
Effective date: 19990921
|Sep 29, 2004
|Fee payment
Year of fee payment: 4
|Sep 18, 2008
|Fee payment
Year of fee payment: 8
|Dec 24, 2012
|Maintenance fee reminder mailed
|May 15, 2013
|Lapse for failure to pay maintenance fees
|Jul 2, 2013
|Expired due to failure to pay maintenance fee
Effective date: 20130515


text:
Page 1
Neurobiology of Fibromyalgia Syndrome
In our review, the neurobiology of fibromyalgia syn-
drome (FM) is discussed in the context of what is known
about neural mechanisms of nociception and central
mechanisms of persistent pain conditions. We present a
general view of mechanisms of nociception, central tem-
poral summation, and central sensitization, and as well
compare sensory tests that examine these mechanisms in
normal pain-free human subjects. We then show how
amplification and other alterations of these mechanisms
apply to patients with FM.
Pain is usually related to impulse input that originates
from nociceptors in somatic or visceral tissues. The
impulses travel in myelinated (A-delta) and unmyelinated
(C) peripheral nerves, which first project to dorsal horn
nociceptor-specific neurons and wide dynamic range neu-
rons, before these second-order neurons transmit noci-
ceptive information to brain regions involved in pain,
including the thalamus, anterior cingulate cortex (ACC),
anterior insular cortex, and somatosensory cortex.
Nociceptor-specific neurons are so termed because they
respond predominantly to specific stimulus intensities
that either cause tissue damage or would cause tissue
damage if maintained over time. Wide dynamic range
neurons respond differentially over a very broad range of
stimulus intensities, from very gentle touch to stimuli that
cause tissue damage. Brain regions that receive input
from nociceptor-specific and wide dynamic range neu-
rons are related to sensory-discriminative, cognitive-eval-
uative, and affective processing of somatosensory noci-
ceptive input. The activation of these brain regions is
associated with pain experience and subsequent reflex
and protective behaviors. Importantly, the same brain
areas are likely to be involved in both acute and persist-
ent pain conditions.
Reflex and reflective behaviors that are aimed at elimi-
nating acute pain are not operative in chronic pain syn-
dromes including FM. Patients with FM, like most
chronic pain sufferers, do not display pain behaviors usu-
ally seen in acute pain, including increased perspiration,
hypertension, hyperthermia, and tachycardia. FM
patients have abnormal pain thresholds (hyperalgesia)
and report amplified pain with a variety of nociceptive
stimuli, including pressure, heat, and cold. Because no
consistent tissue abnormalities have been detected in FM,
central pain processing abnormalities need to be consid-
ered as important contributors to the heightened pain
sensitivity of these patients.
In our review, we also discuss recent evidence that the
clinical pain of patients with FM is related to abnormal
central temporal summation of pain, or "windup,"
evoked by repetitive stimulation of peripheral nociceptive
afferent neurons. Sensory testing experiments can be used
to demonstrate that abnormal windup of FM patients is
related to central nervous system (CNS) mechanisms of
central sensitization and persistent pain.
As background to the central sensory abnormalities of
FM patients, we discuss the normal role of nociceptors
and the central consequences of repetitive stimulation of
nociceptive neurons, and also describe how these mecha-
nisms appear to be distorted in FM patients.
DONALD D. PRICE and ROLAND STAUD
ABSTRACT. Accumulating evidence suggests that fibromyalgia syndrome (FM) pain is maintained by tonic impulse
input from deep tissues, such as muscle and joints, in combination with central sensitization mechanisms.
This nociceptive input may originate in peripheral tissues (trauma and infection) resulting in hyperalge-
sia/allodynia and/or central sensitization. Evidence for abnormal sensitization mechanisms in FM includes
enhanced temporal summation of delayed pain in response to repeated heat taps and repeated muscle taps,
as well as prolonged and enhanced painful after-sensations in FM patients but not control subjects.
Moreover, magnitudes of enhanced after-sensations are predictive of FM patients' ongoing clinical pain.
Such alterations of relevant pain mechanisms may lead to longterm neuroplastic changes that exceed the
antinociceptive capabilities of affected individuals, resulting in ever-increasing pain sensitivity and dysfunc-
tion. Future research needs to address the important role of abnormal nociception and/or antinociception
for chronic pain in FM. (J Rheumatol 2005;32 Suppl 75:22-28)
Key Indexing Terms:
From the Department of Neuroscience and Department of Medicine,
University of Florida, Gainesville, Florida, USA.
The authors have no conflict of financial interest related to the contents
of this article.
D.D. Price, PhD, Departments of Oral and Maxillofacial Surgery and
Neuroscience, Colleges of Dentistry and Medicine; R. Staud MD,
McKnight Brain Institute, University of Florida.
Address reprint requests to D.D. Price, Claude Denson Pepper Center,
PO Box 100416, Gainesville, FL 32610-0416. E-mail:
22 The Journal of Rheumatology 2005, Volume 32 Supplement 75
Personal non-commercial use only. The Journal of Rheumatology Copyright © 2005. All rights reserved.
Page 2
tinguished from second pain by most subjects. In contrast,
second pain (transmitted by unmyelinated C-fibers),
which is thought to be related to some chronic pain states,
is most frequently reported as dull, aching, or burn-
ing8,9,15-17. Similar to windup in the dorsal horn, second
pain increases in intensity when painful stimuli are applied
more often than once every 3 seconds. Windup of both
dorsal horn neurons and second pain can be inhibited by
application of NMDA receptor antagonists, including
dextromethorphan13and ketamine14. These parallels
between windup of dorsal horn neurons and second pain
almost certainly relate to the fact that dorsal horn neurons
that display windup project to pain-related areas of the
brain via several pathways. These pathways include not
only the well characterized spinothalamic tract, but also
the spinoreticular, spinohypothalamic, and the spinopon-
toamygdaloid pathways18. As a consequence of these mul-
tiple central projections, windup in the dorsal horn is like-
ly to be a major cause of windup of second pain. This is
critical, because windup is likely to be related to mecha-
nisms of central sensitization and hence some persistent
pain conditions19,20.
Several types of well controlled experimental stimuli can
reliably evoke windup of pain when applied to somatic tis-
sues of normal pain-free human subjects8,21,22, including
electrical stimulation of C nociceptors8, thermal stimula-
tion of C nociceptors17, and mechanical stimulation of
muscle nociceptors17,21-24. Figure 1 illustrates the charac-
teristics of windup of second pain evoked in normal pain-
free subjects by repeated thermal stimuli at 52°C.
Some persistent pain conditions including FM are
thought to be related to central mechanisms of sensitiza-
Nociception is associated with activation of a heteroge-
neous group of nociceptors that either express the neu-
ropeptide substance P (SP) and calcitonin gene related
peptide (CGRP) or isolectin B4(IB4)1. Their sensory neu-
rons terminate in the dorsal horn of the spinal cord,
mainly in laminae I and II and to a lesser degree in lami-
na V. These spinal cord regions also contain postsynaptic
neurons that express receptors implicated in nociceptive
transmission, such as SP, neurokinin 1, and neurokinin 2,
as well as glutaminergic receptors [N-methyl-D-aspartate
zolepropionic acid (AMPA), kainate, metabotropic].
TRPV-1 and TRPVL-1 receptors have been recently found
to be activated by noxious heat2, mechanical stimuli, or
low pH (acid-sensing ion channels)3,4. Although IB4-posi-
tive neurons can express several of these receptors, they are
the only ones to display the purino-receptor P2X35. This
latter receptor is activated by purines such as adenosine
triphosphate, which are frequently released after tissue
injury. Very little is known about the receptor expression of
neurons that innervate different tissues of the body, but
some tissues seem to contain special pain receptors. Much
information has been obtained from animal models in
which specific pain receptors are lacking. Inbred mice
without TRPV-1 receptors show decreased response to
noxious heat, but mechanical nociception is normal6.
Alternatively, mice without P2X3 receptors show no
reduced nociceptive behavior using known stimuli.
Using electrical shocks to a cutaneous nerve of cats,
Mendell and Wall found that repeated volleys of action
potentials in C-fibers resulted in a progressive increase in
the number of action potentials evoked in second-order
dorsal horn neurons7. Thus, with each successive C-fiber
volley, the evoked impulse discharge of second-order neu-
rons had a higher frequency and was more prolonged.
This progressive increase in response reflects slow tempo-
ral summation and has been termed windup. Windup has
been demonstrated to result from central rather than
peripheral nervous system mechanisms, mostly because
the input from peripheral nociceptors has been shown to
decline or stay the same with stimulus repetition8,9.
Windup of dorsal horn nociceptive neurons involving
NMDA receptor mechanisms10-12can be attenuated in a
dose-dependent manner by NMDA receptor antago-
This important mechanism of pain amplification,
which operates at least partly in the dorsal horn of the
spinal cord, precisely parallels the psychophysical charac-
teristics of temporal summation of second pain. First
pain, which is conducted by myelinated A-delta pain
fibers, is often described as sharp and can be readily dis-
Figure 1. Windup of second pain in healthy control subjects. Twenty
repetitive heat stimuli (52°C) were applied to the hand. Contact time
was 0.7 s; interstimulatory intervals (ISI) varied between 3 s and 6 s, as
shown at upper left. Pain intensity of test stimuli was rated on a verbal
rating scale of 0–100 (0 = no pain; 20 = minimal pain; 100 = unbearable
pain). Only repetitive stimuli at short ISI (3 s) resulted in a significant
increase of pain ratings, compared to long ISI, which produced minimal
pain sensations. From Vierck, et al. J Neurophysiol 1997;78:992- 100217.
Price and Staud: Neurobiology of FM23
Personal non-commercial use only. The Journal of Rheumatology Copyright © 2005. All rights reserved.
Page 3
The noninvasive method of summation of second pain or
windup has been used for the evaluation of central pain
processing in patients with FM41. This technique reveals
sensitivity to input from unmyelinated (C) afferents and
indicates the status of NMDA receptor systems, which
are implicated in a variety of chronic pain conditions.
Using a series of repetitive heat stimuli, we assessed
temporal summation of second pain in both healthy con-
trols and FM subjects41. Although windup pain was
evoked in both controls and patients, the perceived mag-
nitude of the sensory response to the first stimulus with-
in a series was greater for patients versus controls, as was
the degree of temporal summation within a series (Figure
2). Following the last stimulus in a series, painful windup
after-sensations rated at 15 and 30 seconds after the last
stimulus also were greater in magnitude and lasted longer
in FM subjects compared to controls. These results indi-
cate both augmentation and slower decay of nociceptive
input in FM patients and provide convincing evidence for
the presence of central sensitization.
The more prolonged after-sensations during windup
decay, however, may have been simply related to the fact
that greater windup occurred in FM patients. In order to
specifically test whether after-sensations are more intense
and take longer to decay in FM versus controls, we
adjusted the stimulus temperature in a manner that
evoked similar windup pain in both groups, as shown in
Figure 3. Despite similar temporal summation in both
groups, after-sensations were more intense and took
more than twice as long to decay in FM compared to
control subjects. Thus, the presence of enhanced windup
tion wherein nociceptive neurons of the dorsal horn
become hyperresponsive to nociceptive and sometimes
even non-nociceptive somatic stimulation25,26. Central
sensitization, in turn, is characterized by hyperalgesia
and allodynia. It is associated with enlarged receptive
fields and is often thought to occur as a consequence of
slow temporal summation of dorsal horn neurons to
repeated impulses from primary nociceptive neurons.
Since this repetitive impulse input can be elicited by
experimental laboratory stimuli, central sensitization and
windup can be studied in both normal pain-free subjects
and in patients with pain conditions such as FM.
Before we discuss the specific abnormalities of windup in
patients with FM, it would be useful to consider some
general sensory abnormalities and physiological charac-
teristics of these patients.
As described by Mease elsewhere in these proceedings,
FM is a chronic pain syndrome characterized by general-
ized pain, tender points (TP), disturbed sleep, and pro-
nounced fatigue. Pain in FM is consistently felt in the
musculature and may be related to sensitization of CNS
pain pathways. The pathogenesis of FM is unknown,
although abnormal concentration of CNS neuropeptides
and alterations of hypothalamic-pituitary-adrenal axis
have been described27-30. There is a large body of evi-
dence for a generalized lowering of pressure pain thresh-
olds in FM patients31-35. This mechanical allodynia of
FM patients, however, is not limited to TP, but appears to
be widespread35. In addition, almost all studies of FM
patients showed abnormalities of pain sensitivity while
using different methods of psychophysical testing. Most
investigations have utilized thermal (heat and cold),
mechanical, chemical, or electrical stimuli (single or
repetitive) to the skin or muscles.
The most frequently described sensory abnormality in
FM is the presence of TP. Eighteen areas have been
defined as tender points by the American College of
Rheumatology36. In addition to chronic widespread pain,
the presence of decreased mechanical pain thresholds
(tenderness) is required in at least 11 out of 18 TP for the
diagnosis of FM. Abnormal tenderness, however, does
not seem to be restricted to TP sites in FM but this
abnormality is most frequently generalized33,35. Most TP
are located at tendon insertion areas and have shown few
detectable tissue abnormalities. Analysis of algesic sub-
stances at TP sites by microdialysis showed no difference
between FM patients and healthy controls37and magnet-
ic resonance imaging of TP was also unable to detect any
specific abnormalities38. Although there is evidence for
local vasoconstriction of TP areas in FM39, these find-
ings may mostly reflect physical deconditioning40.
Figure 2. Windup of second pain in 10 female patients with FM and
healthy controls, using repetitive heat stimuli of 52°C to the hand.
Contact time of each stimulus was 0.7 s and ISI was 2 s. The rating of
only the first and last stimulus (n = 20) of each series is shown. Pain
intensity of test stimuli was rated on a verbal rating scale of 0–100 (see
definition, legend to Figure 1). From Vierck, et al. J Neurophysiol
24The Journal of Rheumatology 2005, Volume 32 Supplement 75
Personal non-commercial use only. The Journal of Rheumatology Copyright © 2005. All rights reserved.
Page 4
and prolonged stimulus-evoked after-sensations may be
functionally important for the initiation and mainte-
nance of persistent pain conditions such as FM.
Enhanced magnitudes of windup of second pain and
enhanced after-sensations are unlikely to be related to a
response bias because these characteristics are highly spe-
cific. For example, there is no reason why patients with
FM would expect enhanced after-sensations when their
magnitude of windup of second pain is adjusted to match
that of healthy subjects. Further, FM patients do not
complain of ongoing heat pain, but rather pain from
deep tissues. Thus, it is possible that central sensitization
is evoked and maintained by impulses in deep tissues and
thereby produces a central sensitized state during which
central neurons are hyperresponsive to multiple sensory
inputs, including cutaneous heat. There is recent evidence
for this kind of peripheral and central interaction in irri-
table bowel syndrome42. Given these considerations,
windup of heat-induced second pain may be a valuable
diagnostic test in FM patients.
If windup and central sensitization are important mech-
anisms for FM pain, one should expect robust associa-
tions between windup, windup decay, and clinical pain
intensity. In order to test the role of central pain mecha-
nisms such as windup and windup decay for clinical pain
we evaluated their usefulness as predictors of pain inten-
sity of patients with FM. We found that thermal windup
ratings correlated well with clinical pain intensity
(Pearson's r = 0.529), thus emphasizing the important
role of these pain mechanisms for FM. In addition, a sta-
tistical prediction model that included TP count, pain
related negative affect, and windup ratings accounted for
50% of the variance in FM clinical pain intensity43.
Importantly, each of these 3 factors was shown to statis-
tically account for unique amounts of variance in clinical
pain intensity. Windup after-sensation, however, was the
strongest predictor of clinical pain intensity, accounting
for most of the detectable variance (27%).
We have proposed that impulse input from deep tissues,
particularly muscles, reflects the peripheral source that
evokes and maintains central sensitization in FM23. This
proposal predicts that repeated stimulation of muscle
nociceptors would induce windup and central sensitiza-
tion in FM patients. Accordingly, we conducted a study
in which force-controlled mechanical stimulation was
applied to the flexor digitorum muscle of the forearm in
a series of brief contacts (15 stimuli, each of 1 second
duration, at 3 or 5 second interstimulus intervals)23.
These trains of stimuli were applied to both healthy con-
trols and FM patients, as shown in Figure 4. Similar to
cutaneous heat stimuli, FM patients demonstrated much
more pronounced windup as well as more intense and
Figure 3. The decay of pain after windup is slower for FM patients compared to healthy
control subjects (HC) even when the stimulus temperature is adjusted for the 2 groups to
produce the same magnitude of windup. After-sensations at 15 and 30 seconds after last
stimulus are painful for FM but not control subjects. The shaded area represents pain
threshold of the verbal pain rating scale (0-100) used for this study. Based on data from
Staud, et al43. Pain 2003;105:215-22.
Price and Staud: Neurobiology of FM 25
Personal non-commercial use only. The Journal of Rheumatology Copyright © 2005. All rights reserved.
Page 5
slower declining after-sensations compared to control
The explanation we have proposed thus far is that evoked
or ongoing impulse input from deep tissues induces and
maintains central sensitization in patients with FM. This
explanation raises the question of how this peripheral
input is generated. One obvious possibility is that of exer-
cise of muscles associated with abnormal sensitivity
(mechanical allodynia). Exercise has been shown to acti-
vate endogenous opioid and adrenergic systems, but
attenuation of experimental pain by exercise has not been
demonstrated consistently. We therefore assessed the
antinociceptive effects of exercise on windup, a psy-
chophysical method that is especially sensitive to opioid
modulation, in both healthy controls and FM patients44.
In addition, we determined the effects of exercise on
windup after-sensations evoked by repeated thermal
stimuli as described above. Temporal summation of late
pain sensations was substantially attenuated by strenuous
exercise in controls, but enhanced in individuals diag-
nosed with FM, an effect opposite to that obtained from
age/sex matched control subjects. This study indirectly
implicates a role of muscle nociceptors in FM pain and
also suggests that analgesic effects of exercise may be
lacking in FM patients.
Another line of evidence suggests that powerful
antinociceptive mechanisms become activated during
muscle contraction in healthy control subjects45.
Specifically, during isometric muscle contraction of con-
trol subjects, the mechanical pain threshold increases
over the contracted muscles as well as over distal muscle
areas46. In FM patients, however, the pain threshold
decreased over all areas, more pronounced proximal to
the muscle contraction compared to distal47. This exer-
cise related hyperalgesia may be the result of either sensi-
tization of mechanoreceptors in FM or dysfunction of
afferent pain inhibition activated by muscle contraction.
These findings may explain some of the increased pain
during exertion that is reported by FM patients.
The predominant symptom in FM is muscle pain and
stiffness, consistent with our explanation thus far. In fact,
many studies have focused on muscle tissue abnormalities
in FM48,49. Light and electron microscopic evaluations
identified moth-eaten and ragged-red fibers, indicating
uneven and proliferating mitochondria. This finding sug-
gested hypoperfusion of painful muscle tissues and has
led to examinations of muscle microcirculation. Oxygen
multipoint electrodes in trapezius muscles identified
abnormal tissue oxygen pressures in FM patients.
Because microcirculation of muscle tissues is controlled
by locally produced metabolites, humoral factors, and the
sympathetic nervous system, several investigations
focused on these possible mechanisms48,50,51. Sympathetic
ganglion blockade reversed the abnormal muscle find-
ings. In addition, the amount of SP, a neurotransmitter
stored within the afferent nociceptive fibers, was found to
be increased in the trapezius muscles of FM patients
compared to healthy controls52.
Skeletal muscles have different fiber types, including
type I, type IIA, and type IIB. Type I muscle fibers are
Figure 4. Pain ratings during a series of 15 repetitive muscle taps at ISI of 3 and 5 s, aver-
aged across all series presented to controls (HC) and patients with FM. The shaded area
identifies sensation levels below pain threshold (a rating of 20). Based on data from Staud,
et al23. Pain 2003;102:87-95.
26The Journal of Rheumatology 2005, Volume 32 Supplement 75
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text:
Welcome to Central District
SHAPE America Central District serves members in the following states:
Colorado, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota and Wyoming.
News and Announcements
- Call for Central District award nominations! The deadline for submission is October 15.
- Nominations for the 2016-17 Central District Leadership Council are due October 15. Download the nomination form here.
- The Fall 2015 issue of Insight, Central District's member newsletter, is now available online.
Mark you calendar for SHAPE America's SPEAK Out! Day
March 8-9, 2016
is your chance to represent your state, meet with members of Congress
and "speak out" in support of school health and physical education. Sign up starting December 1.


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Sounds Like: Eva Cassidy, Florence and the Machine, Björk, Fleetwood Mac, Stevie Nicks
Bio: All of the songs posted here are 1-take, and completely improvised with little to no effects added afterwards, and no editing. If you wish to hear my more songy-songs please venture to my site- www.nathalieelam.com.
Thanks for sharing in my passion!
"Fantastic shimmer and flashlight in your mu...See Full Bio


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Hold down Control (PC) or Command (Mac) key + mouseclick to select more than one option
Posted by Louie on 2014-12-08
Had dinner with three friends the food was good well prepared n cooked! However the portons were so small everyone left hungry! Pasta is not expensive a $14 plate should be full! Because if this I will not return


text:
Total 8 Jobs
Mega Walk in Drive for Admin Head
MT Educare Ltd. 0-5 years experience
We currently have opening for Admin Head in MT Educare Ltd (Mahesh Tutorials) at Western Zone : Kandivali, Malad East, Andheri Link Road,Vile parle, Santacruz, Mazgaon Total positions: 7 Candidates need to carry updated resume, previous offer letter, appointment letter, last ...
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Lead - UI Designer
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Walk in for Admin Head
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We currently have opening for Admin Head in MT Educare Ltd (Mahesh Tutorials) at Western Zone : Kandivali,Malad,Andheri, Goregaon, Vile parle,Bandra,Santacruz,Grant Road,Mazgaon Total positions: 11 Interested candidates can walk in for an interview with their CV s & a ...
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text: Stayed here with a tour group for a tour of Tuscany. Excellent location for day trips to Florence, Siena, Lucca, Pisa and many more Tuscan towns in the area. Staff was efficient and friendly. Rooms were older but charming and surprisingly enough with comfortable beds. Housekeeping staff kept bathroom amenities well-stocked and clean. The hotel is in a good location, with many cafe's and shops in walking distance. The breakfast needed a little boost, but we never went hungry. I am already planning a trip that includes a return to this hotel.


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